Detection and Counting of Orchard Trees from Vhr Images Using a Geometrical-Optical Model and Marked Template Matching

NASA Astrophysics Data System (ADS)

Maillard, Philippe; Gomes, Marília F.

2016-06-01

This article presents an original algorithm created to detect and count trees in orchards using very high resolution images. The algorithm is based on an adaptation of the "template matching" image processing approach, in which the template is based on a "geometricaloptical" model created from a series of parameters, such as illumination angles, maximum and ambient radiance, and tree size specifications. The algorithm is tested on four images from different regions of the world and different crop types. These images all have < 1 meter spatial resolution and were downloaded from the GoogleEarth application. Results show that the algorithm is very efficient at detecting and counting trees as long as their spectral and spatial characteristics are relatively constant. For walnut, mango and orange trees, the overall accuracy was clearly above 90%. However, the overall success rate for apple trees fell under 75%. It appears that the openness of the apple tree crown is most probably responsible for this poorer result. The algorithm is fully explained with a step-by-step description. At this stage, the algorithm still requires quite a bit of user interaction. The automatic determination of most of the required parameters is under development.

An approach to automated particle picking from electron micrographs based on reduced representation templates.

PubMed

Volkmann, Niels

2004-01-01

Reduced representation templates are used in a real-space pattern matching framework to facilitate automatic particle picking from electron micrographs. The procedure consists of five parts. First, reduced templates are constructed either from models or directly from the data. Second, a real-space pattern matching algorithm is applied using the reduced representations as templates. Third, peaks are selected from the resulting score map using peak-shape characteristics. Fourth, the surviving peaks are tested for distance constraints. Fifth, a correlation-based outlier screening is applied. Test applications to a data set of keyhole limpet hemocyanin particles indicate that the method is robust and reliable.

Improving and Assessing Planet Sensitivity of the GPI Exoplanet Survey with a Forward Model Matched Filter

DOE Office of Scientific and Technical Information (OSTI.GOV)

Ruffio, Jean-Baptiste; Macintosh, Bruce; Nielsen, Eric L.

We present a new matched-filter algorithm for direct detection of point sources in the immediate vicinity of bright stars. The stellar point-spread function (PSF) is first subtracted using a Karhunen-Loéve image processing (KLIP) algorithm with angular and spectral differential imaging (ADI and SDI). The KLIP-induced distortion of the astrophysical signal is included in the matched-filter template by computing a forward model of the PSF at every position in the image. To optimize the performance of the algorithm, we conduct extensive planet injection and recovery tests and tune the exoplanet spectra template and KLIP reduction aggressiveness to maximize the signal-to-noise ratiomore » (S/N) of the recovered planets. We show that only two spectral templates are necessary to recover any young Jovian exoplanets with minimal S/N loss. We also developed a complete pipeline for the automated detection of point-source candidates, the calculation of receiver operating characteristics (ROC), contrast curves based on false positives, and completeness contours. We process in a uniform manner more than 330 data sets from the Gemini Planet Imager Exoplanet Survey and assess GPI typical sensitivity as a function of the star and the hypothetical companion spectral type. This work allows for the first time a comparison of different detection algorithms at a survey scale accounting for both planet completeness and false-positive rate. We show that the new forward model matched filter allows the detection of 50% fainter objects than a conventional cross-correlation technique with a Gaussian PSF template for the same false-positive rate.« less

Study of image matching algorithm and sub-pixel fitting algorithm in target tracking

NASA Astrophysics Data System (ADS)

Yang, Ming-dong; Jia, Jianjun; Qiang, Jia; Wang, Jian-yu

2015-03-01

Image correlation matching is a tracking method that searched a region most approximate to the target template based on the correlation measure between two images. Because there is no need to segment the image, and the computation of this method is little. Image correlation matching is a basic method of target tracking. This paper mainly studies the image matching algorithm of gray scale image, which precision is at sub-pixel level. The matching algorithm used in this paper is SAD (Sum of Absolute Difference) method. This method excels in real-time systems because of its low computation complexity. The SAD method is introduced firstly and the most frequently used sub-pixel fitting algorithms are introduced at the meantime. These fitting algorithms can't be used in real-time systems because they are too complex. However, target tracking often requires high real-time performance, we put forward a fitting algorithm named paraboloidal fitting algorithm based on the consideration above, this algorithm is simple and realized easily in real-time system. The result of this algorithm is compared with that of surface fitting algorithm through image matching simulation. By comparison, the precision difference between these two algorithms is little, it's less than 0.01pixel. In order to research the influence of target rotation on precision of image matching, the experiment of camera rotation was carried on. The detector used in the camera is a CMOS detector. It is fixed to an arc pendulum table, take pictures when the camera rotated different angles. Choose a subarea in the original picture as the template, and search the best matching spot using image matching algorithm mentioned above. The result shows that the matching error is bigger when the target rotation angle is larger. It's an approximate linear relation. Finally, the influence of noise on matching precision was researched. Gaussian noise and pepper and salt noise were added in the image respectively, and the image was processed by mean filter and median filter, then image matching was processed. The result show that when the noise is little, mean filter and median filter can achieve a good result. But when the noise density of salt and pepper noise is bigger than 0.4, or the variance of Gaussian noise is bigger than 0.0015, the result of image matching will be wrong.

Rapid earthquake detection through GPU-Based template matching

NASA Astrophysics Data System (ADS)

Mu, Dawei; Lee, En-Jui; Chen, Po

2017-12-01

The template-matching algorithm (TMA) has been widely adopted for improving the reliability of earthquake detection. The TMA is based on calculating the normalized cross-correlation coefficient (NCC) between a collection of selected template waveforms and the continuous waveform recordings of seismic instruments. In realistic applications, the computational cost of the TMA is much higher than that of traditional techniques. In this study, we provide an analysis of the TMA and show how the GPU architecture provides an almost ideal environment for accelerating the TMA and NCC-based pattern recognition algorithms in general. So far, our best-performing GPU code has achieved a speedup factor of more than 800 with respect to a common sequential CPU code. We demonstrate the performance of our GPU code using seismic waveform recordings from the ML 6.6 Meinong earthquake sequence in Taiwan.

[Algorithm of locally adaptive region growing based on multi-template matching applied to automated detection of hemorrhages].

PubMed

Gao, Wei-Wei; Shen, Jian-Xin; Wang, Yu-Liang; Liang, Chun; Zuo, Jing

2013-02-01

In order to automatically detect hemorrhages in fundus images, and develop an automated diabetic retinopathy screening system, a novel algorithm named locally adaptive region growing based on multi-template matching was established and studied. Firstly, spectral signature of major anatomical structures in fundus was studied, so that the right channel among RGB channels could be selected for different segmentation objects. Secondly, the fundus image was preprocessed by means of HSV brightness correction and contrast limited adaptive histogram equalization (CLAHE). Then, seeds of region growing were founded out by removing optic disc and vessel from the resulting image of normalized cross-correlation (NCC) template matching on the previous preprocessed image with several templates. Finally, locally adaptive region growing segmentation was used to find out the exact contours of hemorrhages, and the automated detection of the lesions was accomplished. The approach was tested on 90 different resolution fundus images with variable color, brightness and quality. Results suggest that the approach could fast and effectively detect hemorrhages in fundus images, and it is stable and robust. As a result, the approach can meet the clinical demands.

Template matching for auditing hospital cost and quality.

PubMed

Silber, Jeffrey H; Rosenbaum, Paul R; Ross, Richard N; Ludwig, Justin M; Wang, Wei; Niknam, Bijan A; Mukherjee, Nabanita; Saynisch, Philip A; Even-Shoshan, Orit; Kelz, Rachel R; Fleisher, Lee A

2014-10-01

Develop an improved method for auditing hospital cost and quality. Medicare claims in general, gynecologic and urologic surgery, and orthopedics from Illinois, Texas, and New York between 2004 and 2006. A template of 300 representative patients was constructed and then used to match 300 patients at hospitals that had a minimum of 500 patients over a 3-year study period. From each of 217 hospitals we chose 300 patients most resembling the template using multivariate matching. The matching algorithm found close matches on procedures and patient characteristics, far more balanced than measured covariates would be in a randomized clinical trial. These matched samples displayed little to no differences across hospitals in common patient characteristics yet found large and statistically significant hospital variation in mortality, complications, failure-to-rescue, readmissions, length of stay, ICU days, cost, and surgical procedure length. Similar patients at different hospitals had substantially different outcomes. The template-matched sample can produce fair, directly standardized audits that evaluate hospitals on patients with similar characteristics, thereby making benchmarking more believable. Through examining matched samples of individual patients, administrators can better detect poor performance at their hospitals and better understand why these problems are occurring. © Health Research and Educational Trust.

Object matching using a locally affine invariant and linear programming techniques.

PubMed

Li, Hongsheng; Huang, Xiaolei; He, Lei

2013-02-01

In this paper, we introduce a new matching method based on a novel locally affine-invariant geometric constraint and linear programming techniques. To model and solve the matching problem in a linear programming formulation, all geometric constraints should be able to be exactly or approximately reformulated into a linear form. This is a major difficulty for this kind of matching algorithm. We propose a novel locally affine-invariant constraint which can be exactly linearized and requires a lot fewer auxiliary variables than other linear programming-based methods do. The key idea behind it is that each point in the template point set can be exactly represented by an affine combination of its neighboring points, whose weights can be solved easily by least squares. Errors of reconstructing each matched point using such weights are used to penalize the disagreement of geometric relationships between the template points and the matched points. The resulting overall objective function can be solved efficiently by linear programming techniques. Our experimental results on both rigid and nonrigid object matching show the effectiveness of the proposed algorithm.

3-D shape estimation of DNA molecules from stereo cryo-electron micro-graphs using a projection-steerable snake.

PubMed

Jacob, Mathews; Blu, Thierry; Vaillant, Cedric; Maddocks, John H; Unser, Michael

2006-01-01

We introduce a three-dimensional (3-D) parametric active contour algorithm for the shape estimation of DNA molecules from stereo cryo-electron micrographs. We estimate the shape by matching the projections of a 3-D global shape model with the micrographs; we choose the global model as a 3-D filament with a B-spline skeleton and a specified radial profile. The active contour algorithm iteratively updates the B-spline coefficients, which requires us to evaluate the projections and match them with the micrographs at every iteration. Since the evaluation of the projections of the global model is computationally expensive, we propose a fast algorithm based on locally approximating it by elongated blob-like templates. We introduce the concept of projection-steerability and derive a projection-steerable elongated template. Since the two-dimensional projections of such a blob at any 3-D orientation can be expressed as a linear combination of a few basis functions, matching the projections of such a 3-D template involves evaluating a weighted sum of inner products between the basis functions and the micrographs. The weights are simple functions of the 3-D orientation and the inner-products are evaluated efficiently by separable filtering. We choose an internal energy term that penalizes the average curvature magnitude. Since the exact length of the DNA molecule is known a priori, we introduce a constraint energy term that forces the curve to have this specified length. The sum of these energies along with the image energy derived from the matching process is minimized using the conjugate gradients algorithm. We validate the algorithm using real, as well as simulated, data and show that it performs well.

Modeling IrisCode and its variants as convex polyhedral cones and its security implications.

PubMed

Kong, Adams Wai-Kin

2013-03-01

IrisCode, developed by Daugman, in 1993, is the most influential iris recognition algorithm. A thorough understanding of IrisCode is essential, because over 100 million persons have been enrolled by this algorithm and many biometric personal identification and template protection methods have been developed based on IrisCode. This paper indicates that a template produced by IrisCode or its variants is a convex polyhedral cone in a hyperspace. Its central ray, being a rough representation of the original biometric signal, can be computed by a simple algorithm, which can often be implemented in one Matlab command line. The central ray is an expected ray and also an optimal ray of an objective function on a group of distributions. This algorithm is derived from geometric properties of a convex polyhedral cone but does not rely on any prior knowledge (e.g., iris images). The experimental results show that biometric templates, including iris and palmprint templates, produced by different recognition methods can be matched through the central rays in their convex polyhedral cones and that templates protected by a method extended from IrisCode can be broken into. These experimental results indicate that, without a thorough security analysis, convex polyhedral cone templates cannot be assumed secure. Additionally, the simplicity of the algorithm implies that even junior hackers without knowledge of advanced image processing and biometric databases can still break into protected templates and reveal relationships among templates produced by different recognition methods.

Template Matching for Auditing Hospital Cost and Quality

PubMed Central

Silber, Jeffrey H; Rosenbaum, Paul R; Ross, Richard N; Ludwig, Justin M; Wang, Wei; Niknam, Bijan A; Mukherjee, Nabanita; Saynisch, Philip A; Even-Shoshan, Orit; Kelz, Rachel R; Fleisher, Lee A

2014-01-01

Objective Develop an improved method for auditing hospital cost and quality. Data Sources/Setting Medicare claims in general, gynecologic and urologic surgery, and orthopedics from Illinois, Texas, and New York between 2004 and 2006. Study Design A template of 300 representative patients was constructed and then used to match 300 patients at hospitals that had a minimum of 500 patients over a 3-year study period. Data Collection/Extraction Methods From each of 217 hospitals we chose 300 patients most resembling the template using multivariate matching. Principal Findings The matching algorithm found close matches on procedures and patient characteristics, far more balanced than measured covariates would be in a randomized clinical trial. These matched samples displayed little to no differences across hospitals in common patient characteristics yet found large and statistically significant hospital variation in mortality, complications, failure-to-rescue, readmissions, length of stay, ICU days, cost, and surgical procedure length. Similar patients at different hospitals had substantially different outcomes. Conclusion The template-matched sample can produce fair, directly standardized audits that evaluate hospitals on patients with similar characteristics, thereby making benchmarking more believable. Through examining matched samples of individual patients, administrators can better detect poor performance at their hospitals and better understand why these problems are occurring. PMID:24588413

A model-based 3D template matching technique for pose acquisition of an uncooperative space object.

PubMed

Opromolla, Roberto; Fasano, Giancarmine; Rufino, Giancarlo; Grassi, Michele

2015-03-16

This paper presents a customized three-dimensional template matching technique for autonomous pose determination of uncooperative targets. This topic is relevant to advanced space applications, like active debris removal and on-orbit servicing. The proposed technique is model-based and produces estimates of the target pose without any prior pose information, by processing three-dimensional point clouds provided by a LIDAR. These estimates are then used to initialize a pose tracking algorithm. Peculiar features of the proposed approach are the use of a reduced number of templates and the idea of building the database of templates on-line, thus significantly reducing the amount of on-board stored data with respect to traditional techniques. An algorithm variant is also introduced aimed at further accelerating the pose acquisition time and reducing the computational cost. Technique performance is investigated within a realistic numerical simulation environment comprising a target model, LIDAR operation and various target-chaser relative dynamics scenarios, relevant to close-proximity flight operations. Specifically, the capability of the proposed techniques to provide a pose solution suitable to initialize the tracking algorithm is demonstrated, as well as their robustness against highly variable pose conditions determined by the relative dynamics. Finally, a criterion for autonomous failure detection of the presented techniques is presented.

A coarse-to-fine kernel matching approach for mean-shift based visual tracking

NASA Astrophysics Data System (ADS)

Liangfu, L.; Zuren, F.; Weidong, C.; Ming, J.

2009-03-01

Mean shift is an efficient pattern match algorithm. It is widely used in visual tracking fields since it need not perform whole search in the image space. It employs gradient optimization method to reduce the time of feature matching and realize rapid object localization, and uses Bhattacharyya coefficient as the similarity measure between object template and candidate template. This thesis presents a mean shift algorithm based on coarse-to-fine search for the best kernel matching. This paper researches for object tracking with large motion area based on mean shift. To realize efficient tracking of such an object, we present a kernel matching method from coarseness to fine. If the motion areas of the object between two frames are very large and they are not overlapped in image space, then the traditional mean shift method can only obtain local optimal value by iterative computing in the old object window area, so the real tracking position cannot be obtained and the object tracking will be disabled. Our proposed algorithm can efficiently use a similarity measure function to realize the rough location of motion object, then use mean shift method to obtain the accurate local optimal value by iterative computing, which successfully realizes object tracking with large motion. Experimental results show its good performance in accuracy and speed when compared with background-weighted histogram algorithm in the literature.

Hybrid geometric-random template-placement algorithm for gravitational wave searches from compact binary coalescences

NASA Astrophysics Data System (ADS)

Roy, Soumen; Sengupta, Anand S.; Thakor, Nilay

2017-05-01

Astrophysical compact binary systems consisting of neutron stars and black holes are an important class of gravitational wave (GW) sources for advanced LIGO detectors. Accurate theoretical waveform models from the inspiral, merger, and ringdown phases of such systems are used to filter detector data under the template-based matched-filtering paradigm. An efficient grid over the parameter space at a fixed minimal match has a direct impact on the overall time taken by these searches. We present a new hybrid geometric-random template placement algorithm for signals described by parameters of two masses and one spin magnitude. Such template banks could potentially be used in GW searches from binary neutron stars and neutron star-black hole systems. The template placement is robust and is able to automatically accommodate curvature and boundary effects with no fine-tuning. We also compare these banks against vanilla stochastic template banks and show that while both are equally efficient in the fitting-factor sense, the bank sizes are ˜25 % larger in the stochastic method. Further, we show that the generation of the proposed hybrid banks can be sped up by nearly an order of magnitude over the stochastic bank. Generic issues related to optimal implementation are discussed in detail. These improvements are expected to directly reduce the computational cost of gravitational wave searches.

Particle Filtering with Region-based Matching for Tracking of Partially Occluded and Scaled Targets*

PubMed Central

Nakhmani, Arie; Tannenbaum, Allen

2012-01-01

Visual tracking of arbitrary targets in clutter is important for a wide range of military and civilian applications. We propose a general framework for the tracking of scaled and partially occluded targets, which do not necessarily have prominent features. The algorithm proposed in the present paper utilizes a modified normalized cross-correlation as the likelihood for a particle filter. The algorithm divides the template, selected by the user in the first video frame, into numerous patches. The matching process of these patches by particle filtering allows one to handle the target’s occlusions and scaling. Experimental results with fixed rectangular templates show that the method is reliable for videos with nonstationary, noisy, and cluttered background, and provides accurate trajectories in cases of target translation, scaling, and occlusion. PMID:22506088

Human Actions Analysis: Templates Generation, Matching and Visualization Applied to Motion Capture of Highly-Skilled Karate Athletes

PubMed Central

Piekarczyk, Marcin; Ogiela, Marek R.

2017-01-01

The aim of this paper is to propose and evaluate the novel method of template generation, matching, comparing and visualization applied to motion capture (kinematic) analysis. To evaluate our approach, we have used motion capture recordings (MoCap) of two highly-skilled black belt karate athletes consisting of 560 recordings of various karate techniques acquired with wearable sensors. We have evaluated the quality of generated templates; we have validated the matching algorithm that calculates similarities and differences between various MoCap data; and we have examined visualizations of important differences and similarities between MoCap data. We have concluded that our algorithms works the best when we are dealing with relatively short (2–4 s) actions that might be averaged and aligned with the dynamic time warping framework. In practice, the methodology is designed to optimize the performance of some full body techniques performed in various sport disciplines, for example combat sports and martial arts. We can also use this approach to generate templates or to compare the correct performance of techniques between various top sportsmen in order to generate a knowledge base of reference MoCap videos. The motion template generated by our method can be used for action recognition purposes. We have used the DTW classifier with angle-based features to classify various karate kicks. We have performed leave-one-out action recognition for the Shorin-ryu and Oyama karate master separately. In this case, 100% actions were correctly classified. In another experiment, we used templates generated from Oyama master recordings to classify Shorin-ryu master recordings and vice versa. In this experiment, the overall recognition rate was 94.2%, which is a very good result for this type of complex action. PMID:29125560

Improving the convergence rate in affine registration of PET and SPECT brain images using histogram equalization.

PubMed

Salas-Gonzalez, D; Górriz, J M; Ramírez, J; Padilla, P; Illán, I A

2013-01-01

A procedure to improve the convergence rate for affine registration methods of medical brain images when the images differ greatly from the template is presented. The methodology is based on a histogram matching of the source images with respect to the reference brain template before proceeding with the affine registration. The preprocessed source brain images are spatially normalized to a template using a general affine model with 12 parameters. A sum of squared differences between the source images and the template is considered as objective function, and a Gauss-Newton optimization algorithm is used to find the minimum of the cost function. Using histogram equalization as a preprocessing step improves the convergence rate in the affine registration algorithm of brain images as we show in this work using SPECT and PET brain images.

BgCut: automatic ship detection from UAV images.

PubMed

Xu, Chao; Zhang, Dongping; Zhang, Zhengning; Feng, Zhiyong

2014-01-01

Ship detection in static UAV aerial images is a fundamental challenge in sea target detection and precise positioning. In this paper, an improved universal background model based on Grabcut algorithm is proposed to segment foreground objects from sea automatically. First, a sea template library including images in different natural conditions is built to provide an initial template to the model. Then the background trimap is obtained by combing some templates matching with region growing algorithm. The output trimap initializes Grabcut background instead of manual intervention and the process of segmentation without iteration. The effectiveness of our proposed model is demonstrated by extensive experiments on a certain area of real UAV aerial images by an airborne Canon 5D Mark. The proposed algorithm is not only adaptive but also with good segmentation. Furthermore, the model in this paper can be well applied in the automated processing of industrial images for related researches.

BgCut: Automatic Ship Detection from UAV Images

PubMed Central

Zhang, Zhengning; Feng, Zhiyong

2014-01-01

Ship detection in static UAV aerial images is a fundamental challenge in sea target detection and precise positioning. In this paper, an improved universal background model based on Grabcut algorithm is proposed to segment foreground objects from sea automatically. First, a sea template library including images in different natural conditions is built to provide an initial template to the model. Then the background trimap is obtained by combing some templates matching with region growing algorithm. The output trimap initializes Grabcut background instead of manual intervention and the process of segmentation without iteration. The effectiveness of our proposed model is demonstrated by extensive experiments on a certain area of real UAV aerial images by an airborne Canon 5D Mark. The proposed algorithm is not only adaptive but also with good segmentation. Furthermore, the model in this paper can be well applied in the automated processing of industrial images for related researches. PMID:24977182

Development of machine-vision system for gap inspection of muskmelon grafted seedlings.

PubMed

Liu, Siyao; Xing, Zuochang; Wang, Zifan; Tian, Subo; Jahun, Falalu Rabiu

2017-01-01

Grafting robots have been developed in the world, but some auxiliary works such as gap-inspecting for grafted seedlings still need to be done by human. An machine-vision system of gap inspection for grafted muskmelon seedlings was developed in this study. The image acquiring system consists of a CCD camera, a lens and a front white lighting source. The image of inspected gap was processed and analyzed by software of HALCON 12.0. The recognition algorithm for the system is based on principle of deformable template matching. A template should be created from an image of qualified grafted seedling gap. Then the gap image of the grafted seedling will be compared with the created template to determine their matching degree. Based on the similarity between the gap image of grafted seedling and the template, the matching degree will be 0 to 1. The less similar for the grafted seedling gap with the template the smaller of matching degree. Thirdly, the gap will be output as qualified or unqualified. If the matching degree of grafted seedling gap and the template is less than 0.58, or there is no match is found, the gap will be judged as unqualified; otherwise the gap will be qualified. Finally, 100 muskmelon seedlings were grafted and inspected to test the gap inspection system. Results showed that the gap inspection machine-vision system could recognize the gap qualification correctly as 98% of human vision. And the inspection speed of this system can reach 15 seedlings·min-1. The gap inspection process in grafting can be fully automated with this developed machine-vision system, and the gap inspection system will be a key step of a fully-automatic grafting robots.

Development of a two wheeled self balancing robot with speech recognition and navigation algorithm

NASA Astrophysics Data System (ADS)

Rahman, Md. Muhaimin; Ashik-E-Rasul, Haq, Nowab. Md. Aminul; Hassan, Mehedi; Hasib, Irfan Mohammad Al; Hassan, K. M. Rafidh

2016-07-01

This paper is aimed to discuss modeling, construction and development of navigation algorithm of a two wheeled self balancing mobile robot in an enclosure. In this paper, we have discussed the design of two of the main controller algorithms, namely PID algorithms, on the robot model. Simulation is performed in the SIMULINK environment. The controller is developed primarily for self-balancing of the robot and also it's positioning. As for the navigation in an enclosure, template matching algorithm is proposed for precise measurement of the robot position. The navigation system needs to be calibrated before navigation process starts. Almost all of the earlier template matching algorithms that can be found in the open literature can only trace the robot. But the proposed algorithm here can also locate the position of other objects in an enclosure, like furniture, tables etc. This will enable the robot to know the exact location of every stationary object in the enclosure. Moreover, some additional features, such as Speech Recognition and Object Detection, are added. For Object Detection, the single board Computer Raspberry Pi is used. The system is programmed to analyze images captured via the camera, which are then processed through background subtraction, followed by active noise reduction.

A template-finding algorithm and a comprehensive benchmark for homology modeling of proteins

PubMed Central

Vallat, Brinda Kizhakke; Pillardy, Jaroslaw; Elber, Ron

2010-01-01

The first step in homology modeling is to identify a template protein for the target sequence. The template structure is used in later phases of the calculation to construct an atomically detailed model for the target. We have built from the Protein Data Bank a large-scale learning set that includes tens of millions of pair matches that can be either a true template or a false one. Discriminatory learning (learning from positive and negative examples) is employed to train a decision tree. Each branch of the tree is a mathematical programming model. The decision tree is tested on an independent set from PDB entries and on the sequences of CASP7. It provides significant enrichment of true templates (between 50-100 percent) when compared to PSI-BLAST. The model is further verified by building atomically detailed structures for each of the tentative true templates with modeller. The probability that a true match does not yield an acceptable structural model (within 6Å RMSD from the native structure), decays linearly as a function of the TM structural-alignment score. PMID:18300226

Template protection and its implementation in 3D face recognition systems

NASA Astrophysics Data System (ADS)

Zhou, Xuebing

2007-04-01

As biometric recognition systems are widely applied in various application areas, security and privacy risks have recently attracted the attention of the biometric community. Template protection techniques prevent stored reference data from revealing private biometric information and enhance the security of biometrics systems against attacks such as identity theft and cross matching. This paper concentrates on a template protection algorithm that merges methods from cryptography, error correction coding and biometrics. The key component of the algorithm is to convert biometric templates into binary vectors. It is shown that the binary vectors should be robust, uniformly distributed, statistically independent and collision-free so that authentication performance can be optimized and information leakage can be avoided. Depending on statistical character of the biometric template, different approaches for transforming biometric templates into compact binary vectors are presented. The proposed methods are integrated into a 3D face recognition system and tested on the 3D facial images of the FRGC database. It is shown that the resulting binary vectors provide an authentication performance that is similar to the original 3D face templates. A high security level is achieved with reasonable false acceptance and false rejection rates of the system, based on an efficient statistical analysis. The algorithm estimates the statistical character of biometric templates from a number of biometric samples in the enrollment database. For the FRGC 3D face database, the small distinction of robustness and discriminative power between the classification results under the assumption of uniquely distributed templates and the ones under the assumption of Gaussian distributed templates is shown in our tests.

Fast-match on particle swarm optimization with variant system mechanism

NASA Astrophysics Data System (ADS)

Wang, Yuehuang; Fang, Xin; Chen, Jie

2018-03-01

Fast-Match is a fast and effective algorithm for approximate template matching under 2D affine transformations, which can match the target with maximum similarity without knowing the target gesture. It depends on the minimum Sum-of-Absolute-Differences (SAD) error to obtain the best affine transformation. The algorithm is widely used in the field of matching images because of its fastness and robustness. In this paper, our approach is to search an approximate affine transformation over Particle Swarm Optimization (PSO) algorithm. We treat each potential transformation as a particle that possesses memory function. Each particle is given a random speed and flows throughout the 2D affine transformation space. To accelerate the algorithm and improve the abilities of seeking the global excellent result, we have introduced the variant system mechanism on this basis. The benefit is that we can avoid matching with huge amount of potential transformations and falling into local optimal condition, so that we can use a few transformations to approximate the optimal solution. The experimental results prove that our method has a faster speed and a higher accuracy performance with smaller affine transformation space.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Colbert, C.; Moles, D.R.

This paper reports that the authors developed for the Air Force the Mark VI Personal Identity Verifier (PIV) for controlling access to a fixed or mobile ICBM site, a computer terminal, or mainframe. The Mark VI records the digitized silhouettes of four fingers of each hand on an AT and T smart card. Like fingerprints, finger shapes, lengths, and widths constitute an unguessable biometric password. A Security Officer enrolls an authorized person who places each hand, in turn, on a backlighted panel. An overhead scanning camera records the right and left hand reference templates on the smart card. The Securitymore » Officer adds to the card: name, personal identification number (PIN), and access restrictions such as permitted days of the week, times of day, and doors. To gain access, cardowner inserts card into a reader slot and places either hand on the panel. Resulting access template is matched to the reference template by three sameness algorithms. The final match score is an average of 12 scores (each of the four fingers, matched for shape, length, and width), expressing the degree of sameness. (A perfect match would score 100.00.) The final match score is compared to a predetermined score (threshold), generating an accept or reject decision.« less

MARZ: Manual and automatic redshifting software

NASA Astrophysics Data System (ADS)

Hinton, S. R.; Davis, Tamara M.; Lidman, C.; Glazebrook, K.; Lewis, G. F.

2016-04-01

The Australian Dark Energy Survey (OzDES) is a 100-night spectroscopic survey underway on the Anglo-Australian Telescope using the fibre-fed 2-degree-field (2dF) spectrograph. We have developed a new redshifting application MARZ with greater usability, flexibility, and the capacity to analyse a wider range of object types than the RUNZ software package previously used for redshifting spectra from 2dF. MARZ is an open-source, client-based, Javascript web-application which provides an intuitive interface and powerful automatic matching capabilities on spectra generated from the AAOmega spectrograph to produce high quality spectroscopic redshift measurements. The software can be run interactively or via the command line, and is easily adaptable to other instruments and pipelines if conforming to the current FITS file standard is not possible. Behind the scenes, a modified version of the AUTOZ cross-correlation algorithm is used to match input spectra against a variety of stellar and galaxy templates, and automatic matching performance for OzDES spectra has increased from 54% (RUNZ) to 91% (MARZ). Spectra not matched correctly by the automatic algorithm can be easily redshifted manually by cycling automatic results, manual template comparison, or marking spectral features.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Campbell, W; Miften, M; Jones, B

Purpose: Pancreatic SBRT relies on extremely accurate delivery of ablative radiation doses to the target, and intra-fractional tracking of fiducial markers can facilitate improvements in dose delivery. However, this requires algorithms that are able to find fiducial markers with high speed and accuracy. The purpose of this study was to develop a novel marker tracking algorithm that is robust against many of the common errors seen with traditional template matching techniques. Methods: Using CBCT projection images, a method was developed to create detailed template images of fiducial marker clusters without prior knowledge of the number of markers, their positions, ormore » their orientations. Briefly, the method (i) enhances markers in projection images, (ii) stabilizes the cluster’s position, (iii) reconstructs the cluster in 3D, and (iv) precomputes a set of static template images dependent on gantry angle. Furthermore, breathing data were used to produce 4D reconstructions of clusters, yielding dynamic template images dependent on gantry angle and breathing amplitude. To test these two approaches, static and dynamic templates were used to track the motion of marker clusters in more than 66,000 projection images from 75 CBCT scans of 15 pancreatic SBRT patients. Results: For both static and dynamic templates, the new technique was able to locate marker clusters present in projection images 100% of the time. The algorithm was also able to correctly locate markers in several instances where only some of the markers were visible due to insufficient field-of-view. In cases where clusters exhibited deformation and/or rotation during breathing, dynamic templates resulted in cross-correlation scores up to 70% higher than static templates. Conclusion: Patient-specific templates provided complete tracking of fiducial marker clusters in CBCT scans, and dynamic templates helped to provide higher cross-correlation scores for deforming/rotating clusters. This novel algorithm provides an extremely accurate method to detect fiducial markers during treatment. Research funding provided by Varian Medical Systems to Miften and Jones.« less

Retina verification system based on biometric graph matching.

PubMed

Lajevardi, Seyed Mehdi; Arakala, Arathi; Davis, Stephen A; Horadam, Kathy J

2013-09-01

This paper presents an automatic retina verification framework based on the biometric graph matching (BGM) algorithm. The retinal vasculature is extracted using a family of matched filters in the frequency domain and morphological operators. Then, retinal templates are defined as formal spatial graphs derived from the retinal vasculature. The BGM algorithm, a noisy graph matching algorithm, robust to translation, non-linear distortion, and small rotations, is used to compare retinal templates. The BGM algorithm uses graph topology to define three distance measures between a pair of graphs, two of which are new. A support vector machine (SVM) classifier is used to distinguish between genuine and imposter comparisons. Using single as well as multiple graph measures, the classifier achieves complete separation on a training set of images from the VARIA database (60% of the data), equaling the state-of-the-art for retina verification. Because the available data set is small, kernel density estimation (KDE) of the genuine and imposter score distributions of the training set are used to measure performance of the BGM algorithm. In the one dimensional case, the KDE model is validated with the testing set. A 0 EER on testing shows that the KDE model is a good fit for the empirical distribution. For the multiple graph measures, a novel combination of the SVM boundary and the KDE model is used to obtain a fair comparison with the KDE model for the single measure. A clear benefit in using multiple graph measures over a single measure to distinguish genuine and imposter comparisons is demonstrated by a drop in theoretical error of between 60% and more than two orders of magnitude.

GASS-WEB: a web server for identifying enzyme active sites based on genetic algorithms.

PubMed

Moraes, João P A; Pappa, Gisele L; Pires, Douglas E V; Izidoro, Sandro C

2017-07-03

Enzyme active sites are important and conserved functional regions of proteins whose identification can be an invaluable step toward protein function prediction. Most of the existing methods for this task are based on active site similarity and present limitations including performing only exact matches on template residues, template size restraints, despite not being capable of finding inter-domain active sites. To fill this gap, we proposed GASS-WEB, a user-friendly web server that uses GASS (Genetic Active Site Search), a method based on an evolutionary algorithm to search for similar active sites in proteins. GASS-WEB can be used under two different scenarios: (i) given a protein of interest, to match a set of specific active site templates; or (ii) given an active site template, looking for it in a database of protein structures. The method has shown to be very effective on a range of experiments and was able to correctly identify >90% of the catalogued active sites from the Catalytic Site Atlas. It also managed to achieve a Matthew correlation coefficient of 0.63 using the Critical Assessment of protein Structure Prediction (CASP 10) dataset. In our analysis, GASS was ranking fourth among 18 methods. GASS-WEB is freely available at http://gass.unifei.edu.br/. © The Author(s) 2017. Published by Oxford University Press on behalf of Nucleic Acids Research.

Visual environment recognition for robot path planning using template matched filters

NASA Astrophysics Data System (ADS)

Orozco-Rosas, Ulises; Picos, Kenia; Díaz-Ramírez, Víctor H.; Montiel, Oscar; Sepúlveda, Roberto

2017-08-01

A visual approach in environment recognition for robot navigation is proposed. This work includes a template matching filtering technique to detect obstacles and feasible paths using a single camera to sense a cluttered environment. In this problem statement, a robot can move from the start to the goal by choosing a single path between multiple possible ways. In order to generate an efficient and safe path for mobile robot navigation, the proposal employs a pseudo-bacterial potential field algorithm to derive optimal potential field functions using evolutionary computation. Simulation results are evaluated in synthetic and real scenes in terms of accuracy of environment recognition and efficiency of path planning computation.

A multi-emitter fitting algorithm for potential live cell super-resolution imaging over a wide range of molecular densities.

PubMed

Takeshima, T; Takahashi, T; Yamashita, J; Okada, Y; Watanabe, S

2018-05-25

Multi-emitter fitting algorithms have been developed to improve the temporal resolution of single-molecule switching nanoscopy, but the molecular density range they can analyse is narrow and the computation required is intensive, significantly limiting their practical application. Here, we propose a computationally fast method, wedged template matching (WTM), an algorithm that uses a template matching technique to localise molecules at any overlapping molecular density from sparse to ultrahigh density with subdiffraction resolution. WTM achieves the localization of overlapping molecules at densities up to 600 molecules μm -2 with a high detection sensitivity and fast computational speed. WTM also shows localization precision comparable with that of DAOSTORM (an algorithm for high-density super-resolution microscopy), at densities up to 20 molecules μm -2 , and better than DAOSTORM at higher molecular densities. The application of WTM to a high-density biological sample image demonstrated that it resolved protein dynamics from live cell images with subdiffraction resolution and a temporal resolution of several hundred milliseconds or less through a significant reduction in the number of camera images required for a high-density reconstruction. WTM algorithm is a computationally fast, multi-emitter fitting algorithm that can analyse over a wide range of molecular densities. The algorithm is available through the website. https://doi.org/10.17632/bf3z6xpn5j.1. © 2018 The Authors. Journal of Microscopy published by JohnWiley & Sons Ltd on behalf of Royal Microscopical Society.

Wolf Attack Probability: A Theoretical Security Measure in Biometric Authentication Systems

NASA Astrophysics Data System (ADS)

Une, Masashi; Otsuka, Akira; Imai, Hideki

This paper will propose a wolf attack probability (WAP) as a new measure for evaluating security of biometric authentication systems. The wolf attack is an attempt to impersonate a victim by feeding “wolves” into the system to be attacked. The “wolf” means an input value which can be falsely accepted as a match with multiple templates. WAP is defined as a maximum success probability of the wolf attack with one wolf sample. In this paper, we give a rigorous definition of the new security measure which gives strength estimation of an individual biometric authentication system against impersonation attacks. We show that if one reestimates using our WAP measure, a typical fingerprint algorithm turns out to be much weaker than theoretically estimated by Ratha et al. Moreover, we apply the wolf attack to a finger-vein-pattern based algorithm. Surprisingly, we show that there exists an extremely strong wolf which falsely matches all templates for any threshold value.

Mouse EEG spike detection based on the adapted continuous wavelet transform

NASA Astrophysics Data System (ADS)

Tieng, Quang M.; Kharatishvili, Irina; Chen, Min; Reutens, David C.

2016-04-01

Objective. Electroencephalography (EEG) is an important tool in the diagnosis of epilepsy. Interictal spikes on EEG are used to monitor the development of epilepsy and the effects of drug therapy. EEG recordings are generally long and the data voluminous. Thus developing a sensitive and reliable automated algorithm for analyzing EEG data is necessary. Approach. A new algorithm for detecting and classifying interictal spikes in mouse EEG recordings is proposed, based on the adapted continuous wavelet transform (CWT). The construction of the adapted mother wavelet is founded on a template obtained from a sample comprising the first few minutes of an EEG data set. Main Result. The algorithm was tested with EEG data from a mouse model of epilepsy and experimental results showed that the algorithm could distinguish EEG spikes from other transient waveforms with a high degree of sensitivity and specificity. Significance. Differing from existing approaches, the proposed approach combines wavelet denoising, to isolate transient signals, with adapted CWT-based template matching, to detect true interictal spikes. Using the adapted wavelet constructed from a predefined template, the adapted CWT is calculated on small EEG segments to fit dynamical changes in the EEG recording.

Image-driven Population Analysis through Mixture Modeling

PubMed Central

Sabuncu, Mert R.; Balci, Serdar K.; Shenton, Martha E.; Golland, Polina

2009-01-01

We present iCluster, a fast and efficient algorithm that clusters a set of images while co-registering them using a parameterized, nonlinear transformation model. The output of the algorithm is a small number of template images that represent different modes in a population. This is in contrast with traditional, hypothesis-driven computational anatomy approaches that assume a single template to construct an atlas. We derive the algorithm based on a generative model of an image population as a mixture of deformable template images. We validate and explore our method in four experiments. In the first experiment, we use synthetic data to explore the behavior of the algorithm and inform a design choice on parameter settings. In the second experiment, we demonstrate the utility of having multiple atlases for the application of localizing temporal lobe brain structures in a pool of subjects that contains healthy controls and schizophrenia patients. Next, we employ iCluster to partition a data set of 415 whole brain MR volumes of subjects aged 18 through 96 years into three anatomical subgroups. Our analysis suggests that these subgroups mainly correspond to age groups. The templates reveal significant structural differences across these age groups that confirm previous findings in aging research. In the final experiment, we run iCluster on a group of 15 patients with dementia and 15 age-matched healthy controls. The algorithm produces two modes, one of which contains dementia patients only. These results suggest that the algorithm can be used to discover sub-populations that correspond to interesting structural or functional “modes.” PMID:19336293

Template match using local feature with view invariance

NASA Astrophysics Data System (ADS)

Lu, Cen; Zhou, Gang

2013-10-01

Matching the template image in the target image is the fundamental task in the field of computer vision. Aiming at the deficiency in the traditional image matching methods and inaccurate matching in scene image with rotation, illumination and view changing, a novel matching algorithm using local features are proposed in this paper. The local histograms of the edge pixels (LHoE) are extracted as the invariable feature to resist view and brightness changing. The merits of the LHoE is that the edge points have been little affected with view changing, and the LHoE can resist not only illumination variance but also the polution of noise. For the process of matching are excuded only on the edge points, the computation burden are highly reduced. Additionally, our approach is conceptually simple, easy to implement and do not need the training phase. The view changing can be considered as the combination of rotation, illumination and shear transformation. Experimental results on simulated and real data demonstrated that the proposed approach is superior to NCC(Normalized cross-correlation) and Histogram-based methods with view changing.

On the precision of automated activation time estimation

NASA Technical Reports Server (NTRS)

Kaplan, D. T.; Smith, J. M.; Rosenbaum, D. S.; Cohen, R. J.

1988-01-01

We examined how the assignment of local activation times in epicardial and endocardial electrograms is affected by sampling rate, ambient signal-to-noise ratio, and sinx/x waveform interpolation. Algorithms used for the estimation of fiducial point locations included dV/dtmax, and a matched filter detection algorithm. Test signals included epicardial and endocardial electrograms overlying both normal and infarcted regions of dog myocardium. Signal-to-noise levels were adjusted by combining known data sets with white noise "colored" to match the spectral characteristics of experimentally recorded noise. For typical signal-to-noise ratios and sampling rates, the template-matching algorithm provided the greatest precision in reproducibly estimating fiducial point location, and sinx/x interpolation allowed for an additional significant improvement. With few restrictions, combining these two techniques may allow for use of digitization rates below the Nyquist rate without significant loss of precision.

Deformable templates guided discriminative models for robust 3D brain MRI segmentation.

PubMed

Liu, Cheng-Yi; Iglesias, Juan Eugenio; Tu, Zhuowen

2013-10-01

Automatically segmenting anatomical structures from 3D brain MRI images is an important task in neuroimaging. One major challenge is to design and learn effective image models accounting for the large variability in anatomy and data acquisition protocols. A deformable template is a type of generative model that attempts to explicitly match an input image with a template (atlas), and thus, they are robust against global intensity changes. On the other hand, discriminative models combine local image features to capture complex image patterns. In this paper, we propose a robust brain image segmentation algorithm that fuses together deformable templates and informative features. It takes advantage of the adaptation capability of the generative model and the classification power of the discriminative models. The proposed algorithm achieves both robustness and efficiency, and can be used to segment brain MRI images with large anatomical variations. We perform an extensive experimental study on four datasets of T1-weighted brain MRI data from different sources (1,082 MRI scans in total) and observe consistent improvement over the state-of-the-art systems.

Automatic detection of motor unit innervation zones of the external anal sphincter by multichannel surface EMG.

PubMed

Ullah, Khalil; Cescon, Corrado; Afsharipour, Babak; Merletti, Roberto

2014-12-01

A method to detect automatically the location of innervation zones (IZs) from 16-channel surface EMG (sEMG) recordings from the external anal sphincter (EAS) muscle is presented in order to guide episiotomy during child delivery. The new algorithm (2DCorr) is applied to individual motor unit action potential (MUAP) templates and is based on bidimensional cross correlation between the interpolated image of each MUAP template and two images obtained by flipping upside-down (around a horizontal axis) and left-right (around a vertical axis) the original one. The method was tested on 640 simulated MUAP templates of the sphincter muscle and compared with previously developed algorithms (Radon Transform, RT; Template Match, TM). Experimental signals were detected from the EAS of 150 subjects using an intra-anal probe with 16 equally spaced circumferential electrodes. The results of the three algorithms were compared with the actual IZ location (simulated signal) and with IZ location provided by visual analysis (VA) (experimental signals). For simulated signals, the inter quartile error range (IQR) between the estimated and the actual locations of the IZ was 0.20, 0.23, 0.42, and 2.32 interelectrode distances (IED) for the VA, 2DCorr, RT and TM methods respectively. Copyright © 2014 Elsevier Ltd. All rights reserved.

Learning templates for artistic portrait lighting analysis.

PubMed

Chen, Xiaowu; Jin, Xin; Wu, Hongyu; Zhao, Qinping

2015-02-01

Lighting is a key factor in creating impressive artistic portraits. In this paper, we propose to analyze portrait lighting by learning templates of lighting styles. Inspired by the experience of artists, we first define several novel features that describe the local contrasts in various face regions. The most informative features are then selected with a stepwise feature pursuit algorithm to derive the templates of various lighting styles. After that, the matching scores that measure the similarity between a testing portrait and those templates are calculated for lighting style classification. Furthermore, we train a regression model by the subjective scores and the feature responses of a template to predict the score of a portrait lighting quality. Based on the templates, a novel face illumination descriptor is defined to measure the difference between two portrait lightings. Experimental results show that the learned templates can well describe the lighting styles, whereas the proposed approach can assess the lighting quality of artistic portraits as human being does.

[Affine transformation-based automatic registration for peripheral digital subtraction angiography (DSA)].

PubMed

Kong, Gang; Dai, Dao-Qing; Zou, Lu-Min

2008-07-01

In order to remove the artifacts of peripheral digital subtraction angiography (DSA), an affine transformation-based automatic image registration algorithm is introduced here. The whole process is described as follows: First, rectangle feature templates are constructed with their centers of the extracted Harris corners in the mask, and motion vectors of the central feature points are estimated using template matching technology with the similarity measure of maximum histogram energy. And then the optimal parameters of the affine transformation are calculated with the matrix singular value decomposition (SVD) method. Finally, bilinear intensity interpolation is taken to the mask according to the specific affine transformation. More than 30 peripheral DSA registrations are performed with the presented algorithm, and as the result, moving artifacts of the images are removed with sub-pixel precision, and the time consumption is less enough to satisfy the clinical requirements. Experimental results show the efficiency and robustness of the algorithm.

Vibration extraction based on fast NCC algorithm and high-speed camera.

PubMed

Lei, Xiujun; Jin, Yi; Guo, Jie; Zhu, Chang'an

2015-09-20

In this study, a high-speed camera system is developed to complete the vibration measurement in real time and to overcome the mass introduced by conventional contact measurements. The proposed system consists of a notebook computer and a high-speed camera which can capture the images as many as 1000 frames per second. In order to process the captured images in the computer, the normalized cross-correlation (NCC) template tracking algorithm with subpixel accuracy is introduced. Additionally, a modified local search algorithm based on the NCC is proposed to reduce the computation time and to increase efficiency significantly. The modified algorithm can rapidly accomplish one displacement extraction 10 times faster than the traditional template matching without installing any target panel onto the structures. Two experiments were carried out under laboratory and outdoor conditions to validate the accuracy and efficiency of the system performance in practice. The results demonstrated the high accuracy and efficiency of the camera system in extracting vibrating signals.

An Improved Vision-based Algorithm for Unmanned Aerial Vehicles Autonomous Landing

NASA Astrophysics Data System (ADS)

Zhao, Yunji; Pei, Hailong

In vision-based autonomous landing system of UAV, the efficiency of target detecting and tracking will directly affect the control system. The improved algorithm of SURF(Speed Up Robust Features) will resolve the problem which is the inefficiency of the SURF algorithm in the autonomous landing system. The improved algorithm is composed of three steps: first, detect the region of the target using the Camshift; second, detect the feature points in the region of the above acquired using the SURF algorithm; third, do the matching between the template target and the region of target in frame. The results of experiment and theoretical analysis testify the efficiency of the algorithm.

A robust and non-invertible fingerprint template for fingerprint matching system.

PubMed

Trivedi, Amit Kumar; Thounaojam, Dalton Meitei; Pal, Shyamosree

2018-05-20

Fingerprint Recognition System is widely deployed in variety of application domain, ranging from forensic to mobile phones. Its widespread deployment in various applications were person authentication are required, has caused concern that a leaked fingerprint template may be used to reconstruct the original fingerprint and the reconstructed fingerprint can be used to circumvent all the applications the person is enrolled. In this paper, a non-invertible fingerprint template that stores only the relative geometric information about the minutiae points is proposed. The spatial location of the minutiae points in original fingerprint and its orientations are not available in the proposed template which makes it impossible to estimate the orientation of fingerprint from the template. The proposed template is invariant to rotation, translation and distortion and immune to reconstruction algorithm. The proposed system is experimented using standard FVC2000 database and yields better results in terms of EER and FMR as compared with latest techniques. Copyright © 2018 Elsevier B.V. All rights reserved.

Automated main-chain model building by template matching and iterative fragment extension.

PubMed

Terwilliger, Thomas C

2003-01-01

An algorithm for the automated macromolecular model building of polypeptide backbones is described. The procedure is hierarchical. In the initial stages, many overlapping polypeptide fragments are built. In subsequent stages, the fragments are extended and then connected. Identification of the locations of helical and beta-strand regions is carried out by FFT-based template matching. Fragment libraries of helices and beta-strands from refined protein structures are then positioned at the potential locations of helices and strands and the longest segments that fit the electron-density map are chosen. The helices and strands are then extended using fragment libraries consisting of sequences three amino acids long derived from refined protein structures. The resulting segments of polypeptide chain are then connected by choosing those which overlap at two or more C(alpha) positions. The fully automated procedure has been implemented in RESOLVE and is capable of model building at resolutions as low as 3.5 A. The algorithm is useful for building a preliminary main-chain model that can serve as a basis for refinement and side-chain addition.

SpikeGUI: software for rapid interictal discharge annotation via template matching and online machine learning.

PubMed

Jing Jin; Dauwels, Justin; Cash, Sydney; Westover, M Brandon

2014-01-01

Detection of interictal discharges is a key element of interpreting EEGs during the diagnosis and management of epilepsy. Because interpretation of clinical EEG data is time-intensive and reliant on experts who are in short supply, there is a great need for automated spike detectors. However, attempts to develop general-purpose spike detectors have so far been severely limited by a lack of expert-annotated data. Huge databases of interictal discharges are therefore in great demand for the development of general-purpose detectors. Detailed manual annotation of interictal discharges is time consuming, which severely limits the willingness of experts to participate. To address such problems, a graphical user interface "SpikeGUI" was developed in our work for the purposes of EEG viewing and rapid interictal discharge annotation. "SpikeGUI" substantially speeds up the task of annotating interictal discharges using a custom-built algorithm based on a combination of template matching and online machine learning techniques. While the algorithm is currently tailored to annotation of interictal epileptiform discharges, it can easily be generalized to other waveforms and signal types.

SpikeGUI: Software for Rapid Interictal Discharge Annotation via Template Matching and Online Machine Learning

PubMed Central

Jin, Jing; Dauwels, Justin; Cash, Sydney; Westover, M. Brandon

2015-01-01

Detection of interictal discharges is a key element of interpreting EEGs during the diagnosis and management of epilepsy. Because interpretation of clinical EEG data is time-intensive and reliant on experts who are in short supply, there is a great need for automated spike detectors. However, attempts to develop general-purpose spike detectors have so far been severely limited by a lack of expert-annotated data. Huge databases of interictal discharges are therefore in great demand for the development of general-purpose detectors. Detailed manual annotation of interictal discharges is time consuming, which severely limits the willingness of experts to participate. To address such problems, a graphical user interface “SpikeGUI” was developed in our work for the purposes of EEG viewing and rapid interictal discharge annotation. “SpikeGUI” substantially speeds up the task of annotating interictal discharges using a custom-built algorithm based on a combination of template matching and online machine learning techniques. While the algorithm is currently tailored to annotation of interictal epileptiform discharges, it can easily be generalized to other waveforms and signal types. PMID:25570976

Visual Object Recognition and Tracking of Tools

NASA Technical Reports Server (NTRS)

English, James; Chang, Chu-Yin; Tardella, Neil

2011-01-01

A method has been created to automatically build an algorithm off-line, using computer-aided design (CAD) models, and to apply this at runtime. The object type is discriminated, and the position and orientation are identified. This system can work with a single image and can provide improved performance using multiple images provided from videos. The spatial processing unit uses three stages: (1) segmentation; (2) initial type, pose, and geometry (ITPG) estimation; and (3) refined type, pose, and geometry (RTPG) calculation. The image segmentation module files all the tools in an image and isolates them from the background. For this, the system uses edge-detection and thresholding to find the pixels that are part of a tool. After the pixels are identified, nearby pixels are grouped into blobs. These blobs represent the potential tools in the image and are the product of the segmentation algorithm. The second module uses matched filtering (or template matching). This approach is used for condensing synthetic images using an image subspace that captures key information. Three degrees of orientation, three degrees of position, and any number of degrees of freedom in geometry change are included. To do this, a template-matching framework is applied. This framework uses an off-line system for calculating template images, measurement images, and the measurements of the template images. These results are used online to match segmented tools against the templates. The final module is the RTPG processor. Its role is to find the exact states of the tools given initial conditions provided by the ITPG module. The requirement that the initial conditions exist allows this module to make use of a local search (whereas the ITPG module had global scope). To perform the local search, 3D model matching is used, where a synthetic image of the object is created and compared to the sensed data. The availability of low-cost PC graphics hardware allows rapid creation of synthetic images. In this approach, a function of orientation, distance, and articulation is defined as a metric on the difference between the captured image and a synthetic image with an object in the given orientation, distance, and articulation. The synthetic image is created using a model that is looked up in an object-model database. A composable software architecture is used for implementation. Video is first preprocessed to remove sensor anomalies (like dead pixels), and then is processed sequentially by a prioritized list of tracker-identifiers.

2D/3D Visual Tracker for Rover Mast

NASA Technical Reports Server (NTRS)

Bajracharya, Max; Madison, Richard W.; Nesnas, Issa A.; Bandari, Esfandiar; Kunz, Clayton; Deans, Matt; Bualat, Maria

2006-01-01

A visual-tracker computer program controls an articulated mast on a Mars rover to keep a designated feature (a target) in view while the rover drives toward the target, avoiding obstacles. Several prior visual-tracker programs have been tested on rover platforms; most require very small and well-estimated motion between consecutive image frames a requirement that is not realistic for a rover on rough terrain. The present visual-tracker program is designed to handle large image motions that lead to significant changes in feature geometry and photometry between frames. When a point is selected in one of the images acquired from stereoscopic cameras on the mast, a stereo triangulation algorithm computes a three-dimensional (3D) location for the target. As the rover moves, its body-mounted cameras feed images to a visual-odometry algorithm, which tracks two-dimensional (2D) corner features and computes their old and new 3D locations. The algorithm rejects points, the 3D motions of which are inconsistent with a rigid-world constraint, and then computes the apparent change in the rover pose (i.e., translation and rotation). The mast pan and tilt angles needed to keep the target centered in the field-of-view of the cameras (thereby minimizing the area over which the 2D-tracking algorithm must operate) are computed from the estimated change in the rover pose, the 3D position of the target feature, and a model of kinematics of the mast. If the motion between the consecutive frames is still large (i.e., 3D tracking was unsuccessful), an adaptive view-based matching technique is applied to the new image. This technique uses correlation-based template matching, in which a feature template is scaled by the ratio between the depth in the original template and the depth of pixels in the new image. This is repeated over the entire search window and the best correlation results indicate the appropriate match. The program could be a core for building application programs for systems that require coordination of vision and robotic motion.

Moving Object Detection Using a Parallax Shift Vector Algorithm

NASA Astrophysics Data System (ADS)

Gural, Peter S.; Otto, Paul R.; Tedesco, Edward F.

2018-07-01

There are various algorithms currently in use to detect asteroids from ground-based observatories, but they are generally restricted to linear or mildly curved movement of the target object across the field of view. Space-based sensors in high inclination, low Earth orbits can induce significant parallax in a collected sequence of images, especially for objects at the typical distances of asteroids in the inner solar system. This results in a highly nonlinear motion pattern of the asteroid across the sensor, which requires a more sophisticated search pattern for detection processing. Both the classical pattern matching used in ground-based asteroid search and the more sensitive matched filtering and synthetic tracking techniques, can be adapted to account for highly complex parallax motion. A new shift vector generation methodology is discussed along with its impacts on commonly used detection algorithms, processing load, and responsiveness to asteroid track reporting. The matched filter, template generator, and pattern matcher source code for the software described herein are available via GitHub.

Automated side-chain model building and sequence assignment by template matching.

PubMed

Terwilliger, Thomas C

2003-01-01

An algorithm is described for automated building of side chains in an electron-density map once a main-chain model is built and for alignment of the protein sequence to the map. The procedure is based on a comparison of electron density at the expected side-chain positions with electron-density templates. The templates are constructed from average amino-acid side-chain densities in 574 refined protein structures. For each contiguous segment of main chain, a matrix with entries corresponding to an estimate of the probability that each of the 20 amino acids is located at each position of the main-chain model is obtained. The probability that this segment corresponds to each possible alignment with the sequence of the protein is estimated using a Bayesian approach and high-confidence matches are kept. Once side-chain identities are determined, the most probable rotamer for each side chain is built into the model. The automated procedure has been implemented in the RESOLVE software. Combined with automated main-chain model building, the procedure produces a preliminary model suitable for refinement and extension by an experienced crystallographer.

Component-based target recognition inspired by human vision

NASA Astrophysics Data System (ADS)

Zheng, Yufeng; Agyepong, Kwabena

2009-05-01

In contrast with machine vision, human can recognize an object from complex background with great flexibility. For example, given the task of finding and circling all cars (no further information) in a picture, you may build a virtual image in mind from the task (or target) description before looking at the picture. Specifically, the virtual car image may be composed of the key components such as driver cabin and wheels. In this paper, we propose a component-based target recognition method by simulating the human recognition process. The component templates (equivalent to the virtual image in mind) of the target (car) are manually decomposed from the target feature image. Meanwhile, the edges of the testing image can be extracted by using a difference of Gaussian (DOG) model that simulates the spatiotemporal response in visual process. A phase correlation matching algorithm is then applied to match the templates with the testing edge image. If all key component templates are matched with the examining object, then this object is recognized as the target. Besides the recognition accuracy, we will also investigate if this method works with part targets (half cars). In our experiments, several natural pictures taken on streets were used to test the proposed method. The preliminary results show that the component-based recognition method is very promising.

Comparative Performance Analysis of Different Fingerprint Biometric Scanners for Patient Matching.

PubMed

Kasiiti, Noah; Wawira, Judy; Purkayastha, Saptarshi; Were, Martin C

2017-01-01

Unique patient identification within health services is an operational challenge in healthcare settings. Use of key identifiers, such as patient names, hospital identification numbers, national ID, and birth date are often inadequate for ensuring unique patient identification. In addition approximate string comparator algorithms, such as distance-based algorithms, have proven suboptimal for improving patient matching, especially in low-resource settings. Biometric approaches may improve unique patient identification. However, before implementing the technology in a given setting, such as health care, the right scanners should be rigorously tested to identify an optimal package for the implementation. This study aimed to investigate the effects of factors such as resolution, template size, and scan capture area on the matching performance of different fingerprint scanners for use within health care settings. Performance analysis of eight different scanners was tested using the demo application distributed as part of the Neurotech Verifinger SDK 6.0.

Dynamic time warping and machine learning for signal quality assessment of pulsatile signals.

PubMed

Li, Q; Clifford, G D

2012-09-01

In this work, we describe a beat-by-beat method for assessing the clinical utility of pulsatile waveforms, primarily recorded from cardiovascular blood volume or pressure changes, concentrating on the photoplethysmogram (PPG). Physiological blood flow is nonstationary, with pulses changing in height, width and morphology due to changes in heart rate, cardiac output, sensor type and hardware or software pre-processing requirements. Moreover, considerable inter-individual and sensor-location variability exists. Simple template matching methods are therefore inappropriate, and a patient-specific adaptive initialization is therefore required. We introduce dynamic time warping to stretch each beat to match a running template and combine it with several other features related to signal quality, including correlation and the percentage of the beat that appeared to be clipped. The features were then presented to a multi-layer perceptron neural network to learn the relationships between the parameters in the presence of good- and bad-quality pulses. An expert-labeled database of 1055 segments of PPG, each 6 s long, recorded from 104 separate critical care admissions during both normal and verified arrhythmic events, was used to train and test our algorithms. An accuracy of 97.5% on the training set and 95.2% on test set was found. The algorithm could be deployed as a stand-alone signal quality assessment algorithm for vetting the clinical utility of PPG traces or any similar quasi-periodic signal.

Automated extraction of pleural effusion in three-dimensional thoracic CT images

NASA Astrophysics Data System (ADS)

Kido, Shoji; Tsunomori, Akinori

2009-02-01

It is important for diagnosis of pulmonary diseases to measure volume of accumulating pleural effusion in threedimensional thoracic CT images quantitatively. However, automated extraction of pulmonary effusion correctly is difficult. Conventional extraction algorithm using a gray-level based threshold can not extract pleural effusion from thoracic wall or mediastinum correctly, because density of pleural effusion in CT images is similar to those of thoracic wall or mediastinum. So, we have developed an automated extraction method of pulmonary effusion by use of extracting lung area with pleural effusion. Our method used a template of lung obtained from a normal lung for segmentation of lungs with pleural effusions. Registration process consisted of two steps. First step was a global matching processing between normal and abnormal lungs of organs such as bronchi, bones (ribs, sternum and vertebrae) and upper surfaces of livers which were extracted using a region-growing algorithm. Second step was a local matching processing between normal and abnormal lungs which were deformed by the parameter obtained from the global matching processing. Finally, we segmented a lung with pleural effusion by use of the template which was deformed by two parameters obtained from the global matching processing and the local matching processing. We compared our method with a conventional extraction method using a gray-level based threshold and two published methods. The extraction rates of pleural effusions obtained from our method were much higher than those obtained from other methods. Automated extraction method of pulmonary effusion by use of extracting lung area with pleural effusion is promising for diagnosis of pulmonary diseases by providing quantitative volume of accumulating pleural effusion.

Robust Observation Detection for Single Object Tracking: Deterministic and Probabilistic Patch-Based Approaches

PubMed Central

Zulkifley, Mohd Asyraf; Rawlinson, David; Moran, Bill

2012-01-01

In video analytics, robust observation detection is very important as the content of the videos varies a lot, especially for tracking implementation. Contrary to the image processing field, the problems of blurring, moderate deformation, low illumination surroundings, illumination change and homogenous texture are normally encountered in video analytics. Patch-Based Observation Detection (PBOD) is developed to improve detection robustness to complex scenes by fusing both feature- and template-based recognition methods. While we believe that feature-based detectors are more distinctive, however, for finding the matching between the frames are best achieved by a collection of points as in template-based detectors. Two methods of PBOD—the deterministic and probabilistic approaches—have been tested to find the best mode of detection. Both algorithms start by building comparison vectors at each detected points of interest. The vectors are matched to build candidate patches based on their respective coordination. For the deterministic method, patch matching is done in 2-level test where threshold-based position and size smoothing are applied to the patch with the highest correlation value. For the second approach, patch matching is done probabilistically by modelling the histograms of the patches by Poisson distributions for both RGB and HSV colour models. Then, maximum likelihood is applied for position smoothing while a Bayesian approach is applied for size smoothing. The result showed that probabilistic PBOD outperforms the deterministic approach with average distance error of 10.03% compared with 21.03%. This algorithm is best implemented as a complement to other simpler detection methods due to heavy processing requirement. PMID:23202226

Study of moving object detecting and tracking algorithm for video surveillance system

NASA Astrophysics Data System (ADS)

Wang, Tao; Zhang, Rongfu

2010-10-01

This paper describes a specific process of moving target detecting and tracking in the video surveillance.Obtain high-quality background is the key to achieving differential target detecting in the video surveillance.The paper is based on a block segmentation method to build clear background,and using the method of background difference to detecing moving target,after a series of treatment we can be extracted the more comprehensive object from original image,then using the smallest bounding rectangle to locate the object.In the video surveillance system, the delay of camera and other reasons lead to tracking lag,the model of Kalman filter based on template matching was proposed,using deduced and estimated capacity of Kalman,the center of smallest bounding rectangle for predictive value,predicted the position in the next moment may appare,followed by template matching in the region as the center of this position,by calculate the cross-correlation similarity of current image and reference image,can determine the best matching center.As narrowed the scope of searching,thereby reduced the searching time,so there be achieve fast-tracking.

Three Dimensional Object Recognition Using a Complex Autoregressive Model

DTIC Science & Technology

1993-12-01

3.4.2 Template Matching Algorithm ...................... 3-16 3.4.3 K-Nearest-Neighbor ( KNN ) Techniques ................. 3-25 3.4.4 Hidden Markov Model...Neighbor ( KNN ) Test Results ...................... 4-13 4.2.1 Single-Look 1-NN Testing .......................... 4-14 4.2.2 Multiple-Look 1-NN Testing...4-15 4.2.3 Discussion of KNN Test Results ...................... 4-15 4.3 Hidden Markov Model (HMM) Test Results

Arraycount, an algorithm for automatic cell counting in microwell arrays.

PubMed

Kachouie, Nezamoddin; Kang, Lifeng; Khademhosseini, Ali

2009-09-01

Microscale technologies have emerged as a powerful tool for studying and manipulating biological systems and miniaturizing experiments. However, the lack of software complementing these techniques has made it difficult to apply them for many high-throughput experiments. This work establishes Arraycount, an approach to automatically count cells in microwell arrays. The procedure consists of fluorescent microscope imaging of cells that are seeded in microwells of a microarray system and then analyzing images via computer to recognize the array and count cells inside each microwell. To start counting, green and red fluorescent images (representing live and dead cells, respectively) are extracted from the original image and processed separately. A template-matching algorithm is proposed in which pre-defined well and cell templates are matched against the red and green images to locate microwells and cells. Subsequently, local maxima in the correlation maps are determined and local maxima maps are thresholded. At the end, the software records the cell counts for each detected microwell on the original image in high-throughput. The automated counting was shown to be accurate compared with manual counting, with a difference of approximately 1-2 cells per microwell: based on cell concentration, the absolute difference between manual and automatic counting measurements was 2.5-13%.

Photovoltaic panel extraction from very high-resolution aerial imagery using region-line primitive association analysis and template matching

NASA Astrophysics Data System (ADS)

Wang, Min; Cui, Qi; Sun, Yujie; Wang, Qiao

2018-07-01

In object-based image analysis (OBIA), object classification performance is jointly determined by image segmentation, sample or rule setting, and classifiers. Typically, as a crucial step to obtain object primitives, image segmentation quality significantly influences subsequent feature extraction and analyses. By contrast, template matching extracts specific objects from images and prevents shape defects caused by image segmentation. However, creating or editing templates is tedious and sometimes results in incomplete or inaccurate templates. In this study, we combine OBIA and template matching techniques to address these problems and aim for accurate photovoltaic panel (PVP) extraction from very high-resolution (VHR) aerial imagery. The proposed method is based on the previously proposed region-line primitive association framework, in which complementary information between region (segment) and line (straight line) primitives is utilized to achieve a more powerful performance than routine OBIA. Several novel concepts, including the mutual fitting ratio and best-fitting template based on region-line primitive association analyses, are proposed. Automatic template generation and matching method for PVP extraction from VHR imagery are designed for concept and model validation. Results show that the proposed method can successfully extract PVPs without any user-specified matching template or training sample. High user independency and accuracy are the main characteristics of the proposed method in comparison with routine OBIA and template matching techniques.

Fan fault diagnosis based on symmetrized dot pattern analysis and image matching

NASA Astrophysics Data System (ADS)

Xu, Xiaogang; Liu, Haixiao; Zhu, Hao; Wang, Songling

2016-07-01

To detect the mechanical failure of fans, a new diagnostic method based on the symmetrized dot pattern (SDP) analysis and image matching is proposed. Vibration signals of 13 kinds of running states are acquired on a centrifugal fan test bed and reconstructed by the SDP technique. The SDP pattern templates of each running state are established. An image matching method is performed to diagnose the fault. In order to improve the diagnostic accuracy, the single template, multiple templates and clustering fault templates are used to perform the image matching.

Dance-the-Music: an educational platform for the modeling, recognition and audiovisual monitoring of dance steps using spatiotemporal motion templates

NASA Astrophysics Data System (ADS)

Maes, Pieter-Jan; Amelynck, Denis; Leman, Marc

2012-12-01

In this article, a computational platform is presented, entitled "Dance-the-Music", that can be used in a dance educational context to explore and learn the basics of dance steps. By introducing a method based on spatiotemporal motion templates, the platform facilitates to train basic step models from sequentially repeated dance figures performed by a dance teacher. Movements are captured with an optical motion capture system. The teachers' models can be visualized from a first-person perspective to instruct students how to perform the specific dance steps in the correct manner. Moreover, recognition algorithms-based on a template matching method-can determine the quality of a student's performance in real time by means of multimodal monitoring techniques. The results of an evaluation study suggest that the Dance-the-Music is effective in helping dance students to master the basics of dance figures.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Aguiar, Ana C.; Chao, Kevin; Beroza, Gregory C.

In this paper, we compare low-frequency earthquakes (LFEs) from triggered and ambient tremor under the southern Central Range, Taiwan. We apply the PageRank algorithm used by Aguiar and Beroza (2014) that exploits the repetitive nature of the LFEs to find repeating LFEs in both ambient and triggered tremor. We use these repeaters to create LFE templates and find that the templates created from both tremor types are very similar. To test their similarity, we use both interchangeably and find that most of both the ambient and triggered tremor match the LFE templates created from either data set, suggesting that LFEsmore » for both events have a common origin. Finally, we locate the LFEs by using local earthquake P wave and S wave information and find that LFEs from triggered and ambient tremor locate to between 20 and 35 km on what we interpret as the deep extension of the Chaochou-Lishan Fault.« less

[An Algorithm to Eliminate Power Frequency Interference in ECG Using Template].

PubMed

Shi, Guohua; Li, Jiang; Xu, Yan; Feng, Liang

2017-01-01

Researching an algorithm to eliminate power frequency interference in ECG. The algorithm first creates power frequency interference template, then, subtracts the template from the original ECG signals, final y, the algorithm gets the ECG signals without interference. Experiment shows the algorithm can eliminate interference effectively and has none side effect to normal signal. It’s efficient and suitable for practice.

A new template matching method based on contour information

NASA Astrophysics Data System (ADS)

Cai, Huiying; Zhu, Feng; Wu, Qingxiao; Li, Sicong

2014-11-01

Template matching is a significant approach in machine vision due to its effectiveness and robustness. However, most of the template matching methods are so time consuming that they can't be used to many real time applications. The closed contour matching method is a popular kind of template matching methods. This paper presents a new closed contour template matching method which is suitable for two dimensional objects. Coarse-to-fine searching strategy is used to improve the matching efficiency and a partial computation elimination scheme is proposed to further speed up the searching process. The method consists of offline model construction and online matching. In the process of model construction, triples and distance image are obtained from the template image. A certain number of triples which are composed by three points are created from the contour information that is extracted from the template image. The rule to select the three points is that the template contour is divided equally into three parts by these points. The distance image is obtained here by distance transform. Each point on the distance image represents the nearest distance between current point and the points on the template contour. During the process of matching, triples of the searching image are created with the same rule as the triples of the model. Through the similarity that is invariant to rotation, translation and scaling between triangles, the triples corresponding to the triples of the model are found. Then we can obtain the initial RST (rotation, translation and scaling) parameters mapping the searching contour to the template contour. In order to speed up the searching process, the points on the searching contour are sampled to reduce the number of the triples. To verify the RST parameters, the searching contour is projected into the distance image, and the mean distance can be computed rapidly by simple operations of addition and multiplication. In the fine searching process, the initial RST parameters are discrete to obtain the final accurate pose of the object. Experimental results show that the proposed method is reasonable and efficient, and can be used in many real time applications.

Motion Evaluation for Rehabilitation Training of the Disabled

NASA Astrophysics Data System (ADS)

Kim, Tae-Young; Park, Jun; Lim, Cheol-Su

In this paper, a motion evaluation technique for rehabilitation training is introduced. Motion recognition technologies have been developed for determining matching motions in the training set. However, we need to measure how well and how much of the motion has been followed for training motion evaluation. We employed a Finite State Machine as a framework of motion evaluation. For similarity analysis, we used weighted angular value differences although any template matching algorithm may be used. For robustness under illumination changes, IR LED's and cameras with IR-pass filter were used. Developed technique was successfully used for rehabilitation training of the disabled. Therapists appraised the system as practically useful.

Local structure preserving sparse coding for infrared target recognition

PubMed Central

Han, Jing; Yue, Jiang; Zhang, Yi; Bai, Lianfa

2017-01-01

Sparse coding performs well in image classification. However, robust target recognition requires a lot of comprehensive template images and the sparse learning process is complex. We incorporate sparsity into a template matching concept to construct a local sparse structure matching (LSSM) model for general infrared target recognition. A local structure preserving sparse coding (LSPSc) formulation is proposed to simultaneously preserve the local sparse and structural information of objects. By adding a spatial local structure constraint into the classical sparse coding algorithm, LSPSc can improve the stability of sparse representation for targets and inhibit background interference in infrared images. Furthermore, a kernel LSPSc (K-LSPSc) formulation is proposed, which extends LSPSc to the kernel space to weaken the influence of the linear structure constraint in nonlinear natural data. Because of the anti-interference and fault-tolerant capabilities, both LSPSc- and K-LSPSc-based LSSM can implement target identification based on a simple template set, which just needs several images containing enough local sparse structures to learn a sufficient sparse structure dictionary of a target class. Specifically, this LSSM approach has stable performance in the target detection with scene, shape and occlusions variations. High performance is demonstrated on several datasets, indicating robust infrared target recognition in diverse environments and imaging conditions. PMID:28323824

Using dynamic programming to improve fiducial marker localization

NASA Astrophysics Data System (ADS)

Wan, Hanlin; Ge, Jiajia; Parikh, Parag

2014-04-01

Fiducial markers are used in a wide range of medical imaging applications. In radiation therapy, they are often implanted near tumors and used as motion surrogates that are tracked with fluoroscopy. We propose a novel and robust method based on dynamic programming (DP) for retrospectively localizing radiopaque fiducial markers in fluoroscopic images. Our method was compared to template matching (TM) algorithms on 407 data sets from 24 patients. We found that the performance of TM varied dramatically depending on the template used (ranging from 47% to 92% of data sets with a mean error <1 mm). DP by itself requires no template and performed as well as the best TM method, localizing the markers in 91% of the data sets with a mean error <1 mm. Finally, by combining DP and TM, we were able to localize the markers in 99% of the data sets with a mean error <1 mm, regardless of the template used. Our results show that DP can be a powerful tool for analyzing tumor motion, capable of accurately locating fiducial markers in fluoroscopic images regardless of marker type, shape, and size.

Detection and location of earthquakes along the west coast of Chile: Examining seismicity in the 2010 M 8.8 Maule and 2014 M 8.1 Iquique earthquake rupture zones.

NASA Astrophysics Data System (ADS)

Diniakos, R. S.; Bilek, S. L.; Rowe, C. A.; Draganov, D.

2015-12-01

The subduction of the Nazca Plate beneath the South American Plate along Chile has led to some of the largest earthquakes recorded on modern seismic instrumentation. These include the 1960 M 9.5 Valdivia, 2010 M 8.8 Maule, and 2014 M 8.1 Iquique earthquakes. Slip heterogeneity for both the 2010 and 2014 earthquakes has been noted in various studies. In order to explore both spatial variations in the continued aftershocks of the 2010 event, and also seismicity to the north along Iquique prior to the 2014 earthquake relative to the high slip regions, we are expanding the catalog of small earthquakes using template matching algorithms to find other small earthquakes in the region. We start with an earthquake catalog developed from regional and local array data; these events provide the templates used to search through waveform data from a temporary seismic array in Malargue, Argentina, located ~300 km west of the Maule region, which operated in 2012. Our template events are first identified on the array stations, and we use a 10-s window around the P-wave arrival as the template. We then use a waveform cross-correlation algorithm to compare the template with day-long seismograms from Malargue stations. The newly detected events are then located using the HYPOINVERSE2000 program. Initial results for 103 templates on 19 of the array stations show that we find 275 new events ,with an average of three new events for each template correlated. For these preliminary results, events from the Maule region appear to provide the most new detections, with an average of ten new events. We will present our locations for the detected events and we will compare them to patterns of high slip along the 2010 rupture zone of the M 8.8 Maule earthquake and the 2014 M 8.1 Iquique event.

Thermal imaging as a biometrics approach to facial signature authentication.

PubMed

Guzman, A M; Goryawala, M; Wang, Jin; Barreto, A; Andrian, J; Rishe, N; Adjouadi, M

2013-01-01

A new thermal imaging framework with unique feature extraction and similarity measurements for face recognition is presented. The research premise is to design specialized algorithms that would extract vasculature information, create a thermal facial signature and identify the individual. The proposed algorithm is fully integrated and consolidates the critical steps of feature extraction through the use of morphological operators, registration using the Linear Image Registration Tool and matching through unique similarity measures designed for this task. The novel approach at developing a thermal signature template using four images taken at various instants of time ensured that unforeseen changes in the vasculature over time did not affect the biometric matching process as the authentication process relied only on consistent thermal features. Thirteen subjects were used for testing the developed technique on an in-house thermal imaging system. The matching using the similarity measures showed an average accuracy of 88.46% for skeletonized signatures and 90.39% for anisotropically diffused signatures. The highly accurate results obtained in the matching process clearly demonstrate the ability of the thermal infrared system to extend in application to other thermal imaging based systems. Empirical results applying this approach to an existing database of thermal images proves this assertion.

Automated Epileptiform Spike Detection via Affinity Propagation-Based Template Matching

PubMed Central

Thomas, John; Jin, Jing; Dauwels, Justin; Cash, Sydney S.; Westover, M. Brandon

2018-01-01

Interictal epileptiform spikes are the key diagnostic biomarkers for epilepsy. The clinical gold standard of spike detection is visual inspection performed by neurologists. This is a tedious, time-consuming, and expert-centered process. The development of automated spike detection systems is necessary in order to provide a faster and more reliable diagnosis of epilepsy. In this paper, we propose an efficient template matching spike detector based on a combination of spike and background waveform templates. We generate a template library by clustering a collection of spikes and background waveforms extracted from a database of 50 patients with epilepsy. We benchmark the performance of five clustering techniques based on the receiver operating characteristic (ROC) curves. In addition, background templates are integrated with existing spike templates to improve the overall performance. The affinity propagation-based template matching system with a combination of spike and background templates is shown to outperform the other four conventional methods with the highest area-under-curve (AUC) of 0.953. PMID:29060543

A novel unsupervised spike sorting algorithm for intracranial EEG.

PubMed

Yadav, R; Shah, A K; Loeb, J A; Swamy, M N S; Agarwal, R

2011-01-01

This paper presents a novel, unsupervised spike classification algorithm for intracranial EEG. The method combines template matching and principal component analysis (PCA) for building a dynamic patient-specific codebook without a priori knowledge of the spike waveforms. The problem of misclassification due to overlapping classes is resolved by identifying similar classes in the codebook using hierarchical clustering. Cluster quality is visually assessed by projecting inter- and intra-clusters onto a 3D plot. Intracranial EEG from 5 patients was utilized to optimize the algorithm. The resulting codebook retains 82.1% of the detected spikes in non-overlapping and disjoint clusters. Initial results suggest a definite role of this method for both rapid review and quantitation of interictal spikes that could enhance both clinical treatment and research studies on epileptic patients.

SU-E-J-108: Template Matching Based On Multiple Templates Can Improve the Tumor Tracking Performance When There Is Large Tumor Deformation

DOE Office of Scientific and Technical Information (OSTI.GOV)

Shi, X; Lin, J; Diwanji, T

2014-06-01

Purpose: Recently, template matching has been shown to be able to track tumor motion on cine-MRI images. However, artifacts such as deformation, rotation, and/or out-of-plane movement could seriously degrade the performance of this technique. In this work, we demonstrate the utility of multiple templates derived from different phases of tumor motion in reducing the negative effects of artifacts and improving the accuracy of template matching methods. Methods: Data from 2 patients with large tumors and significant tumor deformation were analyzed from a group of 12 patients from an earlier study. Cine-MRI (200 frames) imaging was performed while the patients weremore » instructed to breathe normally. Ground truth tumor position was established on each frame manually by a radiation oncologist. Tumor positions were also automatically determined using template matching with either single or multiple (5) templates. The tracking errors, defined as the absolute differences in tumor positions determined by the manual and automated methods, when using either single or multiple templates were compared in both the AP and SI directions, respectively. Results: Using multiple templates reduced the tracking error of template matching. In the SI direction where the tumor movement and deformation were significant, the mean tracking error decreased from 1.94 mm to 0.91 mm (Patient 1) and from 6.61 mm to 2.06 mm (Patient 2). In the AP direction where the tumor movement was small, the reduction of the mean tracking error was significant in Patient 1 (from 3.36 mm to 1.04 mm), but not in Patient 2 ( from 3.86 mm to 3.80 mm). Conclusion: This study shows the effectiveness of using multiple templates in improving the performance of template matching when artifacts like large tumor deformation or out-of-plane motion exists. Accurate tumor tracking capabilities can be integrated with MRI guided radiation therapy systems. This work was supported in part by grants from NIH/NCI CA 124766 and Varian Medical Systems, Palo Alto, CA.« less

Tectonic tremor and LFEs on a reverse fault in Taiwan

DOE PAGES

Aguiar, Ana C.; Chao, Kevin; Beroza, Gregory C.

2017-06-16

In this paper, we compare low-frequency earthquakes (LFEs) from triggered and ambient tremor under the southern Central Range, Taiwan. We apply the PageRank algorithm used by Aguiar and Beroza (2014) that exploits the repetitive nature of the LFEs to find repeating LFEs in both ambient and triggered tremor. We use these repeaters to create LFE templates and find that the templates created from both tremor types are very similar. To test their similarity, we use both interchangeably and find that most of both the ambient and triggered tremor match the LFE templates created from either data set, suggesting that LFEsmore » for both events have a common origin. Finally, we locate the LFEs by using local earthquake P wave and S wave information and find that LFEs from triggered and ambient tremor locate to between 20 and 35 km on what we interpret as the deep extension of the Chaochou-Lishan Fault.« less

Delineating Concealed Faults within Cogdell Oil Field via Earthquake Detection

NASA Astrophysics Data System (ADS)

Aiken, C.; Walter, J. I.; Brudzinski, M.; Skoumal, R.; Savvaidis, A.; Frohlich, C.; Borgfeldt, T.; Dotray, P.

2016-12-01

Cogdell oil field, located within the Permian Basin of western Texas, has experienced several earthquakes ranging from magnitude 1.7 to 4.6, most of which were recorded since 2006. Using the Earthscope USArray, Gan and Frohlich [2013] relocated some of these events and found a positive correlation in the timing of increased earthquake activity and increased CO2 injection volume. However, focal depths of these earthquakes are unknown due to 70 km station spacing of the USArray. Accurate focal depths as well as new detections can delineate subsurface faults and establish whether earthquakes are occurring in the shallow sediments or in the deeper basement. To delineate subsurface fault(s) in this region, we first detect earthquakes not currently listed in the USGS catalog by applying continuous waveform-template matching algorithms to multiple seismic data sets. We utilize seismic data spanning the time frame of 2006 to 2016 - which includes data from the U.S. Geological Survey Global Seismographic Network, the USArray, and the Sweetwater, TX broadband and nodal array located 20-40 km away. The catalog of earthquakes enhanced by template matching reveals events that were well recorded by the large-N Sweetwater array, so we are experimenting with strategies for optimizing template matching using different configurations of many stations. Since earthquake activity in the Cogdell oil field is on-going (a magnitude 2.6 occurred on May 29, 2016), a temporary deployment of TexNet seismometers has been planned for the immediate vicinity of Cogdell oil field in August 2016. Results on focal depths and detection of small magnitude events are pending this small local network deployment.

Window-based method for approximating the Hausdorff in three-dimensional range imagery

DOEpatents

Koch, Mark W [Albuquerque, NM

2009-06-02

One approach to pattern recognition is to use a template from a database of objects and match it to a probe image containing the unknown. Accordingly, the Hausdorff distance can be used to measure the similarity of two sets of points. In particular, the Hausdorff can measure the goodness of a match in the presence of occlusion, clutter, and noise. However, existing 3D algorithms for calculating the Hausdorff are computationally intensive, making them impractical for pattern recognition that requires scanning of large databases. The present invention is directed to a new method that can efficiently, in time and memory, compute the Hausdorff for 3D range imagery. The method uses a window-based approach.

Biometric template revocation

NASA Astrophysics Data System (ADS)

Arndt, Craig M.

2004-08-01

Biometric are a powerful technology for identifying humans both locally and at a distance. In order to perform identification or verification biometric systems capture an image of some biometric of a user or subject. The image is then converted mathematical to representation of the person call a template. Since we know that every human in the world is different each human will have different biometric images (different fingerprints, or faces, etc.). This is what makes biometrics useful for identification. However unlike a credit card number or a password to can be given to a person and later revoked if it is compromised and biometric is with the person for life. The problem then is to develop biometric templates witch can be easily revoked and reissued which are also unique to the user and can be easily used for identification and verification. In this paper we develop and present a method to generate a set of templates which are fully unique to the individual and also revocable. By using bases set compression algorithms in an n-dimensional orthogonal space we can represent a give biometric image in an infinite number of equally valued and unique ways. The verification and biometric matching system would be presented with a given template and revocation code. The code will then representing where in the sequence of n-dimensional vectors to start the recognition.

Immunophenotype Discovery, Hierarchical Organization, and Template-Based Classification of Flow Cytometry Samples

DOE PAGES

Azad, Ariful; Rajwa, Bartek; Pothen, Alex

2016-08-31

We describe algorithms for discovering immunophenotypes from large collections of flow cytometry samples and using them to organize the samples into a hierarchy based on phenotypic similarity. The hierarchical organization is helpful for effective and robust cytometry data mining, including the creation of collections of cell populations’ characteristic of different classes of samples, robust classification, and anomaly detection. We summarize a set of samples belonging to a biological class or category with a statistically derived template for the class. Whereas individual samples are represented in terms of their cell populations (clusters), a template consists of generic meta-populations (a group ofmore » homogeneous cell populations obtained from the samples in a class) that describe key phenotypes shared among all those samples. We organize an FC data collection in a hierarchical data structure that supports the identification of immunophenotypes relevant to clinical diagnosis. A robust template-based classification scheme is also developed, but our primary focus is in the discovery of phenotypic signatures and inter-sample relationships in an FC data collection. This collective analysis approach is more efficient and robust since templates describe phenotypic signatures common to cell populations in several samples while ignoring noise and small sample-specific variations. We have applied the template-based scheme to analyze several datasets, including one representing a healthy immune system and one of acute myeloid leukemia (AML) samples. The last task is challenging due to the phenotypic heterogeneity of the several subtypes of AML. However, we identified thirteen immunophenotypes corresponding to subtypes of AML and were able to distinguish acute promyelocytic leukemia (APL) samples with the markers provided. Clinically, this is helpful since APL has a different treatment regimen from other subtypes of AML. Core algorithms used in our data analysis are available in the flowMatch package at www.bioconductor.org. It has been downloaded nearly 6,000 times since 2014.« less

Immunophenotype Discovery, Hierarchical Organization, and Template-Based Classification of Flow Cytometry Samples

DOE Office of Scientific and Technical Information (OSTI.GOV)

Azad, Ariful; Rajwa, Bartek; Pothen, Alex

We describe algorithms for discovering immunophenotypes from large collections of flow cytometry samples and using them to organize the samples into a hierarchy based on phenotypic similarity. The hierarchical organization is helpful for effective and robust cytometry data mining, including the creation of collections of cell populations’ characteristic of different classes of samples, robust classification, and anomaly detection. We summarize a set of samples belonging to a biological class or category with a statistically derived template for the class. Whereas individual samples are represented in terms of their cell populations (clusters), a template consists of generic meta-populations (a group ofmore » homogeneous cell populations obtained from the samples in a class) that describe key phenotypes shared among all those samples. We organize an FC data collection in a hierarchical data structure that supports the identification of immunophenotypes relevant to clinical diagnosis. A robust template-based classification scheme is also developed, but our primary focus is in the discovery of phenotypic signatures and inter-sample relationships in an FC data collection. This collective analysis approach is more efficient and robust since templates describe phenotypic signatures common to cell populations in several samples while ignoring noise and small sample-specific variations. We have applied the template-based scheme to analyze several datasets, including one representing a healthy immune system and one of acute myeloid leukemia (AML) samples. The last task is challenging due to the phenotypic heterogeneity of the several subtypes of AML. However, we identified thirteen immunophenotypes corresponding to subtypes of AML and were able to distinguish acute promyelocytic leukemia (APL) samples with the markers provided. Clinically, this is helpful since APL has a different treatment regimen from other subtypes of AML. Core algorithms used in our data analysis are available in the flowMatch package at www.bioconductor.org. It has been downloaded nearly 6,000 times since 2014.« less

On the construction of a new stellar classification template library for the LAMOST spectral analysis pipeline

DOE Office of Scientific and Technical Information (OSTI.GOV)

Wei, Peng; Luo, Ali; Li, Yinbi

2014-05-01

The LAMOST spectral analysis pipeline, called the 1D pipeline, aims to classify and measure the spectra observed in the LAMOST survey. Through this pipeline, the observed stellar spectra are classified into different subclasses by matching with template spectra. Consequently, the performance of the stellar classification greatly depends on the quality of the template spectra. In this paper, we construct a new LAMOST stellar spectral classification template library, which is supposed to improve the precision and credibility of the present LAMOST stellar classification. About one million spectra are selected from LAMOST Data Release One to construct the new stellar templates, andmore » they are gathered in 233 groups by two criteria: (1) pseudo g – r colors obtained by convolving the LAMOST spectra with the Sloan Digital Sky Survey ugriz filter response curve, and (2) the stellar subclass given by the LAMOST pipeline. In each group, the template spectra are constructed using three steps. (1) Outliers are excluded using the Local Outlier Probabilities algorithm, and then the principal component analysis method is applied to the remaining spectra of each group. About 5% of the one million spectra are ruled out as outliers. (2) All remaining spectra are reconstructed using the first principal components of each group. (3) The weighted average spectrum is used as the template spectrum in each group. Using the previous 3 steps, we initially obtain 216 stellar template spectra. We visually inspect all template spectra, and 29 spectra are abandoned due to low spectral quality. Furthermore, the MK classification for the remaining 187 template spectra is manually determined by comparing with 3 template libraries. Meanwhile, 10 template spectra whose subclass is difficult to determine are abandoned. Finally, we obtain a new template library containing 183 LAMOST template spectra with 61 different MK classes by combining it with the current library.« less

An electrooculogram-based binary saccade sequence classification (BSSC) technique for augmentative communication and control.

PubMed

Keegan, Johnalan; Burke, Edward; Condron, James

2009-01-01

In the field of assistive technology, the electrooculogram (EOG) can be used as a channel of communication and the basis of a man-machine interface. For many people with severe motor disabilities, simple actions such as changing the TV channel require assistance. This paper describes a method of detecting saccadic eye movements and the use of a saccade sequence classification algorithm to facilitate communication and control. Saccades are fast eye movements that occurs when a person's gaze jumps from one fixation point to another. The classification is based on pre-defined sequences of saccades, guided by a static visual template (e.g. a page or poster). The template, consisting of a table of symbols each having a clearly identifiable fixation point, is situated within view of the user. To execute a particular command, the user moves his or her gaze through a pre-defined path of eye movements. This results in a well-formed sequence of saccades which are translated into a command if a match is found in a library of predefined sequences. A coordinate transformation algorithm is applied to each candidate sequence of recorded saccades to mitigate the effect of changes in the user's position and orientation relative to the visual template. Upon recognition of a saccade sequence from the library, its associated command is executed. A preliminary experiment in which two subjects were instructed to perform a series of command sequences consisting of 8 different commands are presented in the final sections. The system is also shown to be extensible to facilitate convenient text entry via an alphabetic visual template.

Fast localization of optic disc and fovea in retinal images for eye disease screening

NASA Astrophysics Data System (ADS)

Yu, H.; Barriga, S.; Agurto, C.; Echegaray, S.; Pattichis, M.; Zamora, G.; Bauman, W.; Soliz, P.

2011-03-01

Optic disc (OD) and fovea locations are two important anatomical landmarks in automated analysis of retinal disease in color fundus photographs. This paper presents a new, fast, fully automatic optic disc and fovea localization algorithm developed for diabetic retinopathy (DR) screening. The optic disc localization methodology comprises of two steps. First, the OD location is identified using template matching and directional matched filter. To reduce false positives due to bright areas of pathology, we exploit vessel characteristics inside the optic disc. The location of the fovea is estimated as the point of lowest matched filter response within a search area determined by the optic disc location. Second, optic disc segmentation is performed. Based on the detected optic disc location, a fast hybrid level-set algorithm which combines the region information and edge gradient to drive the curve evolution is used to segment the optic disc boundary. Extensive evaluation was performed on 1200 images (Messidor) composed of 540 images of healthy retinas, 431 images with DR but no risk of macular edema (ME), and 229 images with DR and risk of ME. The OD location methodology obtained 98.3% success rate, while fovea location achieved 95% success rate. The average mean absolute distance (MAD) between the OD segmentation algorithm and "gold standard" is 10.5% of estimated OD radius. Qualitatively, 97% of the images achieved Excellent to Fair performance for OD segmentation. The segmentation algorithm performs well even on blurred images.

Single and Multiple Object Tracking Using a Multi-Feature Joint Sparse Representation.

PubMed

Hu, Weiming; Li, Wei; Zhang, Xiaoqin; Maybank, Stephen

2015-04-01

In this paper, we propose a tracking algorithm based on a multi-feature joint sparse representation. The templates for the sparse representation can include pixel values, textures, and edges. In the multi-feature joint optimization, noise or occlusion is dealt with using a set of trivial templates. A sparse weight constraint is introduced to dynamically select the relevant templates from the full set of templates. A variance ratio measure is adopted to adaptively adjust the weights of different features. The multi-feature template set is updated adaptively. We further propose an algorithm for tracking multi-objects with occlusion handling based on the multi-feature joint sparse reconstruction. The observation model based on sparse reconstruction automatically focuses on the visible parts of an occluded object by using the information in the trivial templates. The multi-object tracking is simplified into a joint Bayesian inference. The experimental results show the superiority of our algorithm over several state-of-the-art tracking algorithms.

An automatic algorithm for blink-artifact suppression based on iterative template matching: application to single channel recording of cortical auditory evoked potentials

NASA Astrophysics Data System (ADS)

Valderrama, Joaquin T.; de la Torre, Angel; Van Dun, Bram

2018-02-01

Objective. Artifact reduction in electroencephalogram (EEG) signals is usually necessary to carry out data analysis appropriately. Despite the large amount of denoising techniques available with a multichannel setup, there is a lack of efficient algorithms that remove (not only detect) blink-artifacts from a single channel EEG, which is of interest in many clinical and research applications. This paper describes and evaluates the iterative template matching and suppression (ITMS), a new method proposed for detecting and suppressing the artifact associated with the blink activity from a single channel EEG. Approach. The approach of ITMS consists of (a) an iterative process in which blink-events are detected and the blink-artifact waveform of the analyzed subject is estimated, (b) generation of a signal modeling the blink-artifact, and (c) suppression of this signal from the raw EEG. The performance of ITMS is compared with the multi-window summation of derivatives within a window (MSDW) technique using both synthesized and real EEG data. Main results. Results suggest that ITMS presents an adequate performance in detecting and suppressing blink-artifacts from a single channel EEG. When applied to the analysis of cortical auditory evoked potentials (CAEPs), ITMS provides a significant quality improvement in the resulting responses, i.e. in a cohort of 30 adults, the mean correlation coefficient improved from 0.37 to 0.65 when the blink-artifacts were detected and suppressed by ITMS. Significance. ITMS is an efficient solution to the problem of denoising blink-artifacts in single-channel EEG applications, both in clinical and research fields. The proposed ITMS algorithm is stable; automatic, since it does not require human intervention; low-invasive, because the EEG segments not contaminated by blink-artifacts remain unaltered; and easy to implement, as can be observed in the Matlab script implemeting the algorithm provided as supporting material.

A numerical study of sensory-guided multiple views for improved object identification

NASA Astrophysics Data System (ADS)

Blakeslee, B. A.; Zelnio, E. G.; Koditschek, D. E.

2014-06-01

We explore the potential on-line adjustment of sensory controls for improved object identification and discrimination in the context of a simulated high resolution camera system carried onboard a maneuverable robotic platform that can actively choose its observational position and pose. Our early numerical studies suggest the significant efficacy and enhanced performance achieved by even very simple feedback-driven iteration of the view in contrast to identification from a fixed pose, uninformed by any active adaptation. Specifically, we contrast the discriminative performance of the same conventional classification system when informed by: a random glance at a vehicle; two random glances at a vehicle; or a random glance followed by a guided second look. After each glance, edge detection algorithms isolate the most salient features of the image and template matching is performed through the use of the Hausdor↵ distance, comparing the simulated sensed images with reference images of the vehicles. We present initial simulation statistics that overwhelmingly favor the third scenario. We conclude with a sketch of our near-future steps in this study that will entail: the incorporation of more sophisticated image processing and template matching algorithms; more complex discrimination tasks such as distinguishing between two similar vehicles or vehicles in motion; more realistic models of the observers mobility including platform dynamics and eventually environmental constraints; and expanding the sensing task beyond the identification of a specified object selected from a pre-defined library of alternatives.

Robust Visual Tracking Revisited: From Correlation Filter to Template Matching.

PubMed

Liu, Fanghui; Gong, Chen; Huang, Xiaolin; Zhou, Tao; Yang, Jie; Tao, Dacheng

2018-06-01

In this paper, we propose a novel matching based tracker by investigating the relationship between template matching and the recent popular correlation filter based trackers (CFTs). Compared to the correlation operation in CFTs, a sophisticated similarity metric termed mutual buddies similarity is proposed to exploit the relationship of multiple reciprocal nearest neighbors for target matching. By doing so, our tracker obtains powerful discriminative ability on distinguishing target and background as demonstrated by both empirical and theoretical analyses. Besides, instead of utilizing single template with the improper updating scheme in CFTs, we design a novel online template updating strategy named memory, which aims to select a certain amount of representative and reliable tracking results in history to construct the current stable and expressive template set. This scheme is beneficial for the proposed tracker to comprehensively understand the target appearance variations, recall some stable results. Both qualitative and quantitative evaluations on two benchmarks suggest that the proposed tracking method performs favorably against some recently developed CFTs and other competitive trackers.

Radio-nuclide mixture identification using medium energy resolution detectors

DOEpatents

Nelson, Karl Einar

2013-09-17

According to one embodiment, a method for identifying radio-nuclides includes receiving spectral data, extracting a feature set from the spectral data comparable to a plurality of templates in a template library, and using a branch and bound method to determine a probable template match based on the feature set and templates in the template library. In another embodiment, a device for identifying unknown radio-nuclides includes a processor, a multi-channel analyzer, and a memory operatively coupled to the processor, the memory having computer readable code stored thereon. The computer readable code is configured, when executed by the processor, to receive spectral data, to extract a feature set from the spectral data comparable to a plurality of templates in a template library, and to use a branch and bound method to determine a probable template match based on the feature set and templates in the template library.

Generation and assessment of turntable SAR data for the support of ATR development

NASA Astrophysics Data System (ADS)

Cohen, Marvin N.; Showman, Gregory A.; Sangston, K. James; Sylvester, Vincent B.; Gostin, Lamar; Scheer, C. Ruby

1998-10-01

Inverse synthetic aperture radar (ISAR) imaging on a turntable-tower test range permits convenient generation of high resolution two-dimensional images of radar targets under controlled conditions for testing SAR image processing and for supporting automatic target recognition (ATR) algorithm development. However, turntable ISAR images are often obtained under near-field geometries and hence may suffer geometric distortions not present in airborne SAR images. In this paper, turntable data collected at Georgia Tech's Electromagnetic Test Facility are used to begin to assess the utility of two- dimensional ISAR imaging algorithms in forming images to support ATR development. The imaging algorithms considered include a simple 2D discrete Fourier transform (DFT), a 2-D DFT with geometric correction based on image domain resampling, and a computationally-intensive geometric matched filter solution. Images formed with the various algorithms are used to develop ATR templates, which are then compared with an eye toward utilization in an ATR algorithm.

Incorporating User Input in Template-Based Segmentation

PubMed Central

Vidal, Camille; Beggs, Dale; Younes, Laurent; Jain, Sanjay K.; Jedynak, Bruno

2015-01-01

We present a simple and elegant method to incorporate user input in a template-based segmentation method for diseased organs. The user provides a partial segmentation of the organ of interest, which is used to guide the template towards its target. The user also highlights some elements of the background that should be excluded from the final segmentation. We derive by likelihood maximization a registration algorithm from a simple statistical image model in which the user labels are modeled as Bernoulli random variables. The resulting registration algorithm minimizes the sum of square differences between the binary template and the user labels, while preventing the template from shrinking, and penalizing for the inclusion of background elements into the final segmentation. We assess the performance of the proposed algorithm on synthetic images in which the amount of user annotation is controlled. We demonstrate our algorithm on the segmentation of the lungs of Mycobacterium tuberculosis infected mice from μCT images. PMID:26146532

Information theory-based algorithm for in silico prediction of PCR products with whole genomic sequences as templates.

PubMed

Cao, Youfang; Wang, Lianjie; Xu, Kexue; Kou, Chunhai; Zhang, Yulei; Wei, Guifang; He, Junjian; Wang, Yunfang; Zhao, Liping

2005-07-26

A new algorithm for assessing similarity between primer and template has been developed based on the hypothesis that annealing of primer to template is an information transfer process. Primer sequence is converted to a vector of the full potential hydrogen numbers (3 for G or C, 2 for A or T), while template sequence is converted to a vector of the actual hydrogen bond numbers formed after primer annealing. The former is considered as source information and the latter destination information. An information coefficient is calculated as a measure for fidelity of this information transfer process and thus a measure of similarity between primer and potential annealing site on template. Successful prediction of PCR products from whole genomic sequences with a computer program based on the algorithm demonstrated the potential of this new algorithm in areas like in silico PCR and gene finding.

TU-D-209-03: Alignment of the Patient Graphic Model Using Fluoroscopic Images for Skin Dose Mapping

DOE Office of Scientific and Technical Information (OSTI.GOV)

Oines, A; Oines, A; Kilian-Meneghin, J

2016-06-15

Purpose: The Dose Tracking System (DTS) was developed to provide realtime feedback of skin dose and dose rate during interventional fluoroscopic procedures. A color map on a 3D graphic of the patient represents the cumulative dose distribution on the skin. Automated image correlation algorithms are described which use the fluoroscopic procedure images to align and scale the patient graphic for more accurate dose mapping. Methods: Currently, the DTS employs manual patient graphic selection and alignment. To improve the accuracy of dose mapping and automate the software, various methods are explored to extract information about the beam location and patient morphologymore » from the procedure images. To match patient anatomy with a reference projection image, preprocessing is first used, including edge enhancement, edge detection, and contour detection. Template matching algorithms from OpenCV are then employed to find the location of the beam. Once a match is found, the reference graphic is scaled and rotated to fit the patient, using image registration correlation functions in Matlab. The algorithm runs correlation functions for all points and maps all correlation confidences to a surface map. The highest point of correlation is used for alignment and scaling. The transformation data is saved for later model scaling. Results: Anatomic recognition is used to find matching features between model and image and image registration correlation provides for alignment and scaling at any rotation angle with less than onesecond runtime, and at noise levels in excess of 150% of those found in normal procedures. Conclusion: The algorithm provides the necessary scaling and alignment tools to improve the accuracy of dose distribution mapping on the patient graphic with the DTS. Partial support from NIH Grant R01-EB002873 and Toshiba Medical Systems Corp.« less

Automated CD-SEM recipe creation technology for mass production using CAD data

NASA Astrophysics Data System (ADS)

Kawahara, Toshikazu; Yoshida, Masamichi; Tanaka, Masashi; Ido, Sanyu; Nakano, Hiroyuki; Adachi, Naokaka; Abe, Yuichi; Nagatomo, Wataru

2011-03-01

Critical Dimension Scanning Electron Microscope (CD-SEM) recipe creation needs sample preparation necessary for matching pattern registration, and recipe creation on CD-SEM using the sample, which hinders the reduction in test production cost and time in semiconductor manufacturing factories. From the perspective of cost reduction and improvement of the test production efficiency, automated CD-SEM recipe creation without the sample preparation and the manual operation has been important in the production lines. For the automated CD-SEM recipe creation, we have introduced RecipeDirector (RD) that enables the recipe creation by using Computer-Aided Design (CAD) data and text data that includes measurement information. We have developed a system that automatically creates the CAD data and the text data necessary for the recipe creation on RD; and, for the elimination of the manual operation, we have enhanced RD so that all measurement information can be specified in the text data. As a result, we have established an automated CD-SEM recipe creation system without the sample preparation and the manual operation. For the introduction of the CD-SEM recipe creation system using RD to the production lines, the accuracy of the pattern matching was an issue. The shape of design templates for the matching created from the CAD data was different from that of SEM images in vision. Thus, a development of robust pattern matching algorithm that considers the shape difference was needed. The addition of image processing of the templates for the matching and shape processing of the CAD patterns in the lower layer has enabled the robust pattern matching. This paper describes the automated CD-SEM recipe creation technology for the production lines without the sample preparation and the manual operation using RD applied in Sony Semiconductor Kyusyu Corporation Kumamoto Technology Center (SCK Corporation Kumamoto TEC).

A hospital-specific template for benchmarking its cost and quality.

PubMed

Silber, Jeffrey H; Rosenbaum, Paul R; Ross, Richard N; Ludwig, Justin M; Wang, Wei; Niknam, Bijan A; Saynisch, Philip A; Even-Shoshan, Orit; Kelz, Rachel R; Fleisher, Lee A

2014-10-01

Develop an improved method for auditing hospital cost and quality tailored to a specific hospital's patient population. Medicare claims in general, gynecologic and urologic surgery, and orthopedics from Illinois, New York, and Texas between 2004 and 2006. A template of 300 representative patients from a single index hospital was constructed and used to match 300 patients at 43 hospitals that had a minimum of 500 patients over a 3-year study period. From each of 43 hospitals we chose 300 patients most resembling the template using multivariate matching. We found close matches on procedures and patient characteristics, far more balanced than would be expected in a randomized trial. There were little to no differences between the index hospital's template and the 43 hospitals on most patient characteristics yet large and significant differences in mortality, failure-to-rescue, and cost. Matching can produce fair, directly standardized audits. From the perspective of the index hospital, "hospital-specific" template matching provides the fairness of direct standardization with the specific institutional relevance of indirect standardization. Using this approach, hospitals will be better able to examine their performance, and better determine why they are achieving the results they observe. © Health Research and Educational Trust.

VieSLAF Framework: Enabling Adaptive and Versatile SLA-Management

NASA Astrophysics Data System (ADS)

Brandic, Ivona; Music, Dejan; Leitner, Philipp; Dustdar, Schahram

Novel computing paradigms like Grid and Cloud computing demand guarantees on non-functional requirements such as application execution time or price. Such requirements are usually negotiated following a specific Quality of Service (QoS) model and are expressed using Service Level Agreements (SLAs). Currently available QoS models assume either that service provider and consumer have matching SLA templates and common understanding of the negotiated terms or provide public templates, which can be downloaded and utilized by the end users. On the one hand, matching SLA templates represent an unrealistic assumption in systems where service consumer and provider meet dynamically and on demand. On the other hand, handling of public templates seems to be a rather challenging issue, especially if the templates do not reflect users’ needs. In this paper we present VieSLAF, a novel framework for the specification and management of SLA mappings. Using VieSLAF users may specify, manage, and apply SLA mapping bridging the gap between non-matching SLA templates. Moreover, based on the predefined learning functions and considering accumulated SLA mappings, domain specific public SLA templates can be derived reflecting users’ needs.

A novel framework for feature extraction in multi-sensor action potential sorting.

PubMed

Wu, Shun-Chi; Swindlehurst, A Lee; Nenadic, Zoran

2015-09-30

Extracellular recordings of multi-unit neural activity have become indispensable in neuroscience research. The analysis of the recordings begins with the detection of the action potentials (APs), followed by a classification step where each AP is associated with a given neural source. A feature extraction step is required prior to classification in order to reduce the dimensionality of the data and the impact of noise, allowing source clustering algorithms to work more efficiently. In this paper, we propose a novel framework for multi-sensor AP feature extraction based on the so-called Matched Subspace Detector (MSD), which is shown to be a natural generalization of standard single-sensor algorithms. Clustering using both simulated data and real AP recordings taken in the locust antennal lobe demonstrates that the proposed approach yields features that are discriminatory and lead to promising results. Unlike existing methods, the proposed algorithm finds joint spatio-temporal feature vectors that match the dominant subspace observed in the two-dimensional data without needs for a forward propagation model and AP templates. The proposed MSD approach provides more discriminatory features for unsupervised AP sorting applications. Copyright © 2015 Elsevier B.V. All rights reserved.

A pilot study of a heuristic algorithm for novel template identification from VA electronic medical record text.

PubMed

Redd, Andrew M; Gundlapalli, Adi V; Divita, Guy; Carter, Marjorie E; Tran, Le-Thuy; Samore, Matthew H

2017-07-01

Templates in text notes pose challenges for automated information extraction algorithms. We propose a method that identifies novel templates in plain text medical notes. The identification can then be used to either include or exclude templates when processing notes for information extraction. The two-module method is based on the framework of information foraging and addresses the hypothesis that documents containing templates and the templates within those documents can be identified by common features. The first module takes documents from the corpus and groups those with common templates. This is accomplished through a binned word count hierarchical clustering algorithm. The second module extracts the templates. It uses the groupings and performs a longest common subsequence (LCS) algorithm to obtain the constituent parts of the templates. The method was developed and tested on a random document corpus of 750 notes derived from a large database of US Department of Veterans Affairs (VA) electronic medical notes. The grouping module, using hierarchical clustering, identified 23 groups with 3 documents or more, consisting of 120 documents from the 750 documents in our test corpus. Of these, 18 groups had at least one common template that was present in all documents in the group for a positive predictive value of 78%. The LCS extraction module performed with 100% positive predictive value, 94% sensitivity, and 83% negative predictive value. The human review determined that in 4 groups the template covered the entire document, with the remaining 14 groups containing a common section template. Among documents with templates, the number of templates per document ranged from 1 to 14. The mean and median number of templates per group was 5.9 and 5, respectively. The grouping method was successful in finding like documents containing templates. Of the groups of documents containing templates, the LCS module was successful in deciphering text belonging to the template and text that was extraneous. Major obstacles to improved performance included documents composed of multiple templates, templates that included other templates embedded within them, and variants of templates. We demonstrate proof of concept of the grouping and extraction method of identifying templates in electronic medical records in this pilot study and propose methods to improve performance and scaling up. Published by Elsevier Inc.

Performing label-fusion-based segmentation using multiple automatically generated templates.

PubMed

Chakravarty, M Mallar; Steadman, Patrick; van Eede, Matthijs C; Calcott, Rebecca D; Gu, Victoria; Shaw, Philip; Raznahan, Armin; Collins, D Louis; Lerch, Jason P

2013-10-01

Classically, model-based segmentation procedures match magnetic resonance imaging (MRI) volumes to an expertly labeled atlas using nonlinear registration. The accuracy of these techniques are limited due to atlas biases, misregistration, and resampling error. Multi-atlas-based approaches are used as a remedy and involve matching each subject to a number of manually labeled templates. This approach yields numerous independent segmentations that are fused using a voxel-by-voxel label-voting procedure. In this article, we demonstrate how the multi-atlas approach can be extended to work with input atlases that are unique and extremely time consuming to construct by generating a library of multiple automatically generated templates of different brains (MAGeT Brain). We demonstrate the efficacy of our method for the mouse and human using two different nonlinear registration algorithms (ANIMAL and ANTs). The input atlases consist a high-resolution mouse brain atlas and an atlas of the human basal ganglia and thalamus derived from serial histological data. MAGeT Brain segmentation improves the identification of the mouse anterior commissure (mean Dice Kappa values (κ = 0.801), but may be encountering a ceiling effect for hippocampal segmentations. Applying MAGeT Brain to human subcortical structures improves segmentation accuracy for all structures compared to regular model-based techniques (κ = 0.845, 0.752, and 0.861 for the striatum, globus pallidus, and thalamus, respectively). Experiments performed with three manually derived input templates suggest that MAGeT Brain can approach or exceed the accuracy of multi-atlas label-fusion segmentation (κ = 0.894, 0.815, and 0.895 for the striatum, globus pallidus, and thalamus, respectively). Copyright © 2012 Wiley Periodicals, Inc.

Content analysis of physical examination templates in electronic health records using SNOMED CT.

PubMed

Gøeg, Kirstine Rosenbeck; Chen, Rong; Højen, Anne Randorff; Elberg, Pia

2014-10-01

Most electronic health record (EHR) systems are built on proprietary information models and terminology, which makes achieving semantic interoperability a challenge. Solving interoperability problems requires well-defined standards. In contrast, the need to support clinical work practice requires a local customization of EHR systems. Consequently, contrasting goals may be evident in EHR template design because customization means that local EHR organizations can define their own templates, whereas standardization implies consensus at some level. To explore the complexity of balancing these two goals, this study analyzes the differences and similarities between templates in use today. A similarity analysis was developed on the basis of SNOMED CT. The analysis was performed on four physical examination templates from Denmark and Sweden. The semantic relationships in SNOMED CT were used to quantify similarities and differences. Moreover, the analysis used these identified similarities to investigate the common content of a physical examination template. The analysis showed that there were both similarities and differences in physical examination templates, and the size of the templates varied from 18 to 49 fields. In the SNOMED CT analysis, exact matches and terminology similarities were represented in all template pairs. The number of exact matches ranged from 7 to 24. Moreover, the number of unrelated fields differed a lot from 1/18 to 22/35. Cross-country comparisons tended to have more unrelated content than within-country comparisons. On the basis of identified similarities, it was possible to define the common content of a physical examination. Nevertheless, a complete view on the physical examination required the inclusion of both exact matches and terminology similarities. This study revealed that a core set of items representing the physical examination templates can be generated when the analysis takes into account not only exact matches but also terminology similarities. This core set of items could be a starting point for standardization and semantic interoperability. However, both unmatched terms and terminology matched terms pose a challenge for standardization. Future work will include using local templates as a point of departure in standardization to see if local requirements can be maintained in a standardized framework. Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.

Optimizing microstimulation using a reinforcement learning framework.

PubMed

Brockmeier, Austin J; Choi, John S; Distasio, Marcello M; Francis, Joseph T; Príncipe, José C

2011-01-01

The ability to provide sensory feedback is desired to enhance the functionality of neuroprosthetics. Somatosensory feedback provides closed-loop control to the motor system, which is lacking in feedforward neuroprosthetics. In the case of existing somatosensory function, a template of the natural response can be used as a template of desired response elicited by electrical microstimulation. In the case of no initial training data, microstimulation parameters that produce responses close to the template must be selected in an online manner. We propose using reinforcement learning as a framework to balance the exploration of the parameter space and the continued selection of promising parameters for further stimulation. This approach avoids an explicit model of the neural response from stimulation. We explore a preliminary architecture--treating the task as a k-armed bandit--using offline data recorded for natural touch and thalamic microstimulation, and we examine the methods efficiency in exploring the parameter space while concentrating on promising parameter forms. The best matching stimulation parameters, from k = 68 different forms, are selected by the reinforcement learning algorithm consistently after 334 realizations.

Fast Legendre moment computation for template matching

NASA Astrophysics Data System (ADS)

Li, Bing C.

2017-05-01

Normalized cross correlation (NCC) based template matching is insensitive to intensity changes and it has many applications in image processing, object detection, video tracking and pattern recognition. However, normalized cross correlation implementation is computationally expensive since it involves both correlation computation and normalization implementation. In this paper, we propose Legendre moment approach for fast normalized cross correlation implementation and show that the computational cost of this proposed approach is independent of template mask sizes which is significantly faster than traditional mask size dependent approaches, especially for large mask templates. Legendre polynomials have been widely used in solving Laplace equation in electrodynamics in spherical coordinate systems, and solving Schrodinger equation in quantum mechanics. In this paper, we extend Legendre polynomials from physics to computer vision and pattern recognition fields, and demonstrate that Legendre polynomials can help to reduce the computational cost of NCC based template matching significantly.

Developmental changes in hippocampal shape among preadolescent children.

PubMed

Lin, Muqing; Fwu, Peter T; Buss, Claudia; Davis, Elysia P; Head, Kevin; Muftuler, L Tugan; Sandman, Curt A; Su, Min-Ying

2013-11-01

It is known that the largest developmental changes in the hippocampus take place during the prenatal period and during the first two years of postnatal life. Few studies have been conducted to address the normal developmental trajectory of the hippocampus during childhood. In this study shape analysis was applied to study the normal developing hippocampus in a group of 103 typically developing 6- to 10-year-old preadolescent children. The individual brain was normalized to a template, and then the hippocampus was manually segmented and further divided into the head, body, and tail sub-regions. Three different methods were applied for hippocampal shape analysis: radial distance mapping, surface-based template registration using the robust point matching (RPM) algorithm, and volume-based template registration using the Demons algorithm. All three methods show that the older children have bilateral expanded head segments compared to the younger children. The results analyzed based on radial distance to the centerline were consistent with those analyzed using template-based registration methods. In analyses stratified by sex, it was found that the age-associated anatomical changes were similar in boys and girls, but the age-association was strongest in girls. Total hippocampal volume and sub-regional volumes analyzed using manual segmentation did not show a significant age-association. Our results suggest that shape analysis is sensitive to detect sub-regional differences that are not revealed in volumetric analysis. The three methods presented in this study may be applied in future studies to investigate the normal developmental trajectory of the hippocampus in children. They may be further applied to detect early deviations from the normal developmental trajectory in young children for evaluating susceptibility for psychopathological disorders involving hippocampus. Copyright © 2013 ISDN. Published by Elsevier Ltd. All rights reserved.

Image registration algorithm for high-voltage electric power live line working robot based on binocular vision

NASA Astrophysics Data System (ADS)

Li, Chengqi; Ren, Zhigang; Yang, Bo; An, Qinghao; Yu, Xiangru; Li, Jinping

2017-12-01

In the process of dismounting and assembling the drop switch for the high-voltage electric power live line working (EPL2W) robot, one of the key problems is the precision of positioning for manipulators, gripper and the bolts used to fix drop switch. To solve it, we study the binocular vision system theory of the robot and the characteristic of dismounting and assembling drop switch. We propose a coarse-to-fine image registration algorithm based on image correlation, which can improve the positioning precision of manipulators and bolt significantly. The algorithm performs the following three steps: firstly, the target points are marked respectively in the right and left visions, and then the system judges whether the target point in right vision can satisfy the lowest registration accuracy by using the similarity of target points' backgrounds in right and left visions, this is a typical coarse-to-fine strategy; secondly, the system calculates the epipolar line, and then the regional sequence existing matching points is generated according to neighborhood of epipolar line, the optimal matching image is confirmed by calculating the similarity between template image in left vision and the region in regional sequence according to correlation matching; finally, the precise coordinates of target points in right and left visions are calculated according to the optimal matching image. The experiment results indicate that the positioning accuracy of image coordinate is within 2 pixels, the positioning accuracy in the world coordinate system is within 3 mm, the positioning accuracy of binocular vision satisfies the requirement dismounting and assembling the drop switch.

Robust fluoroscopic respiratory gating for lung cancer radiotherapy without implanted fiducial markers

NASA Astrophysics Data System (ADS)

Cui, Ying; Dy, Jennifer G.; Sharp, Greg C.; Alexander, Brian; Jiang, Steve B.

2007-02-01

For gated lung cancer radiotherapy, it is difficult to generate accurate gating signals due to the large uncertainties when using external surrogates and the risk of pneumothorax when using implanted fiducial markers. We have previously investigated and demonstrated the feasibility of generating gating signals using the correlation scores between the reference template image and the fluoroscopic images acquired during the treatment. In this paper, we present an in-depth study, aiming at the improvement of robustness of the algorithm and its validation using multiple sets of patient data. Three different template generating and matching methods have been developed and evaluated: (1) single template method, (2) multiple template method, and (3) template clustering method. Using the fluoroscopic data acquired during patient setup before each fraction of treatment, reference templates are built that represent the tumour position and shape in the gating window, which is assumed to be at the end-of-exhale phase. For the single template method, all the setup images within the gating window are averaged to generate a composite template. For the multiple template method, each setup image in the gating window is considered as a reference template and used to generate an ensemble of correlation scores. All the scores are then combined to generate the gating signal. For the template clustering method, clustering (grouping of similar objects together) is performed to reduce the large number of reference templates into a few representative ones. Each of these methods has been evaluated against the reference gating signal as manually determined by a radiation oncologist. Five patient datasets were used for evaluation. In each case, gated treatments were simulated at both 35% and 50% duty cycles. False positive, negative and total error rates were computed. Experiments show that the single template method is sensitive to noise; the multiple template and clustering methods are more robust to noise due to the smoothing effect of aggregation of correlation scores; and the clustering method results in the best performance in terms of computational efficiency and accuracy.

System and method for detection of dispersed broadband signals

DOEpatents

Qian, S.; Dunham, M.E.

1999-06-08

A system and method for detecting the presence of dispersed broadband signals in real time are disclosed. The present invention utilizes a bank of matched filters for detecting the received dispersed broadband signals. Each matched filter uses a respective robust time template that has been designed to approximate the dispersed broadband signals of interest, and each time template varies across a spectrum of possible dispersed broadband signal time templates. The received dispersed broadband signal x(t) is received by each of the matched filters, and if one or more matches occurs, then the received data is determined to have signal data of interest. This signal data can then be analyzed and/or transmitted to Earth for analysis, as desired. The system and method of the present invention will prove extremely useful in many fields, including satellite communications, plasma physics, and interstellar research. The varying time templates used in the bank of matched filters are determined as follows. The robust time domain template is assumed to take the form w(t)=A(t)cos[l brace]2[phi](t)[r brace]. Since the instantaneous frequency f(t) is known to be equal to the derivative of the phase [phi](t), the trajectory of a joint time-frequency representation of x(t) is used as an approximation of [phi][prime](t). 10 figs.

System and method for detection of dispersed broadband signals

DOEpatents

Qian, Shie; Dunham, Mark E.

1999-06-08

A system and method for detecting the presence of dispersed broadband signals in real time. The present invention utilizes a bank of matched filters for detecting the received dispersed broadband signals. Each matched filter uses a respective robust time template that has been designed to approximate the dispersed broadband signals of interest, and each time template varies across a spectrum of possible dispersed broadband signal time templates. The received dispersed broadband signal x(t) is received by each of the matched filters, and if one or more matches occurs, then the received data is determined to have signal data of interest. This signal data can then be analyzed and/or transmitted to Earth for analysis, as desired. The system and method of the present invention will prove extremely useful in many fields, including satellite communications, plasma physics, and interstellar research. The varying time templates used in the bank of matched filters are determined as follows. The robust time domain template is assumed to take the form w(t)=A(t)cos{2.phi.(t)}. Since the instantaneous frequency f(t) is known to be equal to the derivative of the phase .phi.(t), the trajectory of a joint time-frequency representation of x(t) is used as an approximation of .phi.'(t).

A Hospital-Specific Template for Benchmarking its Cost and Quality

PubMed Central

Silber, Jeffrey H; Rosenbaum, Paul R; Ross, Richard N; Ludwig, Justin M; Wang, Wei; Niknam, Bijan A; Saynisch, Philip A; Even-Shoshan, Orit; Kelz, Rachel R; Fleisher, Lee A

2014-01-01

Objective Develop an improved method for auditing hospital cost and quality tailored to a specific hospital’s patient population. Data Sources/Setting Medicare claims in general, gynecologic and urologic surgery, and orthopedics from Illinois, New York, and Texas between 2004 and 2006. Study Design A template of 300 representative patients from a single index hospital was constructed and used to match 300 patients at 43 hospitals that had a minimum of 500 patients over a 3-year study period. Data Collection/Extraction Methods From each of 43 hospitals we chose 300 patients most resembling the template using multivariate matching. Principal Findings We found close matches on procedures and patient characteristics, far more balanced than would be expected in a randomized trial. There were little to no differences between the index hospital’s template and the 43 hospitals on most patient characteristics yet large and significant differences in mortality, failure-to-rescue, and cost. Conclusion Matching can produce fair, directly standardized audits. From the perspective of the index hospital, “hospital-specific” template matching provides the fairness of direct standardization with the specific institutional relevance of indirect standardization. Using this approach, hospitals will be better able to examine their performance, and better determine why they are achieving the results they observe. PMID:25201167

Deformably registering and annotating whole CLARITY brains to an atlas via masked LDDMM

NASA Astrophysics Data System (ADS)

Kutten, Kwame S.; Vogelstein, Joshua T.; Charon, Nicolas; Ye, Li; Deisseroth, Karl; Miller, Michael I.

2016-04-01

The CLARITY method renders brains optically transparent to enable high-resolution imaging in the structurally intact brain. Anatomically annotating CLARITY brains is necessary for discovering which regions contain signals of interest. Manually annotating whole-brain, terabyte CLARITY images is difficult, time-consuming, subjective, and error-prone. Automatically registering CLARITY images to a pre-annotated brain atlas offers a solution, but is difficult for several reasons. Removal of the brain from the skull and subsequent storage and processing cause variable non-rigid deformations, thus compounding inter-subject anatomical variability. Additionally, the signal in CLARITY images arises from various biochemical contrast agents which only sparsely label brain structures. This sparse labeling challenges the most commonly used registration algorithms that need to match image histogram statistics to the more densely labeled histological brain atlases. The standard method is a multiscale Mutual Information B-spline algorithm that dynamically generates an average template as an intermediate registration target. We determined that this method performs poorly when registering CLARITY brains to the Allen Institute's Mouse Reference Atlas (ARA), because the image histogram statistics are poorly matched. Therefore, we developed a method (Mask-LDDMM) for registering CLARITY images, that automatically finds the brain boundary and learns the optimal deformation between the brain and atlas masks. Using Mask-LDDMM without an average template provided better results than the standard approach when registering CLARITY brains to the ARA. The LDDMM pipelines developed here provide a fast automated way to anatomically annotate CLARITY images; our code is available as open source software at http://NeuroData.io.

Optimizing Multi-Station Template Matching to Identify and Characterize Induced Seismicity in Ohio

NASA Astrophysics Data System (ADS)

Brudzinski, M. R.; Skoumal, R.; Currie, B. S.

2014-12-01

As oil and gas well completions utilizing multi-stage hydraulic fracturing have become more commonplace, the potential for seismicity induced by the deep disposal of frac-related flowback waters and the hydraulic fracturing process itself has become increasingly important. While it is rare for these processes to induce felt seismicity, the recent increase in the number of deep injection wells and volumes injected have been suspected to have contributed to a substantial increase of events = M 3 in the continental U.S. over the past decade. Earthquake template matching using multi-station waveform cross-correlation is an adept tool for investigating potentially induced sequences due to its proficiency at identifying similar/repeating seismic events. We have sought to refine this approach by investigating a variety of seismic sequences and determining the optimal parameters (station combinations, template lengths and offsets, filter frequencies, data access method, etc.) for identifying induced seismicity. When applied to a sequence near a wastewater injection well in Youngstown, Ohio, our optimized template matching routine yielded 566 events while other template matching studies found ~100-200 events. We also identified 77 events on 4-12 March 2014 that are temporally and spatially correlated with active hydraulic fracturing in Poland Township, Ohio. We find similar improvement in characterizing sequences in Washington and Harrison Counties, which appear to be related to wastewater injection and hydraulic fracturing, respectively. In the Youngstown and Poland Township cases, focal mechanisms and double difference relocation using the cross-correlation matrix finds left-lateral faults striking roughly east-west near the top of the basement. We have also used template matching to determine isolated earthquakes near several other wastewater injection wells are unlikely to be induced based on a lack of similar/repeating sequences. Optimized template matching utilizes high-quality reliable stations within pre-existing seismic networks and is therefore a cost-efficient monitoring strategy for identifying and characterizing potentially induced seismic sequences.

Real-Time Tracking by Double Templates Matching Based on Timed Motion History Image with HSV Feature

PubMed Central

Li, Zhiyong; Li, Pengfei; Yu, Xiaoping; Hashem, Mervat

2014-01-01

It is a challenge to represent the target appearance model for moving object tracking under complex environment. This study presents a novel method with appearance model described by double templates based on timed motion history image with HSV color histogram feature (tMHI-HSV). The main components include offline template and online template initialization, tMHI-HSV-based candidate patches feature histograms calculation, double templates matching (DTM) for object location, and templates updating. Firstly, we initialize the target object region and calculate its HSV color histogram feature as offline template and online template. Secondly, the tMHI-HSV is used to segment the motion region and calculate these candidate object patches' color histograms to represent their appearance models. Finally, we utilize the DTM method to trace the target and update the offline template and online template real-timely. The experimental results show that the proposed method can efficiently handle the scale variation and pose change of the rigid and nonrigid objects, even in illumination change and occlusion visual environment. PMID:24592185

Single Neuron Optimization as a Basis for Accurate Biophysical Modeling: The Case of Cerebellar Granule Cells.

PubMed

Masoli, Stefano; Rizza, Martina F; Sgritta, Martina; Van Geit, Werner; Schürmann, Felix; D'Angelo, Egidio

2017-01-01

In realistic neuronal modeling, once the ionic channel complement has been defined, the maximum ionic conductance (G i-max ) values need to be tuned in order to match the firing pattern revealed by electrophysiological recordings. Recently, selection/mutation genetic algorithms have been proposed to efficiently and automatically tune these parameters. Nonetheless, since similar firing patterns can be achieved through different combinations of G i-max values, it is not clear how well these algorithms approximate the corresponding properties of real cells. Here we have evaluated the issue by exploiting a unique opportunity offered by the cerebellar granule cell (GrC), which is electrotonically compact and has therefore allowed the direct experimental measurement of ionic currents. Previous models were constructed using empirical tuning of G i-max values to match the original data set. Here, by using repetitive discharge patterns as a template, the optimization procedure yielded models that closely approximated the experimental G i-max values. These models, in addition to repetitive firing, captured additional features, including inward rectification, near-threshold oscillations, and resonance, which were not used as features. Thus, parameter optimization using genetic algorithms provided an efficient modeling strategy for reconstructing the biophysical properties of neurons and for the subsequent reconstruction of large-scale neuronal network models.

Search algorithm complexity modeling with application to image alignment and matching

NASA Astrophysics Data System (ADS)

DelMarco, Stephen

2014-05-01

Search algorithm complexity modeling, in the form of penetration rate estimation, provides a useful way to estimate search efficiency in application domains which involve searching over a hypothesis space of reference templates or models, as in model-based object recognition, automatic target recognition, and biometric recognition. The penetration rate quantifies the expected portion of the database that must be searched, and is useful for estimating search algorithm computational requirements. In this paper we perform mathematical modeling to derive general equations for penetration rate estimates that are applicable to a wide range of recognition problems. We extend previous penetration rate analyses to use more general probabilistic modeling assumptions. In particular we provide penetration rate equations within the framework of a model-based image alignment application domain in which a prioritized hierarchical grid search is used to rank subspace bins based on matching probability. We derive general equations, and provide special cases based on simplifying assumptions. We show how previously-derived penetration rate equations are special cases of the general formulation. We apply the analysis to model-based logo image alignment in which a hierarchical grid search is used over a geometric misalignment transform hypothesis space. We present numerical results validating the modeling assumptions and derived formulation.

In-Situ Assays Using a New Advanced Mathematical Algorithm - 12400

DOE Office of Scientific and Technical Information (OSTI.GOV)

Oginni, B.M.; Bronson, F.L.; Field, M.B.

2012-07-01

Current mathematical efficiency modeling software for in-situ counting, such as the commercially available In-Situ Object Calibration Software (ISOCS), typically allows the description of measurement geometries via a list of well-defined templates which describe regular objects, such as boxes, cylinder, or spheres. While for many situations, these regular objects are sufficient to describe the measurement conditions, there are occasions in which a more detailed model is desired. We have developed a new all-purpose geometry template that can extend the flexibility of current ISOCS templates. This new template still utilizes the same advanced mathematical algorithms as current templates, but allows the extensionmore » to a multitude of shapes and objects that can be placed at any location and even combined. In addition, detectors can be placed anywhere and aimed at any location within the measurement scene. Several applications of this algorithm to in-situ waste assay measurements, as well as, validations of this template using Monte Carlo calculations and experimental measurements are studied. Presented in this paper is a new template of the mathematical algorithms for evaluating efficiencies. This new template combines all the advantages of the ISOCS and it allows the use of very complex geometries, it also allows stacking of geometries on one another in the same measurement scene and it allows the detector to be placed anywhere in the measurement scene and pointing in any direction. We have shown that the template compares well with the previous ISOCS software within the limit of convergence of the code, and also compare well with the MCNPX and measured data within the joint uncertainties for the code and the data. The new template agrees with ISOCS to within 1.5% at all energies. It agrees with the MCNPX to within 10% at all energies and it agrees with most geometries within 5%. It finally agrees with measured data to within 10%. This mathematical algorithm can now be used for quickly and accurately evaluating efficiencies for wider range of gamma-ray spectroscopy applications. (authors)« less

Enhanced brainstem and cortical evoked response amplitudes: single-trial covariance analysis.

PubMed

Galbraith, G C

2001-06-01

The purpose of the present study was to develop analytic procedures that improve the definition of sensory evoked response components. Such procedures could benefit all recordings but would especially benefit difficult recordings where many trials are contaminated by muscle and movement artifacts. First, cross-correlation and latency adjustment analyses were applied to the human brainstem frequency-following response and cortical auditory evoked response recorded on the same trials. Lagged cross-correlation functions were computed, for each of 17 subjects, between single-trial data and templates consisting of the sinusoid stimulus waveform for the brainstem response and the subject's own smoothed averaged evoked response P2 component for the cortical response. Trials were considered in the analysis only if the maximum correlation-squared (r2) exceeded .5 (negatively correlated trials were thus included). Identical correlation coefficients may be based on signals with quite different amplitudes, but it is possible to assess amplitude by the nonnormalized covariance function. Next, an algorithm is applied in which each trial with negative covariance is matched to a trial with similar, but positive, covariance and these matched-trial pairs are deleted. When an evoked response signal is present in the data, the majority of trials positively correlate with the template. Thus, a residual of positively correlated trials remains after matched covariance trials are deleted. When these residual trials are averaged, the resulting brainstem and cortical responses show greatly enhanced amplitudes. This result supports the utility of this analysis technique in clarifying and assessing evoked response signals.

Infrared dim moving target tracking via sparsity-based discriminative classifier and convolutional network

NASA Astrophysics Data System (ADS)

Qian, Kun; Zhou, Huixin; Wang, Bingjian; Song, Shangzhen; Zhao, Dong

2017-11-01

Infrared dim and small target tracking is a great challenging task. The main challenge for target tracking is to account for appearance change of an object, which submerges in the cluttered background. An efficient appearance model that exploits both the global template and local representation over infrared image sequences is constructed for dim moving target tracking. A Sparsity-based Discriminative Classifier (SDC) and a Convolutional Network-based Generative Model (CNGM) are combined with a prior model. In the SDC model, a sparse representation-based algorithm is adopted to calculate the confidence value that assigns more weights to target templates than negative background templates. In the CNGM model, simple cell feature maps are obtained by calculating the convolution between target templates and fixed filters, which are extracted from the target region at the first frame. These maps measure similarities between each filter and local intensity patterns across the target template, therefore encoding its local structural information. Then, all the maps form a representation, preserving the inner geometric layout of a candidate template. Furthermore, the fixed target template set is processed via an efficient prior model. The same operation is applied to candidate templates in the CNGM model. The online update scheme not only accounts for appearance variations but also alleviates the migration problem. At last, collaborative confidence values of particles are utilized to generate particles' importance weights. Experiments on various infrared sequences have validated the tracking capability of the presented algorithm. Experimental results show that this algorithm runs in real-time and provides a higher accuracy than state of the art algorithms.

VizieR Online Data Catalog: BAL QSOs from SDSS DR3 (Trump+, 2006)

NASA Astrophysics Data System (ADS)

Trump, J. R.; Hall, P. B.; Reichard, T. A.; Richards, G. T.; Schneider, D. P.; vanden Berk, D. E.; Knapp, G. R.; Anderson, S. F.; Fan, X.; Brinkman, J.; Kleinman, S. J.; Nitta, A.

2007-11-01

We present a total of 4784 unique broad absorption line quasars from the Sloan Digital Sky Survey Third Data Release (Cat. ). An automated algorithm was used to match a continuum to each quasar and to identify regions of flux at least 10% below the continuum over a velocity range of at least 1000km/s in the CIV and MgII absorption regions. The model continuum was selected as the best-fit match from a set of template quasar spectra binned in luminosity, emission line width, and redshift, with the power-law spectral index and amount of dust reddening as additional free parameters. We characterize our sample through the traditional balnicity index and a revised absorption index, as well as through parameters such as the width, outflow velocity, fractional depth, and number of troughs. (1 data file).

A comparison of image processing techniques for bird recognition.

PubMed

Nadimpalli, Uma D; Price, Randy R; Hall, Steven G; Bomma, Pallavi

2006-01-01

Bird predation is one of the major concerns for fish culture in open ponds. A novel method for dispersing birds is the use of autonomous vehicles. Image recognition software can improve their efficiency. Several image processing techniques for recognition of birds have been tested. A series of morphological operations were implemented. We divided images into 3 types, Type 1, Type 2, and Type 3, based on the level of difficulty of recognizing birds. Type 1 images were clear; Type 2 images were medium clear, and Type 3 images were unclear. Local thresholding has been implemented using HSV (Hue, Saturation, and Value), GRAY, and RGB (Red, Green, and Blue) color models on all three sections of images and results were tabulated. Template matching using normal correlation and artificial neural networks (ANN) are the other methods that have been developed in this study in addition to image morphology. Template matching produced satisfactory results irrespective of the difficulty level of images, but artificial neural networks produced accuracies of 100, 60, and 50% on Type 1, Type 2, and Type 3 images, respectively. Correct classification rate can be increased by further training. Future research will focus on testing the recognition algorithms in natural or aquacultural settings on autonomous boats. Applications of such techniques to industrial, agricultural, or related areas are additional future possibilities.

Multiscale Reconstruction for Magnetic Resonance Fingerprinting

PubMed Central

Pierre, Eric Y.; Ma, Dan; Chen, Yong; Badve, Chaitra; Griswold, Mark A.

2015-01-01

Purpose To reduce acquisition time needed to obtain reliable parametric maps with Magnetic Resonance Fingerprinting. Methods An iterative-denoising algorithm is initialized by reconstructing the MRF image series at low image resolution. For subsequent iterations, the method enforces pixel-wise fidelity to the best-matching dictionary template then enforces fidelity to the acquired data at slightly higher spatial resolution. After convergence, parametric maps with desirable spatial resolution are obtained through template matching of the final image series. The proposed method was evaluated on phantom and in-vivo data using the highly-undersampled, variable-density spiral trajectory and compared with the original MRF method. The benefits of additional sparsity constraints were also evaluated. When available, gold standard parameter maps were used to quantify the performance of each method. Results The proposed approach allowed convergence to accurate parametric maps with as few as 300 time points of acquisition, as compared to 1000 in the original MRF work. Simultaneous quantification of T1, T2, proton density (PD) and B0 field variations in the brain was achieved in vivo for a 256×256 matrix for a total acquisition time of 10.2s, representing a 3-fold reduction in acquisition time. Conclusions The proposed iterative multiscale reconstruction reliably increases MRF acquisition speed and accuracy. PMID:26132462

Action detection by double hierarchical multi-structure space-time statistical matching model

NASA Astrophysics Data System (ADS)

Han, Jing; Zhu, Junwei; Cui, Yiyin; Bai, Lianfa; Yue, Jiang

2018-03-01

Aimed at the complex information in videos and low detection efficiency, an actions detection model based on neighboring Gaussian structure and 3D LARK features is put forward. We exploit a double hierarchical multi-structure space-time statistical matching model (DMSM) in temporal action localization. First, a neighboring Gaussian structure is presented to describe the multi-scale structural relationship. Then, a space-time statistical matching method is proposed to achieve two similarity matrices on both large and small scales, which combines double hierarchical structural constraints in model by both the neighboring Gaussian structure and the 3D LARK local structure. Finally, the double hierarchical similarity is fused and analyzed to detect actions. Besides, the multi-scale composite template extends the model application into multi-view. Experimental results of DMSM on the complex visual tracker benchmark data sets and THUMOS 2014 data sets show the promising performance. Compared with other state-of-the-art algorithm, DMSM achieves superior performances.

Action detection by double hierarchical multi-structure space–time statistical matching model

NASA Astrophysics Data System (ADS)

Han, Jing; Zhu, Junwei; Cui, Yiyin; Bai, Lianfa; Yue, Jiang

2018-06-01

Aimed at the complex information in videos and low detection efficiency, an actions detection model based on neighboring Gaussian structure and 3D LARK features is put forward. We exploit a double hierarchical multi-structure space-time statistical matching model (DMSM) in temporal action localization. First, a neighboring Gaussian structure is presented to describe the multi-scale structural relationship. Then, a space-time statistical matching method is proposed to achieve two similarity matrices on both large and small scales, which combines double hierarchical structural constraints in model by both the neighboring Gaussian structure and the 3D LARK local structure. Finally, the double hierarchical similarity is fused and analyzed to detect actions. Besides, the multi-scale composite template extends the model application into multi-view. Experimental results of DMSM on the complex visual tracker benchmark data sets and THUMOS 2014 data sets show the promising performance. Compared with other state-of-the-art algorithm, DMSM achieves superior performances.

Rapid and Robust Cross-Correlation-Based Seismic Phase Identification Using an Approximate Nearest Neighbor Method

NASA Astrophysics Data System (ADS)

Tibi, R.; Young, C. J.; Gonzales, A.; Ballard, S.; Encarnacao, A. V.

2016-12-01

The matched filtering technique involving the cross-correlation of a waveform of interest with archived signals from a template library has proven to be a powerful tool for detecting events in regions with repeating seismicity. However, waveform correlation is computationally expensive, and therefore impractical for large template sets unless dedicated distributed computing hardware and software are used. In this study, we introduce an Approximate Nearest Neighbor (ANN) approach that enables the use of very large template libraries for waveform correlation without requiring a complex distributed computing system. Our method begins with a projection into a reduced dimensionality space based on correlation with a randomized subset of the full template archive. Searching for a specified number of nearest neighbors is accomplished by using randomized K-dimensional trees. We used the approach to search for matches to each of 2700 analyst-reviewed signal detections reported for May 2010 for the IMS station MKAR. The template library in this case consists of a dataset of more than 200,000 analyst-reviewed signal detections for the same station from 2002-2014 (excluding May 2010). Of these signal detections, 60% are teleseismic first P, and 15% regional phases (Pn, Pg, Sn, and Lg). The analyses performed on a standard desktop computer shows that the proposed approach performs the search of the large template libraries about 20 times faster than the standard full linear search, while achieving recall rates greater than 80%, with the recall rate increasing for higher correlation values. To decide whether to confirm a match, we use a hybrid method involving a cluster approach for queries with two or more matches, and correlation score for single matches. Of the signal detections that passed our confirmation process, 52% were teleseismic first P, and 30% were regional phases.

Vision-based vehicle detection and tracking algorithm design

NASA Astrophysics Data System (ADS)

Hwang, Junyeon; Huh, Kunsoo; Lee, Donghwi

2009-12-01

The vision-based vehicle detection in front of an ego-vehicle is regarded as promising for driver assistance as well as for autonomous vehicle guidance. The feasibility of vehicle detection in a passenger car requires accurate and robust sensing performance. A multivehicle detection system based on stereo vision has been developed for better accuracy and robustness. This system utilizes morphological filter, feature detector, template matching, and epipolar constraint techniques in order to detect the corresponding pairs of vehicles. After the initial detection, the system executes the tracking algorithm for the vehicles. The proposed system can detect front vehicles such as the leading vehicle and side-lane vehicles. The position parameters of the vehicles located in front are obtained based on the detection information. The proposed vehicle detection system is implemented on a passenger car, and its performance is verified experimentally.

Object-oriented recognition of high-resolution remote sensing image

NASA Astrophysics Data System (ADS)

Wang, Yongyan; Li, Haitao; Chen, Hong; Xu, Yuannan

2016-01-01

With the development of remote sensing imaging technology and the improvement of multi-source image's resolution in satellite visible light, multi-spectral and hyper spectral , the high resolution remote sensing image has been widely used in various fields, for example military field, surveying and mapping, geophysical prospecting, environment and so forth. In remote sensing image, the segmentation of ground targets, feature extraction and the technology of automatic recognition are the hotspot and difficulty in the research of modern information technology. This paper also presents an object-oriented remote sensing image scene classification method. The method is consist of vehicles typical objects classification generation, nonparametric density estimation theory, mean shift segmentation theory, multi-scale corner detection algorithm, local shape matching algorithm based on template. Remote sensing vehicles image classification software system is designed and implemented to meet the requirements .

Vertebra identification using template matching modelmp and K-means clustering.

PubMed

Larhmam, Mohamed Amine; Benjelloun, Mohammed; Mahmoudi, Saïd

2014-03-01

Accurate vertebra detection and segmentation are essential steps for automating the diagnosis of spinal disorders. This study is dedicated to vertebra alignment measurement, the first step in a computer-aided diagnosis tool for cervical spine trauma. Automated vertebral segment alignment determination is a challenging task due to low contrast imaging and noise. A software tool for segmenting vertebrae and detecting subluxations has clinical significance. A robust method was developed and tested for cervical vertebra identification and segmentation that extracts parameters used for vertebra alignment measurement. Our contribution involves a novel combination of a template matching method and an unsupervised clustering algorithm. In this method, we build a geometric vertebra mean model. To achieve vertebra detection, manual selection of the region of interest is performed initially on the input image. Subsequent preprocessing is done to enhance image contrast and detect edges. Candidate vertebra localization is then carried out by using a modified generalized Hough transform (GHT). Next, an adapted cost function is used to compute local voted centers and filter boundary data. Thereafter, a K-means clustering algorithm is applied to obtain clusters distribution corresponding to the targeted vertebrae. These clusters are combined with the vote parameters to detect vertebra centers. Rigid segmentation is then carried out by using GHT parameters. Finally, cervical spine curves are extracted to measure vertebra alignment. The proposed approach was successfully applied to a set of 66 high-resolution X-ray images. Robust detection was achieved in 97.5 % of the 330 tested cervical vertebrae. An automated vertebral identification method was developed and demonstrated to be robust to noise and occlusion. This work presents a first step toward an automated computer-aided diagnosis system for cervical spine trauma detection.

Structural action recognition in body sensor networks: distributed classification based on string matching.

PubMed

Ghasemzadeh, Hassan; Loseu, Vitali; Jafari, Roozbeh

2010-03-01

Mobile sensor-based systems are emerging as promising platforms for healthcare monitoring. An important goal of these systems is to extract physiological information about the subject wearing the network. Such information can be used for life logging, quality of life measures, fall detection, extraction of contextual information, and many other applications. Data collected by these sensor nodes are overwhelming, and hence, an efficient data processing technique is essential. In this paper, we present a system using inexpensive, off-the-shelf inertial sensor nodes that constructs motion transcripts from biomedical signals and identifies movements by taking collaboration between the nodes into consideration. Transcripts are built of motion primitives and aim to reduce the complexity of the original data. We then label each primitive with a unique symbol and generate a sequence of symbols, known as motion template, representing a particular action. This model leads to a distributed algorithm for action recognition using edit distance with respect to motion templates. The algorithm reduces the number of active nodes during every classification decision. We present our results using data collected from five normal subjects performing transitional movements. The results clearly illustrate the effectiveness of our framework. In particular, we obtain a classification accuracy of 84.13% with only one sensor node involved in the classification process.

A narrow band pattern-matching model of vowel perception

NASA Astrophysics Data System (ADS)

Hillenbrand, James M.; Houde, Robert A.

2003-02-01

The purpose of this paper is to propose and evaluate a new model of vowel perception which assumes that vowel identity is recognized by a template-matching process involving the comparison of narrow band input spectra with a set of smoothed spectral-shape templates that are learned through ordinary exposure to speech. In the present simulation of this process, the input spectra are computed over a sufficiently long window to resolve individual harmonics of voiced speech. Prior to template creation and pattern matching, the narrow band spectra are amplitude equalized by a spectrum-level normalization process, and the information-bearing spectral peaks are enhanced by a ``flooring'' procedure that zeroes out spectral values below a threshold function consisting of a center-weighted running average of spectral amplitudes. Templates for each vowel category are created simply by averaging the narrow band spectra of like vowels spoken by a panel of talkers. In the present implementation, separate templates are used for men, women, and children. The pattern matching is implemented with a simple city-block distance measure given by the sum of the channel-by-channel differences between the narrow band input spectrum (level-equalized and floored) and each vowel template. Spectral movement is taken into account by computing the distance measure at several points throughout the course of the vowel. The input spectrum is assigned to the vowel template that results in the smallest difference accumulated over the sequence of spectral slices. The model was evaluated using a large database consisting of 12 vowels in /hVd/ context spoken by 45 men, 48 women, and 46 children. The narrow band model classified vowels in this database with a degree of accuracy (91.4%) approaching that of human listeners.

Automated real-time search and analysis algorithms for a non-contact 3D profiling system

NASA Astrophysics Data System (ADS)

Haynes, Mark; Wu, Chih-Hang John; Beck, B. Terry; Peterman, Robert J.

2013-04-01

The purpose of this research is to develop a new means of identifying and extracting geometrical feature statistics from a non-contact precision-measurement 3D profilometer. Autonomous algorithms have been developed to search through large-scale Cartesian point clouds to identify and extract geometrical features. These algorithms are developed with the intent of providing real-time production quality control of cold-rolled steel wires. The steel wires in question are prestressing steel reinforcement wires for concrete members. The geometry of the wire is critical in the performance of the overall concrete structure. For this research a custom 3D non-contact profilometry system has been developed that utilizes laser displacement sensors for submicron resolution surface profiling. Optimizations in the control and sensory system allow for data points to be collected at up to an approximate 400,000 points per second. In order to achieve geometrical feature extraction and tolerancing with this large volume of data, the algorithms employed are optimized for parsing large data quantities. The methods used provide a unique means of maintaining high resolution data of the surface profiles while keeping algorithm running times within practical bounds for industrial application. By a combination of regional sampling, iterative search, spatial filtering, frequency filtering, spatial clustering, and template matching a robust feature identification method has been developed. These algorithms provide an autonomous means of verifying tolerances in geometrical features. The key method of identifying the features is through a combination of downhill simplex and geometrical feature templates. By performing downhill simplex through several procedural programming layers of different search and filtering techniques, very specific geometrical features can be identified within the point cloud and analyzed for proper tolerancing. Being able to perform this quality control in real time provides significant opportunities in cost savings in both equipment protection and waste minimization.

Mutual information-based template matching scheme for detection of breast masses: from mammography to digital breast tomosynthesis

PubMed Central

Mazurowski, Maciej A; Lo, Joseph Y; Harrawood, Brian P; Tourassi, Georgia D

2011-01-01

Development of a computational decision aid for a new medical imaging modality typically is a long and complicated process. It consists of collecting data in the form of images and annotations, development of image processing and pattern recognition algorithms for analysis of the new images and finally testing of the resulting system. Since new imaging modalities are developed more rapidly than ever before, any effort for decreasing the time and cost of this development process could result in maximizing the benefit of the new imaging modality to patients by making the computer aids quickly available to radiologists that interpret the images. In this paper, we make a step in this direction and investigate the possibility of translating the knowledge about the detection problem from one imaging modality to another. Specifically, we present a computer-aided detection (CAD) system for mammographic masses that uses a mutual information-based template matching scheme with intelligently selected templates. We presented principles of template matching with mutual information for mammography before. In this paper, we present an implementation of those principles in a complete computer-aided detection system. The proposed system, through an automatic optimization process, chooses the most useful templates (mammographic regions of interest) using a large database of previously collected and annotated mammograms. Through this process, the knowledge about the task of detecting masses in mammograms is incorporated in the system. Then we evaluate whether our system developed for screen-film mammograms can be successfully applied not only to other mammograms but also to digital breast tomosynthesis (DBT) reconstructed slices without adding any DBT cases for training. Our rationale is that since mutual information is known to be a robust intermodality image similarity measure, it has high potential of transferring knowledge between modalities in the context of the mass detection task. Experimental evaluation of the system on mammograms showed competitive performance compared to other mammography CAD systems recently published in the literature. When the system was applied “as-is” to DBT, its performance was notably worse than that for mammograms. However, with a simple additional preprocessing step, the performance of the system reached levels similar to that obtained for mammograms. In conclusion, the presented CAD system not only performed competitively on screen-film mammograms but it also performed robustly on DBT showing that direct transfer of knowledge across breast imaging modalities for mass detection is in fact possible. PMID:21554985

NOTE: Fluoroscopic gating without implanted fiducial markers for lung cancer radiotherapy based on support vector machines

NASA Astrophysics Data System (ADS)

Cui, Ying; Dy, Jennifer G.; Alexander, Brian; Jiang, Steve B.

2008-08-01

Various problems with the current state-of-the-art techniques for gated radiotherapy have prevented this new treatment modality from being widely implemented in clinical routine. These problems are caused mainly by applying various external respiratory surrogates. There might be large uncertainties in deriving the tumor position from external respiratory surrogates. While tracking implanted fiducial markers has sufficient accuracy, this procedure may not be widely accepted due to the risk of pneumothorax. Previously, we have developed a technique to generate gating signals from fluoroscopic images without implanted fiducial markers using template matching methods (Berbeco et al 2005 Phys. Med. Biol. 50 4481-90, Cui et al 2007b Phys. Med. Biol. 52 741-55). In this note, our main contribution is to provide a totally different new view of the gating problem by recasting it as a classification problem. Then, we solve this classification problem by a well-studied powerful classification method called a support vector machine (SVM). Note that the goal of an automated gating tool is to decide when to turn the beam ON or OFF. We treat ON and OFF as the two classes in our classification problem. We create our labeled training data during the patient setup session by utilizing the reference gating signal, manually determined by a radiation oncologist. We then pre-process these labeled training images and build our SVM prediction model. During treatment delivery, fluoroscopic images are continuously acquired, pre-processed and sent as an input to the SVM. Finally, our SVM model will output the predicted labels as gating signals. We test the proposed technique on five sequences of fluoroscopic images from five lung cancer patients against the reference gating signal as ground truth. We compare the performance of the SVM to our previous template matching method (Cui et al 2007b Phys. Med. Biol. 52 741-55). We find that the SVM is slightly more accurate on average (1-3%) than the template matching method, when delivering the target dose. And the average duty cycle is 4-6% longer. Given the very limited patient dataset, we cannot conclude that the SVM is more accurate and efficient than the template matching method. However, our preliminary results show that the SVM is a potentially precise and efficient algorithm for generating gating signals for radiotherapy. This work demonstrates that the gating problem can be considered as a classification problem and solved accordingly.

Iris Matching Based on Personalized Weight Map.

PubMed

Dong, Wenbo; Sun, Zhenan; Tan, Tieniu

2011-09-01

Iris recognition typically involves three steps, namely, iris image preprocessing, feature extraction, and feature matching. The first two steps of iris recognition have been well studied, but the last step is less addressed. Each human iris has its unique visual pattern and local image features also vary from region to region, which leads to significant differences in robustness and distinctiveness among the feature codes derived from different iris regions. However, most state-of-the-art iris recognition methods use a uniform matching strategy, where features extracted from different regions of the same person or the same region for different individuals are considered to be equally important. This paper proposes a personalized iris matching strategy using a class-specific weight map learned from the training images of the same iris class. The weight map can be updated online during the iris recognition procedure when the successfully recognized iris images are regarded as the new training data. The weight map reflects the robustness of an encoding algorithm on different iris regions by assigning an appropriate weight to each feature code for iris matching. Such a weight map trained by sufficient iris templates is convergent and robust against various noise. Extensive and comprehensive experiments demonstrate that the proposed personalized iris matching strategy achieves much better iris recognition performance than uniform strategies, especially for poor quality iris images.

Evaluation of MRI and cannabinoid type 1 receptor PET templates constructed using DARTEL for spatial normalization of rat brains

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kronfeld, Andrea; Müller-Forell, Wibke; Buchholz, Hans-Georg

Purpose: Image registration is one prerequisite for the analysis of brain regions in magnetic-resonance-imaging (MRI) or positron-emission-tomography (PET) studies. Diffeomorphic anatomical registration through exponentiated Lie algebra (DARTEL) is a nonlinear, diffeomorphic algorithm for image registration and construction of image templates. The goal of this small animal study was (1) the evaluation of a MRI and calculation of several cannabinoid type 1 (CB1) receptor PET templates constructed using DARTEL and (2) the analysis of the image registration accuracy of MR and PET images to their DARTEL templates with reference to analytical and iterative PET reconstruction algorithms. Methods: Five male Sprague Dawleymore » rats were investigated for template construction using MRI and [{sup 18}F]MK-9470 PET for CB1 receptor representation. PET images were reconstructed using the algorithms filtered back-projection, ordered subset expectation maximization in 2D, and maximum a posteriori in 3D. Landmarks were defined on each MR image, and templates were constructed under different settings, i.e., based on different tissue class images [gray matter (GM), white matter (WM), and GM + WM] and regularization forms (“linear elastic energy,” “membrane energy,” and “bending energy”). Registration accuracy for MRI and PET templates was evaluated by means of the distance between landmark coordinates. Results: The best MRI template was constructed based on gray and white matter images and the regularization form linear elastic energy. In this case, most distances between landmark coordinates were <1 mm. Accordingly, MRI-based spatial normalization was most accurate, but results of the PET-based spatial normalization were quite comparable. Conclusions: Image registration using DARTEL provides a standardized and automatic framework for small animal brain data analysis. The authors were able to show that this method works with high reliability and validity. Using DARTEL templates together with nonlinear registration algorithms allows for accurate spatial normalization of combined MRI/PET or PET-only studies.« less

Security enhanced BioEncoding for protecting iris codes

NASA Astrophysics Data System (ADS)

Ouda, Osama; Tsumura, Norimichi; Nakaguchi, Toshiya

2011-06-01

Improving the security of biometric template protection techniques is a key prerequisite for the widespread deployment of biometric technologies. BioEncoding is a recently proposed template protection scheme, based on the concept of cancelable biometrics, for protecting biometric templates represented as binary strings such as iris codes. The main advantage of BioEncoding over other template protection schemes is that it does not require user-specific keys and/or tokens during verification. Besides, it satisfies all the requirements of the cancelable biometrics construct without deteriorating the matching accuracy. However, although it has been shown that BioEncoding is secure enough against simple brute-force search attacks, the security of BioEncoded templates against more smart attacks, such as record multiplicity attacks, has not been sufficiently investigated. In this paper, a rigorous security analysis of BioEncoding is presented. Firstly, resistance of BioEncoded templates against brute-force attacks is revisited thoroughly. Secondly, we show that although the cancelable transformation employed in BioEncoding might be non-invertible for a single protected template, the original iris code could be inverted by correlating several templates used in different applications but created from the same iris. Accordingly, we propose an important modification to the BioEncoding transformation process in order to hinder attackers from exploiting this type of attacks. The effectiveness of adopting the suggested modification is validated and its impact on the matching accuracy is investigated empirically using CASIA-IrisV3-Interval dataset. Experimental results confirm the efficacy of the proposed approach and show that it preserves the matching accuracy of the unprotected iris recognition system.

Task demands determine the specificity of the search template.

PubMed

Bravo, Mary J; Farid, Hany

2012-01-01

When searching for an object, an observer holds a representation of the target in mind while scanning the scene. If the observer repeats the search, performance may become more efficient as the observer hones this target representation, or "search template," to match the specific demands of the search task. An effective search template must have two characteristics: It must reliably discriminate the target from the distractors, and it must tolerate variability in the appearance of the target. The present experiment examined how the tolerance of the search template is affected by the search task. Two groups of 18 observers trained on the same set of stimuli blocked either by target image (block-by-image group) or by target category (block-by-category group). One or two days after training, both groups were tested on a related search task. The pattern of test results revealed that the two groups of observers had developed different search templates, and that the templates of the block-by-category observers better captured the general characteristics of the category. These results demonstrate that observers match their search templates to the demands of the search task.

Discriminative structural approaches for enzyme active-site prediction.

PubMed

Kato, Tsuyoshi; Nagano, Nozomi

2011-02-15

Predicting enzyme active-sites in proteins is an important issue not only for protein sciences but also for a variety of practical applications such as drug design. Because enzyme reaction mechanisms are based on the local structures of enzyme active-sites, various template-based methods that compare local structures in proteins have been developed to date. In comparing such local sites, a simple measurement, RMSD, has been used so far. This paper introduces new machine learning algorithms that refine the similarity/deviation for comparison of local structures. The similarity/deviation is applied to two types of applications, single template analysis and multiple template analysis. In the single template analysis, a single template is used as a query to search proteins for active sites, whereas a protein structure is examined as a query to discover the possible active-sites using a set of templates in the multiple template analysis. This paper experimentally illustrates that the machine learning algorithms effectively improve the similarity/deviation measurements for both the analyses.

Mapping of a standard documentation template to the ICF core sets for arthritis and low back pain.

PubMed

Escorpizo, Reuben; Davis, Kandace; Stumbo, Teri

2010-12-01

To identify the contents of a documentation template in The Guide to Physical Therapist Practice using the International Classification of Functioning, Disability, and Health (ICF) Core Sets for rheumatoid arthritis, osteoarthritis, and low back pain (LBP) as reference. Concepts were identified from items of an outpatient documentation template and mapped to the ICF using established linking rules. The ICF categories that were linked were compared with existing arthritis and LBP Core Sets. Based on the ICF, the template had the highest number (29%) of linked categories under Activities and participation while Body structures had the least (17%). ICF categories in the arthritis and LBP Core Sets had a 37-55% match with the ICF categories found in the template. We found 164 concepts that were not classified or not defined and 37 as personal factors. The arthritis and LBP Core Sets were reflected in the contents of the template. ICF categories in the Core Sets were reflected in the template (demonstrating up to 55% match). Potential integration of ICF in documentation templates could be explored and examined in the future to enhance clinical encounters and multidisciplinary communication. Copyright © 2010 John Wiley & Sons, Ltd.

SU-G-206-01: A Fully Automated CT Tool to Facilitate Phantom Image QA for Quantitative Imaging in Clinical Trials

DOE Office of Scientific and Technical Information (OSTI.GOV)

Wahi-Anwar, M; Lo, P; Kim, H

Purpose: The use of Quantitative Imaging (QI) methods in Clinical Trials requires both verification of adherence to a specified protocol and an assessment of scanner performance under that protocol, which are currently accomplished manually. This work introduces automated phantom identification and image QA measure extraction towards a fully-automated CT phantom QA system to perform these functions and facilitate the use of Quantitative Imaging methods in clinical trials. Methods: This study used a retrospective cohort of CT phantom scans from existing clinical trial protocols - totaling 84 phantoms, across 3 phantom types using various scanners and protocols. The QA system identifiesmore » the input phantom scan through an ensemble of threshold-based classifiers. Each classifier - corresponding to a phantom type - contains a template slice, which is compared to the input scan on a slice-by-slice basis, resulting in slice-wise similarity metric values for each slice compared. Pre-trained thresholds (established from a training set of phantom images matching the template type) are used to filter the similarity distribution, and the slice with the most optimal local mean similarity, with local neighboring slices meeting the threshold requirement, is chosen as the classifier’s matched slice (if it existed). The classifier with the matched slice possessing the most optimal local mean similarity is then chosen as the ensemble’s best matching slice. If the best matching slice exists, image QA algorithm and ROIs corresponding to the matching classifier extracted the image QA measures. Results: Automated phantom identification performed with 84.5% accuracy and 88.8% sensitivity on 84 phantoms. Automated image quality measurements (following standard protocol) on identified water phantoms (n=35) matched user QA decisions with 100% accuracy. Conclusion: We provide a fullyautomated CT phantom QA system consistent with manual QA performance. Further work will include parallel component to automatically verify image acquisition parameters and automated adherence to specifications. Institutional research agreement, Siemens Healthcare; Past recipient, research grant support, Siemens Healthcare; Consultant, Toshiba America Medical Systems; Consultant, Samsung Electronics; NIH Grant support from: U01 CA181156.« less

A real-time TV logo tracking method using template matching

NASA Astrophysics Data System (ADS)

Li, Zhi; Sang, Xinzhu; Yan, Binbin; Leng, Junmin

2012-11-01

A fast and accurate TV Logo detection method is presented based on real-time image filtering, noise eliminating and recognition of image features including edge and gray level information. It is important to accurately extract the optical template using the time averaging method from the sample video stream, and then different templates are used to match different logos in separated video streams with different resolution based on the topology features of logos. 12 video streams with different logos are used to verify the proposed method, and the experimental result demonstrates that the achieved accuracy can be up to 99%.

Object Tracking and Target Reacquisition Based on 3-D Range Data for Moving Vehicles

PubMed Central

Lee, Jehoon; Lankton, Shawn; Tannenbaum, Allen

2013-01-01

In this paper, we propose an approach for tracking an object of interest based on 3-D range data. We employ particle filtering and active contours to simultaneously estimate the global motion of the object and its local deformations. The proposed algorithm takes advantage of range information to deal with the challenging (but common) situation in which the tracked object disappears from the image domain entirely and reappears later. To cope with this problem, a method based on principle component analysis (PCA) of shape information is proposed. In the proposed method, if the target disappears out of frame, shape similarity energy is used to detect target candidates that match a template shape learned online from previously observed frames. Thus, we require no a priori knowledge of the target’s shape. Experimental results show the practical applicability and robustness of the proposed algorithm in realistic tracking scenarios. PMID:21486717

Automatic segmentation of mandible in panoramic x-ray.

PubMed

Abdi, Amir Hossein; Kasaei, Shohreh; Mehdizadeh, Mojdeh

2015-10-01

As the panoramic x-ray is the most common extraoral radiography in dentistry, segmentation of its anatomical structures facilitates diagnosis and registration of dental records. This study presents a fast and accurate method for automatic segmentation of mandible in panoramic x-rays. In the proposed four-step algorithm, a superior border is extracted through horizontal integral projections. A modified Canny edge detector accompanied by morphological operators extracts the inferior border of the mandible body. The exterior borders of ramuses are extracted through a contour tracing method based on the average model of mandible. The best-matched template is fetched from the atlas of mandibles to complete the contour of left and right processes. The algorithm was tested on a set of 95 panoramic x-rays. Evaluating the results against manual segmentations of three expert dentists showed that the method is robust. It achieved an average performance of [Formula: see text] in Dice similarity, specificity, and sensitivity.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Panfil, J; Patel, R; Surucu, M

Purpose: To compare markerless template-based tracking of lung tumors using dual energy (DE) cone-beam computed tomography (CBCT) projections versus single energy (SE) CBCT projections. Methods: A RANDO chest phantom with a simulated tumor in the upper right lung was used to investigate the effectiveness of tumor tracking using DE and SE CBCT projections. Planar kV projections from CBCT acquisitions were captured at 60 kVp (4 mAs) and 120 kVp (1 mAs) using the Varian TrueBeam and non-commercial iTools Capture software. Projections were taken at approximately every 0.53° while the gantry rotated. Due to limitations of the phantom, angles for whichmore » the shoulders blocked the tumor were excluded from tracking analysis. DE images were constructed using a weighted logarithmic subtraction that removed bony anatomy while preserving soft tissue structures. The tumors were tracked separately on DE and SE (120 kVp) images using a template-based tracking algorithm. The tracking results were compared to ground truth coordinates designated by a physician. Matches with a distance of greater than 3 mm from ground truth were designated as failing to track. Results: 363 frames were analyzed. The algorithm successfully tracked the tumor on 89.8% (326/363) of DE frames compared to 54.3% (197/363) of SE frames (p<0.0001). Average distance between tracking and ground truth coordinates was 1.27 +/− 0.67 mm for DE versus 1.83+/−0.74 mm for SE (p<0.0001). Conclusion: This study demonstrates the effectiveness of markerless template-based tracking using DE CBCT. DE imaging resulted in better detectability with more accurate localization on average versus SE. Supported by a grant from Varian Medical Systems.« less

The concept of template-based de novo design from drug-derived molecular fragments and its application to TAR RNA.

PubMed

Schüller, Andreas; Suhartono, Marcel; Fechner, Uli; Tanrikulu, Yusuf; Breitung, Sven; Scheffer, Ute; Göbel, Michael W; Schneider, Gisbert

2008-02-01

Principles of fragment-based molecular design are presented and discussed in the context of de novo drug design. The underlying idea is to dissect known drug molecules in fragments by straightforward pseudo-retro-synthesis. The resulting building blocks are then used for automated assembly of new molecules. A particular question has been whether this approach is actually able to perform scaffold-hopping. A prospective case study illustrates the usefulness of fragment-based de novo design for finding new scaffolds. We were able to identify a novel ligand disrupting the interaction between the Tat peptide and TAR RNA, which is part of the human immunodeficiency virus (HIV-1) mRNA. Using a single template structure (acetylpromazine) as reference molecule and a topological pharmacophore descriptor (CATS), new chemotypes were automatically generated by our de novo design software Flux. Flux features an evolutionary algorithm for fragment-based compound assembly and optimization. Pharmacophore superimposition and docking into the target RNA suggest perfect matching between the template molecule and the designed compound. Chemical synthesis was straightforward, and bioactivity of the designed molecule was confirmed in a FRET assay. This study demonstrates the practicability of de novo design to generating RNA ligands containing novel molecular scaffolds.

3D Facial Pattern Analysis for Autism

DTIC Science & Technology

2010-07-01

each individual’s data were scaled by the geometric mean of all possible linear distances between landmarks, following. The first two principal...over traditional template matching in that it can represent geometrical and non- geometrical changes of an object in the parametric template space...set of vertex templates can be generated from the root template by geometric or non- geometric transformation. Let Mtt ,...1 be M normalized vertex

Morphometry Based on Effective and Accurate Correspondences of Localized Patterns (MEACOLP)

PubMed Central

Wang, Hu; Ren, Yanshuang; Bai, Lijun; Zhang, Wensheng; Tian, Jie

2012-01-01

Local features in volumetric images have been used to identify correspondences of localized anatomical structures for brain morphometry. However, the correspondences are often sparse thus ineffective in reflecting the underlying structures, making it unreliable to evaluate specific morphological differences. This paper presents a morphometry method (MEACOLP) based on correspondences with improved effectiveness and accuracy. A novel two-level scale-invariant feature transform is used to enhance the detection repeatability of local features and to recall the correspondences that might be missed in previous studies. Template patterns whose correspondences could be commonly identified in each group are constructed to serve as the basis for morphometric analysis. A matching algorithm is developed to reduce the identification errors by comparing neighboring local features and rejecting unreliable matches. The two-sample t-test is finally adopted to analyze specific properties of the template patterns. Experiments are performed on the public OASIS database to clinically analyze brain images of Alzheimer's disease (AD) and normal controls (NC). MEACOLP automatically identifies known morphological differences between AD and NC brains, and characterizes the differences well as the scaling and translation of underlying structures. Most of the significant differences are identified in only a single hemisphere, indicating that AD-related structures are characterized by strong anatomical asymmetry. In addition, classification trials to differentiate AD subjects from NC confirm that the morphological differences are reliably related to the groups of interest. PMID:22540000

Multiscale reconstruction for MR fingerprinting.

PubMed

Pierre, Eric Y; Ma, Dan; Chen, Yong; Badve, Chaitra; Griswold, Mark A

2016-06-01

To reduce the acquisition time needed to obtain reliable parametric maps with Magnetic Resonance Fingerprinting. An iterative-denoising algorithm is initialized by reconstructing the MRF image series at low image resolution. For subsequent iterations, the method enforces pixel-wise fidelity to the best-matching dictionary template then enforces fidelity to the acquired data at slightly higher spatial resolution. After convergence, parametric maps with desirable spatial resolution are obtained through template matching of the final image series. The proposed method was evaluated on phantom and in vivo data using the highly undersampled, variable-density spiral trajectory and compared with the original MRF method. The benefits of additional sparsity constraints were also evaluated. When available, gold standard parameter maps were used to quantify the performance of each method. The proposed approach allowed convergence to accurate parametric maps with as few as 300 time points of acquisition, as compared to 1000 in the original MRF work. Simultaneous quantification of T1, T2, proton density (PD), and B0 field variations in the brain was achieved in vivo for a 256 × 256 matrix for a total acquisition time of 10.2 s, representing a three-fold reduction in acquisition time. The proposed iterative multiscale reconstruction reliably increases MRF acquisition speed and accuracy. Magn Reson Med 75:2481-2492, 2016. © 2015 Wiley Periodicals, Inc. © 2015 Wiley Periodicals, Inc.

New development of the image matching algorithm

NASA Astrophysics Data System (ADS)

Zhang, Xiaoqiang; Feng, Zhao

2018-04-01

To study the image matching algorithm, algorithm four elements are described, i.e., similarity measurement, feature space, search space and search strategy. Four common indexes for evaluating the image matching algorithm are described, i.e., matching accuracy, matching efficiency, robustness and universality. Meanwhile, this paper describes the principle of image matching algorithm based on the gray value, image matching algorithm based on the feature, image matching algorithm based on the frequency domain analysis, image matching algorithm based on the neural network and image matching algorithm based on the semantic recognition, and analyzes their characteristics and latest research achievements. Finally, the development trend of image matching algorithm is discussed. This study is significant for the algorithm improvement, new algorithm design and algorithm selection in practice.

A new combined surface and volume registration

NASA Astrophysics Data System (ADS)

Lepore, Natasha; Joshi, Anand A.; Leahy, Richard M.; Brun, Caroline; Chou, Yi-Yu; Pennec, Xavier; Lee, Agatha D.; Barysheva, Marina; De Zubicaray, Greig I.; Wright, Margaret J.; McMahon, Katie L.; Toga, Arthur W.; Thompson, Paul M.

2010-03-01

3D registration of brain MRI data is vital for many medical imaging applications. However, purely intensitybased approaches for inter-subject matching of brain structure are generally inaccurate in cortical regions, due to the highly complex network of sulci and gyri, which vary widely across subjects. Here we combine a surfacebased cortical registration with a 3D fluid one for the first time, enabling precise matching of cortical folds, but allowing large deformations in the enclosed brain volume, which guarantee diffeomorphisms. This greatly improves the matching of anatomy in cortical areas. The cortices are segmented and registered with the software Freesurfer. The deformation field is initially extended to the full 3D brain volume using a 3D harmonic mapping that preserves the matching between cortical surfaces. Finally, these deformation fields are used to initialize a 3D Riemannian fluid registration algorithm, that improves the alignment of subcortical brain regions. We validate this method on an MRI dataset from 92 healthy adult twins. Results are compared to those based on volumetric registration without surface constraints; the resulting mean templates resolve consistent anatomical features both subcortically and at the cortex, suggesting that the approach is well-suited for cross-subject integration of functional and anatomic data.

Semi-automatic delineation of the spino-laminar junction curve on lateral x-ray radiographs of the cervical spine

NASA Astrophysics Data System (ADS)

Narang, Benjamin; Phillips, Michael; Knapp, Karen; Appelboam, Andy; Reuben, Adam; Slabaugh, Greg

2015-03-01

Assessment of the cervical spine using x-ray radiography is an important task when providing emergency room care to trauma patients suspected of a cervical spine injury. In routine clinical practice, a physician will inspect the alignment of the cervical spine vertebrae by mentally tracing three alignment curves along the anterior and posterior sides of the cervical vertebral bodies, as well as one along the spinolaminar junction. In this paper, we propose an algorithm to semi-automatically delineate the spinolaminar junction curve, given a single reference point and the corners of each vertebral body. From the reference point, our method extracts a region of interest, and performs template matching using normalized cross-correlation to find matching regions along the spinolaminar junction. Matching points are then fit to a third order spline, producing an interpolating curve. Experimental results demonstrate promising results, on average producing a modified Hausdorff distance of 1.8 mm, validated on a dataset consisting of 29 patients including those with degenerative change, retrolisthesis, and fracture.

TESS: a geometric hashing algorithm for deriving 3D coordinate templates for searching structural databases. Application to enzyme active sites.

PubMed Central

Wallace, A. C.; Borkakoti, N.; Thornton, J. M.

1997-01-01

It is well established that sequence templates such as those in the PROSITE and PRINTS databases are powerful tools for predicting the biological function and tertiary structure for newly derived protein sequences. The number of X-ray and NMR protein structures is increasing rapidly and it is apparent that a 3D equivalent of the sequence templates is needed. Here, we describe an algorithm called TESS that automatically derives 3D templates from structures deposited in the Brookhaven Protein Data Bank. While a new sequence can be searched for sequence patterns, a new structure can be scanned against these 3D templates to identify functional sites. As examples, 3D templates are derived for enzymes with an O-His-O "catalytic triad" and for the ribonucleases and lysozymes. When these 3D templates are applied to a large data set of nonidentical proteins, several interesting hits are located. This suggests that the development of a 3D template database may help to identify the function of new protein structures, if unknown, as well as to design proteins with specific functions. PMID:9385633

Multimodal biometric approach for cancelable face template generation

NASA Astrophysics Data System (ADS)

Paul, Padma Polash; Gavrilova, Marina

2012-06-01

Due to the rapid growth of biometric technology, template protection becomes crucial to secure integrity of the biometric security system and prevent unauthorized access. Cancelable biometrics is emerging as one of the best solutions to secure the biometric identification and verification system. We present a novel technique for robust cancelable template generation algorithm that takes advantage of the multimodal biometric using feature level fusion. Feature level fusion of different facial features is applied to generate the cancelable template. A proposed algorithm based on the multi-fold random projection and fuzzy communication scheme is used for this purpose. In cancelable template generation, one of the main difficulties is keeping interclass variance of the feature. We have found that interclass variations of the features that are lost during multi fold random projection can be recovered using fusion of different feature subsets and projecting in a new feature domain. Applying the multimodal technique in feature level, we enhance the interclass variability hence improving the performance of the system. We have tested the system for classifier fusion for different feature subset and different cancelable template fusion. Experiments have shown that cancelable template improves the performance of the biometric system compared with the original template.

CAD system for footwear design based on whole real 3D data of last surface

NASA Astrophysics Data System (ADS)

Song, Wanzhong; Su, Xianyu

2000-10-01

Two major parts of application of CAD in footwear design are studied: the development of last surface; computer-aided design of planar shoe-template. A new quasi-experiential development algorithm of last surface based on triangulation approximation is presented. This development algorithm consumes less time and does not need any interactive operation for precisely development compared with other development algorithm of last surface. Based on this algorithm, a software, SHOEMAKERTM, which contains computer aided automatic measurement, automatic development of last surface and computer aide design of shoe-template has been developed.

Prostate contouring in MRI guided biopsy.

PubMed

Vikal, Siddharth; Haker, Steven; Tempany, Clare; Fichtinger, Gabor

2009-03-27

With MRI possibly becoming a modality of choice for detection and staging of prostate cancer, fast and accurate outlining of the prostate is required in the volume of clinical interest. We present a semi-automatic algorithm that uses a priori knowledge of prostate shape to arrive at the final prostate contour. The contour of one slice is then used as initial estimate in the neighboring slices. Thus we propagate the contour in 3D through steps of refinement in each slice. The algorithm makes only minimum assumptions about the prostate shape. A statistical shape model of prostate contour in polar transform space is employed to narrow search space. Further, shape guidance is implicitly imposed by allowing only plausible edge orientations using template matching. The algorithm does not require region-homogeneity, discriminative edge force, or any particular edge profile. Likewise, it makes no assumption on the imaging coils and pulse sequences used and it is robust to the patient's pose (supine, prone, etc.). The contour method was validated using expert segmentation on clinical MRI data. We recorded a mean absolute distance of 2.0 ± 0.6 mm and dice similarity coefficient of 0.93 ± 0.3 in midsection. The algorithm takes about 1 second per slice.

Prostate contouring in MRI guided biopsy

PubMed Central

Vikal, Siddharth; Haker, Steven; Tempany, Clare; Fichtinger, Gabor

2010-01-01

With MRI possibly becoming a modality of choice for detection and staging of prostate cancer, fast and accurate outlining of the prostate is required in the volume of clinical interest. We present a semi-automatic algorithm that uses a priori knowledge of prostate shape to arrive at the final prostate contour. The contour of one slice is then used as initial estimate in the neighboring slices. Thus we propagate the contour in 3D through steps of refinement in each slice. The algorithm makes only minimum assumptions about the prostate shape. A statistical shape model of prostate contour in polar transform space is employed to narrow search space. Further, shape guidance is implicitly imposed by allowing only plausible edge orientations using template matching. The algorithm does not require region-homogeneity, discriminative edge force, or any particular edge profile. Likewise, it makes no assumption on the imaging coils and pulse sequences used and it is robust to the patient's pose (supine, prone, etc.). The contour method was validated using expert segmentation on clinical MRI data. We recorded a mean absolute distance of 2.0 ± 0.6 mm and dice similarity coefficient of 0.93 ± 0.3 in midsection. The algorithm takes about 1 second per slice. PMID:21132083

Real-Time Neural Signals Decoding onto Off-the-Shelf DSP Processors for Neuroprosthetic Applications.

PubMed

Pani, Danilo; Barabino, Gianluca; Citi, Luca; Meloni, Paolo; Raspopovic, Stanisa; Micera, Silvestro; Raffo, Luigi

2016-09-01

The control of upper limb neuroprostheses through the peripheral nervous system (PNS) can allow restoring motor functions in amputees. At present, the important aspect of the real-time implementation of neural decoding algorithms on embedded systems has been often overlooked, notwithstanding the impact that limited hardware resources have on the efficiency/effectiveness of any given algorithm. Present study is addressing the optimization of a template matching based algorithm for PNS signals decoding that is a milestone for its real-time, full implementation onto a floating-point digital signal processor (DSP). The proposed optimized real-time algorithm achieves up to 96% of correct classification on real PNS signals acquired through LIFE electrodes on animals, and can correctly sort spikes of a synthetic cortical dataset with sufficiently uncorrelated spike morphologies (93% average correct classification) comparably to the results obtained with top spike sorter (94% on average on the same dataset). The power consumption enables more than 24 h processing at the maximum load, and latency model has been derived to enable a fair performance assessment. The final embodiment demonstrates the real-time performance onto a low-power off-the-shelf DSP, opening to experiments exploiting the efferent signals to control a motor neuroprosthesis.

Kinect-based sign language recognition of static and dynamic hand movements

NASA Astrophysics Data System (ADS)

Dalawis, Rando C.; Olayao, Kenneth Deniel R.; Ramos, Evan Geoffrey I.; Samonte, Mary Jane C.

2017-02-01

A different approach of sign language recognition of static and dynamic hand movements was developed in this study using normalized correlation algorithm. The goal of this research was to translate fingerspelling sign language into text using MATLAB and Microsoft Kinect. Digital input image captured by Kinect devices are matched from template samples stored in a database. This Human Computer Interaction (HCI) prototype was developed to help people with communication disability to express their thoughts with ease. Frame segmentation and feature extraction was used to give meaning to the captured images. Sequential and random testing was used to test both static and dynamic fingerspelling gestures. The researchers explained some factors they encountered causing some misclassification of signs.

Enhanced ICBM Diffusion Tensor Template of the Human Brain

PubMed Central

Zhang, Shengwei; Peng, Huiling; Dawe, Robert J.; Arfanakis, Konstantinos

2010-01-01

Development of a diffusion tensor (DT) template that is representative of the micro-architecture of the human brain is crucial for comparisons of neuronal structural integrity and brain connectivity across populations, as well as for the generation of a detailed white matter atlas. Furthermore, a DT template in ICBM space may simplify consolidation of information from DT, anatomical and functional MRI studies. The previously developed “IIT DT brain template” was produced in ICBM-152 space, based on a large number of subjects from a limited age-range, using data with minimal image artifacts, and non-linear registration. That template was characterized by higher image sharpness, provided the ability to distinguish smaller white matter fiber structures, and contained fewer image artifacts, than several previously published DT templates. However, low-dimensional registration was used in the development of that template, which led to a mismatch of DT information across subjects, eventually manifested as loss of local diffusion information and errors in the final tensors. Also, low-dimensional registration led to a mismatch of the anatomy in the IIT and ICBM-152 templates. In this work, a significantly improved DT brain template in ICBM-152 space was developed, using high-dimensional non-linear registration and the raw data collected for the purposes of the IIT template. The accuracy of inter-subject DT matching was significantly increased compared to that achieved for the development of the IIT template. Consequently, the new template contained DT information that was more representative of single-subject human brain data, and was characterized by higher image sharpness than the IIT template. Furthermore, a bootstrap approach demonstrated that the variance of tensor characteristics was lower in the new template. Additionally, compared to the IIT template, brain anatomy in the new template more accurately matched ICBM-152 space. Finally, spatial normalization of a number of DT datasets through registration to the new and existing IIT templates was improved when using the new template. PMID:20851772

Lip reading using neural networks

NASA Astrophysics Data System (ADS)

Kalbande, Dhananjay; Mishra, Akassh A.; Patil, Sanjivani; Nirgudkar, Sneha; Patel, Prashant

2011-10-01

Computerized lip reading, or speech reading, is concerned with the difficult task of converting a video signal of a speaking person to written text. It has several applications like teaching deaf and dumb to speak and communicate effectively with the other people, its crime fighting potential and invariance to acoustic environment. We convert the video of the subject speaking vowels into images and then images are further selected manually for processing. However, several factors like fast speech, bad pronunciation, and poor illumination, movement of face, moustaches and beards make lip reading difficult. Contour tracking methods and Template matching are used for the extraction of lips from the face. K Nearest Neighbor algorithm is then used to classify the 'speaking' images and the 'silent' images. The sequence of images is then transformed into segments of utterances. Feature vector is calculated on each frame for all the segments and is stored in the database with properly labeled class. Character recognition is performed using modified KNN algorithm which assigns more weight to nearer neighbors. This paper reports the recognition of vowels using KNN algorithms

A Fast Approach to Automatic Detection of Brain Lesions

PubMed Central

Koley, Subhranil; Chakraborty, Chandan; Mainero, Caterina; Fischl, Bruce; Aganj, Iman

2017-01-01

Template matching is a popular approach to computer-aided detection of brain lesions from magnetic resonance (MR) images. The outcomes are often sufficient for localizing lesions and assisting clinicians in diagnosis. However, processing large MR volumes with three-dimensional (3D) templates is demanding in terms of computational resources, hence the importance of the reduction of computational complexity of template matching, particularly in situations in which time is crucial (e.g. emergent stroke). In view of this, we make use of 3D Gaussian templates with varying radii and propose a new method to compute the normalized cross-correlation coefficient as a similarity metric between the MR volume and the template to detect brain lesions. Contrary to the conventional fast Fourier transform (FFT) based approach, whose runtime grows as O(N logN) with the number of voxels, the proposed method computes the cross-correlation in O(N). We show through our experiments that the proposed method outperforms the FFT approach in terms of computational time, and retains comparable accuracy. PMID:29082383

Nonlinear matching measure for the analysis of on-off type DNA microarray images

NASA Astrophysics Data System (ADS)

Kim, Jong D.; Park, Misun; Kim, Jongwon

2003-07-01

In this paper, we propose a new nonlinear matching measure for automatic analysis of the on-off type DNA microarray images in which the hybridized spots are detected by the template matching method. The targeting spots of HPV DNA chips are designed for genotyping the human papilloma virus(HPV). The proposed measure is obtained by binarythresholding over the whole template region and taking the number of white pixels inside the spotted area. This measure is evaluated in terms of the accuracy of the estimated marker location to show better performance than the normalized covariance.

Reconstruction of ECG signals in presence of corruption.

PubMed

Ganeshapillai, Gartheeban; Liu, Jessica F; Guttag, John

2011-01-01

We present an approach to identifying and reconstructing corrupted regions in a multi-parameter physiological signal. The method, which uses information in correlated signals, is specifically designed to preserve clinically significant aspects of the signals. We use template matching to jointly segment the multi-parameter signal, morphological dissimilarity to estimate the quality of the signal segment, similarity search using features on a database of templates to find the closest match, and time-warping to reconstruct the corrupted segment with the matching template. In experiments carried out on the MIT-BIH Arrhythmia Database, a two-parameter database with many clinically significant arrhythmias, our method improved the classification accuracy of the beat type by more than 7 times on a signal corrupted with white Gaussian noise, and increased the similarity to the original signal, as measured by the normalized residual distance, by more than 2.5 times.

Monocular correspondence detection for symmetrical objects by template matching

NASA Astrophysics Data System (ADS)

Vilmar, G.; Besslich, Philipp W., Jr.

1990-09-01

We describe a possibility to reconstruct 3-D information from a single view of an 3-D bilateral symmetric object. The symmetry assumption allows us to obtain a " second view" from a different viewpoint by a simple reflection of the monocular image. Therefore we have to solve the correspondence problem in a special case where known feature-based or area-based binocular approaches fail. In principle our approach is based on a frequency domain template matching of the features on the epipolar lines. During a training period our system " learns" the assignment of correspondence models to image features. The object shape is interpolated when no template matches to the image features. This fact is an important advantage of this methodology because no " real world" image holds the symmetry assumption perfectly. To simplify the training process we used single views on human faces (e. g. passport photos) but our system is trainable on any other kind of objects.

Supervised learning of tools for content-based search of image databases

NASA Astrophysics Data System (ADS)

Delanoy, Richard L.

1996-03-01

A computer environment, called the Toolkit for Image Mining (TIM), is being developed with the goal of enabling users with diverse interests and varied computer skills to create search tools for content-based image retrieval and other pattern matching tasks. Search tools are generated using a simple paradigm of supervised learning that is based on the user pointing at mistakes of classification made by the current search tool. As mistakes are identified, a learning algorithm uses the identified mistakes to build up a model of the user's intentions, construct a new search tool, apply the search tool to a test image, display the match results as feedback to the user, and accept new inputs from the user. Search tools are constructed in the form of functional templates, which are generalized matched filters capable of knowledge- based image processing. The ability of this system to learn the user's intentions from experience contrasts with other existing approaches to content-based image retrieval that base searches on the characteristics of a single input example or on a predefined and semantically- constrained textual query. Currently, TIM is capable of learning spectral and textural patterns, but should be adaptable to the learning of shapes, as well. Possible applications of TIM include not only content-based image retrieval, but also quantitative image analysis, the generation of metadata for annotating images, data prioritization or data reduction in bandwidth-limited situations, and the construction of components for larger, more complex computer vision algorithms.

A Hybrid Approach to Protect Palmprint Templates

PubMed Central

Sun, Dongmei; Xiong, Ke; Qiu, Zhengding

2014-01-01

Biometric template protection is indispensable to protect personal privacy in large-scale deployment of biometric systems. Accuracy, changeability, and security are three critical requirements for template protection algorithms. However, existing template protection algorithms cannot satisfy all these requirements well. In this paper, we propose a hybrid approach that combines random projection and fuzzy vault to improve the performances at these three points. Heterogeneous space is designed for combining random projection and fuzzy vault properly in the hybrid scheme. New chaff point generation method is also proposed to enhance the security of the heterogeneous vault. Theoretical analyses of proposed hybrid approach in terms of accuracy, changeability, and security are given in this paper. Palmprint database based experimental results well support the theoretical analyses and demonstrate the effectiveness of proposed hybrid approach. PMID:24982977

A hybrid approach to protect palmprint templates.

PubMed

Liu, Hailun; Sun, Dongmei; Xiong, Ke; Qiu, Zhengding

2014-01-01

Biometric template protection is indispensable to protect personal privacy in large-scale deployment of biometric systems. Accuracy, changeability, and security are three critical requirements for template protection algorithms. However, existing template protection algorithms cannot satisfy all these requirements well. In this paper, we propose a hybrid approach that combines random projection and fuzzy vault to improve the performances at these three points. Heterogeneous space is designed for combining random projection and fuzzy vault properly in the hybrid scheme. New chaff point generation method is also proposed to enhance the security of the heterogeneous vault. Theoretical analyses of proposed hybrid approach in terms of accuracy, changeability, and security are given in this paper. Palmprint database based experimental results well support the theoretical analyses and demonstrate the effectiveness of proposed hybrid approach.

Alignment and bit extraction for secure fingerprint biometrics

NASA Astrophysics Data System (ADS)

Nagar, A.; Rane, S.; Vetro, A.

2010-01-01

Security of biometric templates stored in a system is important because a stolen template can compromise system security as well as user privacy. Therefore, a number of secure biometrics schemes have been proposed that facilitate matching of feature templates without the need for a stored biometric sample. However, most of these schemes suffer from poor matching performance owing to the difficulty of designing biometric features that remain robust over repeated biometric measurements. This paper describes a scheme to extract binary features from fingerprints using minutia points and fingerprint ridges. The features are amenable to direct matching based on binary Hamming distance, but are especially suitable for use in secure biometric cryptosystems that use standard error correcting codes. Given all binary features, a method for retaining only the most discriminable features is presented which improves the Genuine Accept Rate (GAR) from 82% to 90% at a False Accept Rate (FAR) of 0.1% on a well-known public database. Additionally, incorporating singular points such as a core or delta feature is shown to improve the matching tradeoff.

Computerized detection of breast lesions in multi-centre and multi-instrument DCE-MR data using 3D principal component maps and template matching

NASA Astrophysics Data System (ADS)

Ertas, Gokhan; Doran, Simon; Leach, Martin O.

2011-12-01

In this study, we introduce a novel, robust and accurate computerized algorithm based on volumetric principal component maps and template matching that facilitates lesion detection on dynamic contrast-enhanced MR. The study dataset comprises 24 204 contrast-enhanced breast MR images corresponding to 4034 axial slices from 47 women in the UK multi-centre study of MRI screening for breast cancer and categorized as high risk. The scans analysed here were performed on six different models of scanner from three commercial vendors, sited in 13 clinics around the UK. 1952 slices from this dataset, containing 15 benign and 13 malignant lesions, were used for training. The remaining 2082 slices, with 14 benign and 12 malignant lesions, were used for test purposes. To prevent false positives being detected from other tissues and regions of the body, breast volumes are segmented from pre-contrast images using a fast semi-automated algorithm. Principal component analysis is applied to the centred intensity vectors formed from the dynamic contrast-enhanced T1-weighted images of the segmented breasts, followed by automatic thresholding to eliminate fatty tissues and slowly enhancing normal parenchyma and a convolution and filtering process to minimize artefacts from moderately enhanced normal parenchyma and blood vessels. Finally, suspicious lesions are identified through a volumetric sixfold neighbourhood connectivity search and calculation of two morphological features: volume and volumetric eccentricity, to exclude highly enhanced blood vessels, nipples and normal parenchyma and to localize lesions. This provides satisfactory lesion localization. For a detection sensitivity of 100%, the overall false-positive detection rate of the system is 1.02/lesion, 1.17/case and 0.08/slice, comparing favourably with previous studies. This approach may facilitate detection of lesions in multi-centre and multi-instrument dynamic contrast-enhanced breast MR data.

Temporal regularization of ultrasound-based liver motion estimation for image-guided radiation therapy

DOE Office of Scientific and Technical Information (OSTI.GOV)

O’Shea, Tuathan P., E-mail: tuathan.oshea@icr.ac.uk; Bamber, Jeffrey C.; Harris, Emma J.

Purpose: Ultrasound-based motion estimation is an expanding subfield of image-guided radiation therapy. Although ultrasound can detect tissue motion that is a fraction of a millimeter, its accuracy is variable. For controlling linear accelerator tracking and gating, ultrasound motion estimates must remain highly accurate throughout the imaging sequence. This study presents a temporal regularization method for correlation-based template matching which aims to improve the accuracy of motion estimates. Methods: Liver ultrasound sequences (15–23 Hz imaging rate, 2.5–5.5 min length) from ten healthy volunteers under free breathing were used. Anatomical features (blood vessels) in each sequence were manually annotated for comparison withmore » normalized cross-correlation based template matching. Five sequences from a Siemens Acuson™ scanner were used for algorithm development (training set). Results from incremental tracking (IT) were compared with a temporal regularization method, which included a highly specific similarity metric and state observer, known as the α–β filter/similarity threshold (ABST). A further five sequences from an Elekta Clarity™ system were used for validation, without alteration of the tracking algorithm (validation set). Results: Overall, the ABST method produced marked improvements in vessel tracking accuracy. For the training set, the mean and 95th percentile (95%) errors (defined as the difference from manual annotations) were 1.6 and 1.4 mm, respectively (compared to 6.2 and 9.1 mm, respectively, for IT). For each sequence, the use of the state observer leads to improvement in the 95% error. For the validation set, the mean and 95% errors for the ABST method were 0.8 and 1.5 mm, respectively. Conclusions: Ultrasound-based motion estimation has potential to monitor liver translation over long time periods with high accuracy. Nonrigid motion (strain) and the quality of the ultrasound data are likely to have an impact on tracking performance. A future study will investigate spatial uniformity of motion and its effect on the motion estimation errors.« less

Waveform Similarity Analysis: A Simple Template Comparing Approach for Detecting and Quantifying Noisy Evoked Compound Action Potentials.

PubMed

Potas, Jason Robert; de Castro, Newton Gonçalves; Maddess, Ted; de Souza, Marcio Nogueira

2015-01-01

Experimental electrophysiological assessment of evoked responses from regenerating nerves is challenging due to the typical complex response of events dispersed over various latencies and poor signal-to-noise ratio. Our objective was to automate the detection of compound action potential events and derive their latencies and magnitudes using a simple cross-correlation template comparison approach. For this, we developed an algorithm called Waveform Similarity Analysis. To test the algorithm, challenging signals were generated in vivo by stimulating sural and sciatic nerves, whilst recording evoked potentials at the sciatic nerve and tibialis anterior muscle, respectively, in animals recovering from sciatic nerve transection. Our template for the algorithm was generated based on responses evoked from the intact side. We also simulated noisy signals and examined the output of the Waveform Similarity Analysis algorithm with imperfect templates. Signals were detected and quantified using Waveform Similarity Analysis, which was compared to event detection, latency and magnitude measurements of the same signals performed by a trained observer, a process we called Trained Eye Analysis. The Waveform Similarity Analysis algorithm could successfully detect and quantify simple or complex responses from nerve and muscle compound action potentials of intact or regenerated nerves. Incorrectly specifying the template outperformed Trained Eye Analysis for predicting signal amplitude, but produced consistent latency errors for the simulated signals examined. Compared to the trained eye, Waveform Similarity Analysis is automatic, objective, does not rely on the observer to identify and/or measure peaks, and can detect small clustered events even when signal-to-noise ratio is poor. Waveform Similarity Analysis provides a simple, reliable and convenient approach to quantify latencies and magnitudes of complex waveforms and therefore serves as a useful tool for studying evoked compound action potentials in neural regeneration studies.

Waveform Similarity Analysis: A Simple Template Comparing Approach for Detecting and Quantifying Noisy Evoked Compound Action Potentials

PubMed Central

Potas, Jason Robert; de Castro, Newton Gonçalves; Maddess, Ted; de Souza, Marcio Nogueira

2015-01-01

Experimental electrophysiological assessment of evoked responses from regenerating nerves is challenging due to the typical complex response of events dispersed over various latencies and poor signal-to-noise ratio. Our objective was to automate the detection of compound action potential events and derive their latencies and magnitudes using a simple cross-correlation template comparison approach. For this, we developed an algorithm called Waveform Similarity Analysis. To test the algorithm, challenging signals were generated in vivo by stimulating sural and sciatic nerves, whilst recording evoked potentials at the sciatic nerve and tibialis anterior muscle, respectively, in animals recovering from sciatic nerve transection. Our template for the algorithm was generated based on responses evoked from the intact side. We also simulated noisy signals and examined the output of the Waveform Similarity Analysis algorithm with imperfect templates. Signals were detected and quantified using Waveform Similarity Analysis, which was compared to event detection, latency and magnitude measurements of the same signals performed by a trained observer, a process we called Trained Eye Analysis. The Waveform Similarity Analysis algorithm could successfully detect and quantify simple or complex responses from nerve and muscle compound action potentials of intact or regenerated nerves. Incorrectly specifying the template outperformed Trained Eye Analysis for predicting signal amplitude, but produced consistent latency errors for the simulated signals examined. Compared to the trained eye, Waveform Similarity Analysis is automatic, objective, does not rely on the observer to identify and/or measure peaks, and can detect small clustered events even when signal-to-noise ratio is poor. Waveform Similarity Analysis provides a simple, reliable and convenient approach to quantify latencies and magnitudes of complex waveforms and therefore serves as a useful tool for studying evoked compound action potentials in neural regeneration studies. PMID:26325291

Performance Evaluation of Fusing Protected Fingerprint Minutiae Templates on the Decision Level

PubMed Central

Yang, Bian; Busch, Christoph; de Groot, Koen; Xu, Haiyun; Veldhuis, Raymond N. J.

2012-01-01

In a biometric authentication system using protected templates, a pseudonymous identifier is the part of a protected template that can be directly compared. Each compared pair of pseudonymous identifiers results in a decision testing whether both identifiers are derived from the same biometric characteristic. Compared to an unprotected system, most existing biometric template protection methods cause to a certain extent degradation in biometric performance. Fusion is therefore a promising way to enhance the biometric performance in template-protected biometric systems. Compared to feature level fusion and score level fusion, decision level fusion has not only the least fusion complexity, but also the maximum interoperability across different biometric features, template protection and recognition algorithms, templates formats, and comparison score rules. However, performance improvement via decision level fusion is not obvious. It is influenced by both the dependency and the performance gap among the conducted tests for fusion. We investigate in this paper several fusion scenarios (multi-sample, multi-instance, multi-sensor, multi-algorithm, and their combinations) on the binary decision level, and evaluate their biometric performance and fusion efficiency on a multi-sensor fingerprint database with 71,994 samples. PMID:22778583

Tumour auto-contouring on 2d cine MRI for locally advanced lung cancer: A comparative study.

PubMed

Fast, Martin F; Eiben, Björn; Menten, Martin J; Wetscherek, Andreas; Hawkes, David J; McClelland, Jamie R; Oelfke, Uwe

2017-12-01

Radiotherapy guidance based on magnetic resonance imaging (MRI) is currently becoming a clinical reality. Fast 2d cine MRI sequences are expected to increase the precision of radiation delivery by facilitating tumour delineation during treatment. This study compares four auto-contouring algorithms for the task of delineating the primary tumour in six locally advanced (LA) lung cancer patients. Twenty-two cine MRI sequences were acquired using either a balanced steady-state free precession or a spoiled gradient echo imaging technique. Contours derived by the auto-contouring algorithms were compared against manual reference contours. A selection of eight image data sets was also used to assess the inter-observer delineation uncertainty. Algorithmically derived contours agreed well with the manual reference contours (median Dice similarity index: ⩾0.91). Multi-template matching and deformable image registration performed significantly better than feature-driven registration and the pulse-coupled neural network (PCNN). Neither MRI sequence nor image orientation was a conclusive predictor for algorithmic performance. Motion significantly degraded the performance of the PCNN. The inter-observer variability was of the same order of magnitude as the algorithmic performance. Auto-contouring of tumours on cine MRI is feasible in LA lung cancer patients. Despite large variations in implementation complexity, the different algorithms all have relatively similar performance. Copyright © 2017 The Author(s). Published by Elsevier B.V. All rights reserved.

A Framework for the Comparative Assessment of Neuronal Spike Sorting Algorithms towards More Accurate Off-Line and On-Line Microelectrode Arrays Data Analysis.

PubMed

Regalia, Giulia; Coelli, Stefania; Biffi, Emilia; Ferrigno, Giancarlo; Pedrocchi, Alessandra

2016-01-01

Neuronal spike sorting algorithms are designed to retrieve neuronal network activity on a single-cell level from extracellular multiunit recordings with Microelectrode Arrays (MEAs). In typical analysis of MEA data, one spike sorting algorithm is applied indiscriminately to all electrode signals. However, this approach neglects the dependency of algorithms' performances on the neuronal signals properties at each channel, which require data-centric methods. Moreover, sorting is commonly performed off-line, which is time and memory consuming and prevents researchers from having an immediate glance at ongoing experiments. The aim of this work is to provide a versatile framework to support the evaluation and comparison of different spike classification algorithms suitable for both off-line and on-line analysis. We incorporated different spike sorting "building blocks" into a Matlab-based software, including 4 feature extraction methods, 3 feature clustering methods, and 1 template matching classifier. The framework was validated by applying different algorithms on simulated and real signals from neuronal cultures coupled to MEAs. Moreover, the system has been proven effective in running on-line analysis on a standard desktop computer, after the selection of the most suitable sorting methods. This work provides a useful and versatile instrument for a supported comparison of different options for spike sorting towards more accurate off-line and on-line MEA data analysis.

A Framework for the Comparative Assessment of Neuronal Spike Sorting Algorithms towards More Accurate Off-Line and On-Line Microelectrode Arrays Data Analysis

PubMed Central

Pedrocchi, Alessandra

2016-01-01

Neuronal spike sorting algorithms are designed to retrieve neuronal network activity on a single-cell level from extracellular multiunit recordings with Microelectrode Arrays (MEAs). In typical analysis of MEA data, one spike sorting algorithm is applied indiscriminately to all electrode signals. However, this approach neglects the dependency of algorithms' performances on the neuronal signals properties at each channel, which require data-centric methods. Moreover, sorting is commonly performed off-line, which is time and memory consuming and prevents researchers from having an immediate glance at ongoing experiments. The aim of this work is to provide a versatile framework to support the evaluation and comparison of different spike classification algorithms suitable for both off-line and on-line analysis. We incorporated different spike sorting “building blocks” into a Matlab-based software, including 4 feature extraction methods, 3 feature clustering methods, and 1 template matching classifier. The framework was validated by applying different algorithms on simulated and real signals from neuronal cultures coupled to MEAs. Moreover, the system has been proven effective in running on-line analysis on a standard desktop computer, after the selection of the most suitable sorting methods. This work provides a useful and versatile instrument for a supported comparison of different options for spike sorting towards more accurate off-line and on-line MEA data analysis. PMID:27239191

DOE Office of Scientific and Technical Information (OSTI.GOV)

Scibelli, Samantha; Newberg, Heidi Jo; Carlin, Jeffrey L.

We present a census of the 12,060 spectra of blue objects ((g – r){sub 0} < –0.25) in the Sloan Digital Sky Survey (SDSS) Data Release 8 (DR8). As part of the data release, all of the spectra were cross-correlated with 48 template spectra of stars, galaxies, and QSOs to determine the best match. We compared the blue spectra by eye to the templates assigned in SDSS DR8. 10,856 of the objects matched their assigned template, 170 could not be classified due to low signal-to-noise ratio, and 1034 were given new classifications. We identify 7458 DA white dwarfs, 1145 DBmore » white dwarfs, 273 rarer white dwarfs (including carbon, DZ, DQ, and magnetic), 294 subdwarf O stars, 648 subdwarf B stars, 679 blue horizontal branch stars, 1026 blue stragglers, 13 cataclysmic variables, 129 white dwarf-M dwarf binaries, 36 objects with spectra similar to DO white dwarfs, 179, quasi-stellar objects (QSOs), and 10 galaxies. We provide two tables of these objects, sample spectra that match the templates, figures showing all of the spectra that were grouped by eye, and diagnostic plots that show the positions, colors, apparent magnitudes, proper motions, etc., for each classification. Future surveys will be able to use templates similar to stars in each of the classes we identify to automatically classify blue stars, including rare types.« less

DOE Office of Scientific and Technical Information (OSTI.GOV)

Scibelli, Samantha; Newberg, Heidi Jo; Carlin, Jeffrey L.

In this work, we present a census of the 12,060 spectra of blue objects (more » $$(g-r)_0<-0.25$$) in the Sloan Digital Sky Survey (SDSS) Data Release 8 (DR8). As part of the data release, all of the spectra were cross-correlated with 48 template spectra of stars, galaxies and QSOs to determine the best match. We compared the blue spectra by eye to the templates assigned in SDSS DR8. 10,856 of the objects matched their assigned template, 170 could not be classified due to low signal-to-noise (S/N), and 1034 were given new classifications. We identify 7458 DA white dwarfs, 1145 DB white dwarfs, 273 rarer white dwarfs (including carbon, DZ, DQ, and magnetic), 294 subdwarf O stars, 648 subdwarf B stars, 679 blue horizontal branch stars, 1026 blue stragglers, 13 cataclysmic variables, 129 white dwarf - M dwarf binaries, 36 objects with spectra similar to DO white dwarfs, 179 QSOs, and 10 galaxies. We provide two tables of these objects, sample spectra that match the templates, figures showing all of the spectra that were grouped by eye, and diagnostic plots that show the positions, colors, apparent magnitudes, proper motions, etc. for each classification. In conclusion, future surveys will be able to use templates similar to stars in each of the classes we identify to classify blue stars, including rare types, automatically.« less

CENSUS OF BLUE STARS IN SDSS DR8

DOE PAGES

Scibelli, Samantha; Newberg, Heidi Jo; Carlin, Jeffrey L.; ...

2014-12-02

In this work, we present a census of the 12,060 spectra of blue objects (more » $$(g-r)_0<-0.25$$) in the Sloan Digital Sky Survey (SDSS) Data Release 8 (DR8). As part of the data release, all of the spectra were cross-correlated with 48 template spectra of stars, galaxies and QSOs to determine the best match. We compared the blue spectra by eye to the templates assigned in SDSS DR8. 10,856 of the objects matched their assigned template, 170 could not be classified due to low signal-to-noise (S/N), and 1034 were given new classifications. We identify 7458 DA white dwarfs, 1145 DB white dwarfs, 273 rarer white dwarfs (including carbon, DZ, DQ, and magnetic), 294 subdwarf O stars, 648 subdwarf B stars, 679 blue horizontal branch stars, 1026 blue stragglers, 13 cataclysmic variables, 129 white dwarf - M dwarf binaries, 36 objects with spectra similar to DO white dwarfs, 179 QSOs, and 10 galaxies. We provide two tables of these objects, sample spectra that match the templates, figures showing all of the spectra that were grouped by eye, and diagnostic plots that show the positions, colors, apparent magnitudes, proper motions, etc. for each classification. In conclusion, future surveys will be able to use templates similar to stars in each of the classes we identify to classify blue stars, including rare types, automatically.« less

Smartphone-Based Real-time Assessment of Swallowing Ability From the Swallowing Sound.

PubMed

Jayatilake, Dushyantha; Ueno, Tomoyuki; Teramoto, Yohei; Nakai, Kei; Hidaka, Kikue; Ayuzawa, Satoshi; Eguchi, Kiyoshi; Matsumura, Akira; Suzuki, Kenji

2015-01-01

Dysphagia can cause serious challenges to both physical and mental health. Aspiration due to dysphagia is a major health risk that could cause pneumonia and even death. The videofluoroscopic swallow study (VFSS), which is considered the gold standard for the diagnosis of dysphagia, is not widely available, expensive and causes exposure to radiation. The screening tests used for dysphagia need to be carried out by trained staff, and the evaluations are usually non-quantifiable. This paper investigates the development of the Swallowscope, a smartphone-based device and a feasible real-time swallowing sound-processing algorithm for the automatic screening, quantitative evaluation, and the visualisation of swallowing ability. The device can be used during activities of daily life with minimal intervention, making it potentially more capable of capturing aspirations and risky swallow patterns through the continuous monitoring. It also consists of a cloud-based system for the server-side analyzing and automatic sharing of the swallowing sound. The real-time algorithm we developed for the detection of dry and water swallows is based on a template matching approach. We analyzed the wavelet transformation-based spectral characteristics and the temporal characteristics of simultaneous synchronised VFSS and swallowing sound recordings of 25% barium mixed 3-ml water swallows of 70 subjects and the dry or saliva swallowing sound of 15 healthy subjects to establish the parameters of the template. With this algorithm, we achieved an overall detection accuracy of 79.3% (standard error: 4.2%) for the 92 water swallows; and a precision of 83.7% (range: 66.6%-100%) and a recall of 93.9% (range: 72.7%-100%) for the 71 episodes of dry swallows.

Smartphone-Based Real-time Assessment of Swallowing Ability From the Swallowing Sound

PubMed Central

Ueno, Tomoyuki; Teramoto, Yohei; Nakai, Kei; Hidaka, Kikue; Ayuzawa, Satoshi; Eguchi, Kiyoshi; Matsumura, Akira; Suzuki, Kenji

2015-01-01

Dysphagia can cause serious challenges to both physical and mental health. Aspiration due to dysphagia is a major health risk that could cause pneumonia and even death. The videofluoroscopic swallow study (VFSS), which is considered the gold standard for the diagnosis of dysphagia, is not widely available, expensive and causes exposure to radiation. The screening tests used for dysphagia need to be carried out by trained staff, and the evaluations are usually non-quantifiable. This paper investigates the development of the Swallowscope, a smartphone-based device and a feasible real-time swallowing sound-processing algorithm for the automatic screening, quantitative evaluation, and the visualisation of swallowing ability. The device can be used during activities of daily life with minimal intervention, making it potentially more capable of capturing aspirations and risky swallow patterns through the continuous monitoring. It also consists of a cloud-based system for the server-side analyzing and automatic sharing of the swallowing sound. The real-time algorithm we developed for the detection of dry and water swallows is based on a template matching approach. We analyzed the wavelet transformation-based spectral characteristics and the temporal characteristics of simultaneous synchronised VFSS and swallowing sound recordings of 25% barium mixed 3-ml water swallows of 70 subjects and the dry or saliva swallowing sound of 15 healthy subjects to establish the parameters of the template. With this algorithm, we achieved an overall detection accuracy of 79.3% (standard error: 4.2%) for the 92 water swallows; and a precision of 83.7% (range: 66.6%–100%) and a recall of 93.9% (range: 72.7%–100%) for the 71 episodes of dry swallows. PMID:27170905

MRI-guided tumor tracking in lung cancer radiotherapy

NASA Astrophysics Data System (ADS)

Cerviño, Laura I.; Du, Jiang; Jiang, Steve B.

2011-07-01

Precise tracking of lung tumor motion during treatment delivery still represents a challenge in radiation therapy. Prototypes of MRI-linac hybrid systems are being created which have the potential of ionization-free real-time imaging of the tumor. This study evaluates the performance of lung tumor tracking algorithms in cine-MRI sagittal images from five healthy volunteers. Visible vascular structures were used as targets. Volunteers performed several series of regular and irregular breathing. Two tracking algorithms were implemented and evaluated: a template matching (TM) algorithm in combination with surrogate tracking using the diaphragm (surrogate was used when the maximum correlation between the template and the image in the search window was less than specified), and an artificial neural network (ANN) model based on the principal components of a region of interest that encompasses the target motion. The mean tracking error ē and the error at 95% confidence level e95 were evaluated for each model. The ANN model led to ē = 1.5 mm and e95 = 4.2 mm, while TM led to ē = 0.6 mm and e95 = 1.0 mm. An extra series was considered separately to evaluate the benefit of using surrogate tracking in combination with TM when target out-of-plane motion occurs. For this series, the mean error was 7.2 mm using only TM and 1.7 mm when the surrogate was used in combination with TM. Results show that, as opposed to tracking with other imaging modalities, ANN does not perform well in MR-guided tracking. TM, however, leads to highly accurate tracking. Out-of-plane motion could be addressed by surrogate tracking using the diaphragm, which can be easily identified in the images.

[Using neural networks based template matching method to obtain redshifts of normal galaxies].

PubMed

Xu, Xin; Luo, A-li; Wu, Fu-chao; Zhao, Yong-heng

2005-06-01

Galaxies can be divided into two classes: normal galaxy (NG) and active galaxy (AG). In order to determine NG redshifts, an automatic effective method is proposed in this paper, which consists of the following three main steps: (1) From the template of normal galaxy, the two sets of samples are simulated, one with the redshift of 0.0-0.3, the other of 0.3-0.5, then the PCA is used to extract the main components, and train samples are projected to the main component subspace to obtain characteristic spectra. (2) The characteristic spectra are used to train a Probabilistic Neural Network to obtain a Bayes classifier. (3) An unknown real NG spectrum is first inputted to this Bayes classifier to determine the possible range of redshift, then the template matching is invoked to locate the redshift value within the estimated range. Compared with the traditional template matching technique with an unconstrained range, our proposed method not only halves the computational load, but also increases the estimation accuracy. As a result, the proposed method is particularly useful for automatic spectrum processing produced from a large-scale sky survey project.

Guided filter and convolutional network based tracking for infrared dim moving target

NASA Astrophysics Data System (ADS)

Qian, Kun; Zhou, Huixin; Qin, Hanlin; Rong, Shenghui; Zhao, Dong; Du, Juan

2017-09-01

The dim moving target usually submerges in strong noise, and its motion observability is debased by numerous false alarms for low signal-to-noise ratio. A tracking algorithm that integrates the Guided Image Filter (GIF) and the Convolutional neural network (CNN) into the particle filter framework is presented to cope with the uncertainty of dim targets. First, the initial target template is treated as a guidance to filter incoming templates depending on similarities between the guidance and candidate templates. The GIF algorithm utilizes the structure in the guidance and performs as an edge-preserving smoothing operator. Therefore, the guidance helps to preserve the detail of valuable templates and makes inaccurate ones blurry, alleviating the tracking deviation effectively. Besides, the two-layer CNN method is adopted to obtain a powerful appearance representation. Subsequently, a Bayesian classifier is trained with these discriminative yet strong features. Moreover, an adaptive learning factor is introduced to prevent the update of classifier's parameters when a target undergoes sever background. At last, classifier responses of particles are utilized to generate particle importance weights and a re-sample procedure preserves samples according to the weight. In the predication stage, a 2-order transition model considers the target velocity to estimate current position. Experimental results demonstrate that the presented algorithm outperforms several relative algorithms in the accuracy.

Rotation invariants of vector fields from orthogonal moments

DOE Office of Scientific and Technical Information (OSTI.GOV)

Yang, Bo; Kostková, Jitka; Flusser, Jan

Vector field images are a type of new multidimensional data that appear in many engineering areas. Although the vector fields can be visualized as images, they differ from graylevel and color images in several aspects. In order to analyze them, special methods and algorithms must be originally developed or substantially adapted from the traditional image processing area. Here, we propose a method for the description and matching of vector field patterns under an unknown rotation of the field. Rotation of a vector field is so-called total rotation, where the action is applied not only on the spatial coordinates but alsomore » on the field values. Invariants of vector fields with respect to total rotation constructed from orthogonal Gaussian–Hermite moments and Zernike moments are introduced. Their numerical stability is shown to be better than that of the invariants published so far. We demonstrate their usefulness in a real world template matching application of rotated vector fields.« less

Rotation invariants of vector fields from orthogonal moments

DOE PAGES

Yang, Bo; Kostková, Jitka; Flusser, Jan; ...

2017-09-11

Vector field images are a type of new multidimensional data that appear in many engineering areas. Although the vector fields can be visualized as images, they differ from graylevel and color images in several aspects. In order to analyze them, special methods and algorithms must be originally developed or substantially adapted from the traditional image processing area. Here, we propose a method for the description and matching of vector field patterns under an unknown rotation of the field. Rotation of a vector field is so-called total rotation, where the action is applied not only on the spatial coordinates but alsomore » on the field values. Invariants of vector fields with respect to total rotation constructed from orthogonal Gaussian–Hermite moments and Zernike moments are introduced. Their numerical stability is shown to be better than that of the invariants published so far. We demonstrate their usefulness in a real world template matching application of rotated vector fields.« less

Real-time automatic fiducial marker tracking in low contrast cine-MV images

DOE Office of Scientific and Technical Information (OSTI.GOV)

Lin, Wei-Yang; Lin, Shu-Fang; Yang, Sheng-Chang

2013-01-15

Purpose: To develop a real-time automatic method for tracking implanted radiographic markers in low-contrast cine-MV patient images used in image-guided radiation therapy (IGRT). Methods: Intrafraction motion tracking using radiotherapy beam-line MV images have gained some attention recently in IGRT because no additional imaging dose is introduced. However, MV images have much lower contrast than kV images, therefore a robust and automatic algorithm for marker detection in MV images is a prerequisite. Previous marker detection methods are all based on template matching or its derivatives. Template matching needs to match object shape that changes significantly for different implantation and projection angle.more » While these methods require a large number of templates to cover various situations, they are often forced to use a smaller number of templates to reduce the computation load because their methods all require exhaustive search in the region of interest. The authors solve this problem by synergetic use of modern but well-tested computer vision and artificial intelligence techniques; specifically the authors detect implanted markers utilizing discriminant analysis for initialization and use mean-shift feature space analysis for sequential tracking. This novel approach avoids exhaustive search by exploiting the temporal correlation between consecutive frames and makes it possible to perform more sophisticated detection at the beginning to improve the accuracy, followed by ultrafast sequential tracking after the initialization. The method was evaluated and validated using 1149 cine-MV images from two prostate IGRT patients and compared with manual marker detection results from six researchers. The average of the manual detection results is considered as the ground truth for comparisons. Results: The average root-mean-square errors of our real-time automatic tracking method from the ground truth are 1.9 and 2.1 pixels for the two patients (0.26 mm/pixel). The standard deviations of the results from the 6 researchers are 2.3 and 2.6 pixels. The proposed framework takes about 128 ms to detect four markers in the first MV images and about 23 ms to track these markers in each of the subsequent images. Conclusions: The unified framework for tracking of multiple markers presented here can achieve marker detection accuracy similar to manual detection even in low-contrast cine-MV images. It can cope with shape deformations of fiducial markers at different gantry angles. The fast processing speed reduces the image processing portion of the system latency, therefore can improve the performance of real-time motion compensation.« less

A novel cloning template designing method by using an artificial bee colony algorithm for edge detection of CNN based imaging sensors.

PubMed

Parmaksızoğlu, Selami; Alçı, Mustafa

2011-01-01

Cellular Neural Networks (CNNs) have been widely used recently in applications such as edge detection, noise reduction and object detection, which are among the main computer imaging processes. They can also be realized as hardware based imaging sensors. The fact that hardware CNN models produce robust and effective results has attracted the attention of researchers using these structures within image sensors. Realization of desired CNN behavior such as edge detection can be achieved by correctly setting a cloning template without changing the structure of the CNN. To achieve different behaviors effectively, designing a cloning template is one of the most important research topics in this field. In this study, the edge detecting process that is used as a preliminary process for segmentation, identification and coding applications is conducted by using CNN structures. In order to design the cloning template of goal-oriented CNN architecture, an Artificial Bee Colony (ABC) algorithm which is inspired from the foraging behavior of honeybees is used and the performance analysis of ABC for this application is examined with multiple runs. The CNN template generated by the ABC algorithm is tested by using artificial and real test images. The results are subjectively and quantitatively compared with well-known classical edge detection methods, and other CNN based edge detector cloning templates available in the imaging literature. The results show that the proposed method is more successful than other methods.

A Novel Cloning Template Designing Method by Using an Artificial Bee Colony Algorithm for Edge Detection of CNN Based Imaging Sensors

PubMed Central

Parmaksızoğlu, Selami; Alçı, Mustafa

2011-01-01

Cellular Neural Networks (CNNs) have been widely used recently in applications such as edge detection, noise reduction and object detection, which are among the main computer imaging processes. They can also be realized as hardware based imaging sensors. The fact that hardware CNN models produce robust and effective results has attracted the attention of researchers using these structures within image sensors. Realization of desired CNN behavior such as edge detection can be achieved by correctly setting a cloning template without changing the structure of the CNN. To achieve different behaviors effectively, designing a cloning template is one of the most important research topics in this field. In this study, the edge detecting process that is used as a preliminary process for segmentation, identification and coding applications is conducted by using CNN structures. In order to design the cloning template of goal-oriented CNN architecture, an Artificial Bee Colony (ABC) algorithm which is inspired from the foraging behavior of honeybees is used and the performance analysis of ABC for this application is examined with multiple runs. The CNN template generated by the ABC algorithm is tested by using artificial and real test images. The results are subjectively and quantitatively compared with well-known classical edge detection methods, and other CNN based edge detector cloning templates available in the imaging literature. The results show that the proposed method is more successful than other methods. PMID:22163903

Consensus-Based Sorting of Neuronal Spike Waveforms

PubMed Central

Fournier, Julien; Mueller, Christian M.; Shein-Idelson, Mark; Hemberger, Mike

2016-01-01

Optimizing spike-sorting algorithms is difficult because sorted clusters can rarely be checked against independently obtained “ground truth” data. In most spike-sorting algorithms in use today, the optimality of a clustering solution is assessed relative to some assumption on the distribution of the spike shapes associated with a particular single unit (e.g., Gaussianity) and by visual inspection of the clustering solution followed by manual validation. When the spatiotemporal waveforms of spikes from different cells overlap, the decision as to whether two spikes should be assigned to the same source can be quite subjective, if it is not based on reliable quantitative measures. We propose a new approach, whereby spike clusters are identified from the most consensual partition across an ensemble of clustering solutions. Using the variability of the clustering solutions across successive iterations of the same clustering algorithm (template matching based on K-means clusters), we estimate the probability of spikes being clustered together and identify groups of spikes that are not statistically distinguishable from one another. Thus, we identify spikes that are most likely to be clustered together and therefore correspond to consistent spike clusters. This method has the potential advantage that it does not rely on any model of the spike shapes. It also provides estimates of the proportion of misclassified spikes for each of the identified clusters. We tested our algorithm on several datasets for which there exists a ground truth (simultaneous intracellular data), and show that it performs close to the optimum reached by a support vector machine trained on the ground truth. We also show that the estimated rate of misclassification matches the proportion of misclassified spikes measured from the ground truth data. PMID:27536990

Consensus-Based Sorting of Neuronal Spike Waveforms.

PubMed

Fournier, Julien; Mueller, Christian M; Shein-Idelson, Mark; Hemberger, Mike; Laurent, Gilles

2016-01-01

Optimizing spike-sorting algorithms is difficult because sorted clusters can rarely be checked against independently obtained "ground truth" data. In most spike-sorting algorithms in use today, the optimality of a clustering solution is assessed relative to some assumption on the distribution of the spike shapes associated with a particular single unit (e.g., Gaussianity) and by visual inspection of the clustering solution followed by manual validation. When the spatiotemporal waveforms of spikes from different cells overlap, the decision as to whether two spikes should be assigned to the same source can be quite subjective, if it is not based on reliable quantitative measures. We propose a new approach, whereby spike clusters are identified from the most consensual partition across an ensemble of clustering solutions. Using the variability of the clustering solutions across successive iterations of the same clustering algorithm (template matching based on K-means clusters), we estimate the probability of spikes being clustered together and identify groups of spikes that are not statistically distinguishable from one another. Thus, we identify spikes that are most likely to be clustered together and therefore correspond to consistent spike clusters. This method has the potential advantage that it does not rely on any model of the spike shapes. It also provides estimates of the proportion of misclassified spikes for each of the identified clusters. We tested our algorithm on several datasets for which there exists a ground truth (simultaneous intracellular data), and show that it performs close to the optimum reached by a support vector machine trained on the ground truth. We also show that the estimated rate of misclassification matches the proportion of misclassified spikes measured from the ground truth data.

Multiview human activity recognition system based on spatiotemporal template for video surveillance system

NASA Astrophysics Data System (ADS)

Kushwaha, Alok Kumar Singh; Srivastava, Rajeev

2015-09-01

An efficient view invariant framework for the recognition of human activities from an input video sequence is presented. The proposed framework is composed of three consecutive modules: (i) detect and locate people by background subtraction, (ii) view invariant spatiotemporal template creation for different activities, (iii) and finally, template matching is performed for view invariant activity recognition. The foreground objects present in a scene are extracted using change detection and background modeling. The view invariant templates are constructed using the motion history images and object shape information for different human activities in a video sequence. For matching the spatiotemporal templates for various activities, the moment invariants and Mahalanobis distance are used. The proposed approach is tested successfully on our own viewpoint dataset, KTH action recognition dataset, i3DPost multiview dataset, MSR viewpoint action dataset, VideoWeb multiview dataset, and WVU multiview human action recognition dataset. From the experimental results and analysis over the chosen datasets, it is observed that the proposed framework is robust, flexible, and efficient with respect to multiple views activity recognition, scale, and phase variations.

Subpixel Mapping of Hyperspectral Image Based on Linear Subpixel Feature Detection and Object Optimization

NASA Astrophysics Data System (ADS)

Liu, Zhaoxin; Zhao, Liaoying; Li, Xiaorun; Chen, Shuhan

2018-04-01

Owing to the limitation of spatial resolution of the imaging sensor and the variability of ground surfaces, mixed pixels are widesperead in hyperspectral imagery. The traditional subpixel mapping algorithms treat all mixed pixels as boundary-mixed pixels while ignoring the existence of linear subpixels. To solve this question, this paper proposed a new subpixel mapping method based on linear subpixel feature detection and object optimization. Firstly, the fraction value of each class is obtained by spectral unmixing. Secondly, the linear subpixel features are pre-determined based on the hyperspectral characteristics and the linear subpixel feature; the remaining mixed pixels are detected based on maximum linearization index analysis. The classes of linear subpixels are determined by using template matching method. Finally, the whole subpixel mapping results are iteratively optimized by binary particle swarm optimization algorithm. The performance of the proposed subpixel mapping method is evaluated via experiments based on simulated and real hyperspectral data sets. The experimental results demonstrate that the proposed method can improve the accuracy of subpixel mapping.

Combining point context and dynamic time warping for online gesture recognition

NASA Astrophysics Data System (ADS)

Mao, Xia; Li, Chen

2017-05-01

Previous gesture recognition methods usually focused on recognizing gestures after the entire gesture sequences were obtained. However, in many practical applications, a system has to identify gestures before they end to give instant feedback. We present an online gesture recognition approach that can realize early recognition of unfinished gestures with low latency. First, a curvature buffer-based point context (CBPC) descriptor is proposed to extract the shape feature of a gesture trajectory. The CBPC descriptor is a complete descriptor with a simple computation, and thus has its superiority in online scenarios. Then, we introduce an online windowed dynamic time warping algorithm to realize online matching between the ongoing gesture and the template gestures. In the algorithm, computational complexity is effectively decreased by adding a sliding window to the accumulative distance matrix. Lastly, the experiments are conducted on the Australian sign language data set and the Kinect hand gesture (KHG) data set. Results show that the proposed method outperforms other state-of-the-art methods especially when gesture information is incomplete.

Markov chain algorithms: a template for building future robust low-power systems

PubMed Central

Deka, Biplab; Birklykke, Alex A.; Duwe, Henry; Mansinghka, Vikash K.; Kumar, Rakesh

2014-01-01

Although computational systems are looking towards post CMOS devices in the pursuit of lower power, the expected inherent unreliability of such devices makes it difficult to design robust systems without additional power overheads for guaranteeing robustness. As such, algorithmic structures with inherent ability to tolerate computational errors are of significant interest. We propose to cast applications as stochastic algorithms based on Markov chains (MCs) as such algorithms are both sufficiently general and tolerant to transition errors. We show with four example applications—Boolean satisfiability, sorting, low-density parity-check decoding and clustering—how applications can be cast as MC algorithms. Using algorithmic fault injection techniques, we demonstrate the robustness of these implementations to transition errors with high error rates. Based on these results, we make a case for using MCs as an algorithmic template for future robust low-power systems. PMID:24842030

VizieR Online Data Catalog: LAMOST candidate members of star clusters (Xiang+, 2015)

NASA Astrophysics Data System (ADS)

Xiang, M. S.; Liu, X. W.; Yuan, H. B.; Huang, Y.; Huo, Z. Y.; Zhang, H. W.; Chen, B. Q.; Zhang, H. H.; Sun, N. C.; Wang, C.; Zhao, Y. H.; Shi, J. R.; Luo, A. L.; Li, G. P.; Wu, Y.; Bai, Z. R.; Zhang, Y.; Hou, Y. H.; Yuan, H. L.; Li, G. W.; Wei, Z.

2015-08-01

In this work, we describe the algorithms and implementation of LSP3, the LAMOST Stellar Parameter Pipeline at Peking University, a pipeline developed to determine the stellar parameters (radial velocity Vr, effective temperature Teff, surface gravity logg and metallicity [Fe/H]) from LAMOST spectra based on a template-matching technique. Following the data policy of LAMOST surveys, the data as well as the LSP3 pipeline will be public released as value-added products of the first data release of LAMOST (LAMOST DR1; Bai et al., 2015, A&A submitted), currently scheduled in 2014 December and can be accessed via http://lamost973.pku.edu.cn/site/node/4, along with a description file. (1 data file).

Optimization of image processing algorithms on mobile platforms

NASA Astrophysics Data System (ADS)

Poudel, Pramod; Shirvaikar, Mukul

2011-03-01

This work presents a technique to optimize popular image processing algorithms on mobile platforms such as cell phones, net-books and personal digital assistants (PDAs). The increasing demand for video applications like context-aware computing on mobile embedded systems requires the use of computationally intensive image processing algorithms. The system engineer has a mandate to optimize them so as to meet real-time deadlines. A methodology to take advantage of the asymmetric dual-core processor, which includes an ARM and a DSP core supported by shared memory, is presented with implementation details. The target platform chosen is the popular OMAP 3530 processor for embedded media systems. It has an asymmetric dual-core architecture with an ARM Cortex-A8 and a TMS320C64x Digital Signal Processor (DSP). The development platform was the BeagleBoard with 256 MB of NAND RAM and 256 MB SDRAM memory. The basic image correlation algorithm is chosen for benchmarking as it finds widespread application for various template matching tasks such as face-recognition. The basic algorithm prototypes conform to OpenCV, a popular computer vision library. OpenCV algorithms can be easily ported to the ARM core which runs a popular operating system such as Linux or Windows CE. However, the DSP is architecturally more efficient at handling DFT algorithms. The algorithms are tested on a variety of images and performance results are presented measuring the speedup obtained due to dual-core implementation. A major advantage of this approach is that it allows the ARM processor to perform important real-time tasks, while the DSP addresses performance-hungry algorithms.

Vision-based measurement for rotational speed by improving Lucas-Kanade template tracking algorithm.

PubMed

Guo, Jie; Zhu, Chang'an; Lu, Siliang; Zhang, Dashan; Zhang, Chunyu

2016-09-01

Rotational angle and speed are important parameters for condition monitoring and fault diagnosis of rotating machineries, and their measurement is useful in precision machining and early warning of faults. In this study, a novel vision-based measurement algorithm is proposed to complete this task. A high-speed camera is first used to capture the video of the rotational object. To extract the rotational angle, the template-based Lucas-Kanade algorithm is introduced to complete motion tracking by aligning the template image in the video sequence. Given the special case of nonplanar surface of the cylinder object, a nonlinear transformation is designed for modeling the rotation tracking. In spite of the unconventional and complex form, the transformation can realize angle extraction concisely with only one parameter. A simulation is then conducted to verify the tracking effect, and a practical tracking strategy is further proposed to track consecutively the video sequence. Based on the proposed algorithm, instantaneous rotational speed (IRS) can be measured accurately and efficiently. Finally, the effectiveness of the proposed algorithm is verified on a brushless direct current motor test rig through the comparison with results obtained by the microphone. Experimental results demonstrate that the proposed algorithm can extract accurately rotational angles and can measure IRS with the advantage of noncontact and effectiveness.

Automated kidney morphology measurements from ultrasound images using texture and edge analysis

NASA Astrophysics Data System (ADS)

Ravishankar, Hariharan; Annangi, Pavan; Washburn, Michael; Lanning, Justin

2016-04-01

In a typical ultrasound scan, a sonographer measures Kidney morphology to assess renal abnormalities. Kidney morphology can also help to discriminate between chronic and acute kidney failure. The caliper placements and volume measurements are often time consuming and an automated solution will help to improve accuracy, repeatability and throughput. In this work, we developed an automated Kidney morphology measurement solution from long axis Ultrasound scans. Automated kidney segmentation is challenging due to wide variability in kidney shape, size, weak contrast of the kidney boundaries and presence of strong edges like diaphragm, fat layers. To address the challenges and be able to accurately localize and detect kidney regions, we present a two-step algorithm that makes use of edge and texture information in combination with anatomical cues. First, we use an edge analysis technique to localize kidney region by matching the edge map with predefined templates. To accurately estimate the kidney morphology, we use textural information in a machine learning algorithm framework using Haar features and Gradient boosting classifier. We have tested the algorithm on 45 unseen cases and the performance against ground truth is measured by computing Dice overlap, % error in major and minor axis of kidney. The algorithm shows successful performance on 80% cases.

Mode-dependent templates and scan order for H.264/AVC-based intra lossless coding.

PubMed

Gu, Zhouye; Lin, Weisi; Lee, Bu-Sung; Lau, Chiew Tong; Sun, Ming-Ting

2012-09-01

In H.264/advanced video coding (AVC), lossless coding and lossy coding share the same entropy coding module. However, the entropy coders in the H.264/AVC standard were original designed for lossy video coding and do not yield adequate performance for lossless video coding. In this paper, we analyze the problem with the current lossless coding scheme and propose a mode-dependent template (MD-template) based method for intra lossless coding. By exploring the statistical redundancy of the prediction residual in the H.264/AVC intra prediction modes, more zero coefficients are generated. By designing a new scan order for each MD-template, the scanned coefficients sequence fits the H.264/AVC entropy coders better. A fast implementation algorithm is also designed. With little computation increase, experimental results confirm that the proposed fast algorithm achieves about 7.2% bit saving compared with the current H.264/AVC fidelity range extensions high profile.

SnapDock—template-based docking by Geometric Hashing

PubMed Central

Estrin, Michael; Wolfson, Haim J.

2017-01-01

Abstract Motivation: A highly efficient template-based protein–protein docking algorithm, nicknamed SnapDock, is presented. It employs a Geometric Hashing-based structural alignment scheme to align the target proteins to the interfaces of non-redundant protein–protein interface libraries. Docking of a pair of proteins utilizing the 22 600 interface PIFACE library is performed in < 2 min on the average. A flexible version of the algorithm allowing hinge motion in one of the proteins is presented as well. Results: To evaluate the performance of the algorithm a blind re-modelling of 3547 PDB complexes, which have been uploaded after the PIFACE publication has been performed with success ratio of about 35%. Interestingly, a similar experiment with the template free PatchDock docking algorithm yielded a success rate of about 23% with roughly 1/3 of the solutions different from those of SnapDock. Consequently, the combination of the two methods gave a 42% success ratio. Availability and implementation: A web server of the application is under development. Contact: michaelestrin@gmail.com or wolfson@tau.ac.il PMID:28881968

VizieR Online Data Catalog: Census of blue stars in SDSS DR8 (Scibelli+, 2014)

NASA Astrophysics Data System (ADS)

Scibelli, S.; Newberg, H. J.; Carlin, J. L.; Yanny, B.

2015-02-01

We present a census of the 12060 spectra of blue objects ((g-r)0<-0.25) in the Sloan Digital Sky Survey (SDSS) Data Release 8 (DR8). As part of the data release, all of the spectra were cross-correlated with 48 template spectra of stars, galaxies, and QSOs to determine the best match. We compared the blue spectra by eye to the templates assigned in SDSS DR8. 10856 of the objects matched their assigned template, 170 could not be classified due to low signal-to-noise ratio, and 1034 were given new classifications. We identify 7458 DA white dwarfs, 1145 DB white dwarfs, 273 rarer white dwarfs (including carbon, DZ, DQ, and magnetic), 294 subdwarf O stars, 648 subdwarf B stars, 679 blue horizontal branch stars, 1026 blue stragglers, 13 cataclysmic variables, 129 white dwarf-M dwarf binaries, 36 objects with spectra similar to DO white dwarfs, 179, quasi-stellar objects (QSOs), and 10 galaxies. We provide two tables of these objects, sample spectra that match the templates, figures showing all of the spectra that were grouped by eye, and diagnostic plots that show the positions, colors, apparent magnitudes, proper motions, etc., for each classification. (3 data files).

Deep searches for broadband extended gravitational-wave emission bursts by heterogeneous computing

NASA Astrophysics Data System (ADS)

van Putten, Maurice H. P. M.

2017-09-01

We present a heterogeneous search algorithm for broadband extended gravitational-wave emission, expected from gamma-ray bursts and energetic core-collapse supernovae. It searches the (f,\\dot{f})-plane for long-duration bursts by inner engines slowly exhausting their energy reservoir by matched filtering on a graphics processor unit (GPU) over a template bank of millions of 1 s duration chirps. Parseval's theorem is used to predict the standard deviation σ of the filter output, taking advantage of the near-Gaussian noise in the LIGO S6 data over 350-2000 Hz. Tails exceeding a multiple of σ are communicated back to a central processing unit. This algorithm attains about 65% efficiency overall, normalized to the fast Fourier transform. At about one million correlations per second over data segments of 16 s duration (N=2^{16} samples), better than real-time analysis is achieved on a cluster of about a dozen GPUs. We demonstrate its application to the capture of high-frequency hardware LIGO injections. This algorithm serves as a starting point for deep all-sky searches in both archive data and real-time analysis in current observational runs.

System and method for constructing filters for detecting signals whose frequency content varies with time

DOEpatents

Qian, S.; Dunham, M.E.

1996-11-12

A system and method are disclosed for constructing a bank of filters which detect the presence of signals whose frequency content varies with time. The present invention includes a novel system and method for developing one or more time templates designed to match the received signals of interest and the bank of matched filters use the one or more time templates to detect the received signals. Each matched filter compares the received signal x(t) with a respective, unique time template that has been designed to approximate a form of the signals of interest. The robust time domain template is assumed to be of the order of w(t)=A(t)cos(2{pi}{phi}(t)) and the present invention uses the trajectory of a joint time-frequency representation of x(t) as an approximation of the instantaneous frequency function {phi}{prime}(t). First, numerous data samples of the received signal x(t) are collected. A joint time frequency representation is then applied to represent the signal, preferably using the time frequency distribution series. The joint time-frequency transformation represents the analyzed signal energy at time t and frequency f, P(t,f), which is a three-dimensional plot of time vs. frequency vs. signal energy. Then P(t,f) is reduced to a multivalued function f(t), a two dimensional plot of time vs. frequency, using a thresholding process. Curve fitting steps are then performed on the time/frequency plot, preferably using Levenberg-Marquardt curve fitting techniques, to derive a general instantaneous frequency function {phi}{prime}(t) which best fits the multivalued function f(t). Integrating {phi}{prime}(t) along t yields {phi}{prime}(t), which is then inserted into the form of the time template equation. A suitable amplitude A(t) is also preferably determined. Once the time template has been determined, one or more filters are developed which each use a version or form of the time template. 7 figs.

Illumination invariant feature point matching for high-resolution planetary remote sensing images

NASA Astrophysics Data System (ADS)

Wu, Bo; Zeng, Hai; Hu, Han

2018-03-01

Despite its success with regular close-range and remote-sensing images, the scale-invariant feature transform (SIFT) algorithm is essentially not invariant to illumination differences due to the use of gradients for feature description. In planetary remote sensing imagery, which normally lacks sufficient textural information, salient regions are generally triggered by the shadow effects of keypoints, reducing the matching performance of classical SIFT. Based on the observation of dual peaks in a histogram of the dominant orientations of SIFT keypoints, this paper proposes an illumination-invariant SIFT matching method for high-resolution planetary remote sensing images. First, as the peaks in the orientation histogram are generally aligned closely with the sub-solar azimuth angle at the time of image collection, an adaptive suppression Gaussian function is tuned to level the histogram and thereby alleviate the differences in illumination caused by a changing solar angle. Next, the suppression function is incorporated into the original SIFT procedure for obtaining feature descriptors, which are used for initial image matching. Finally, as the distribution of feature descriptors changes after anisotropic suppression, and the ratio check used for matching and outlier removal in classical SIFT may produce inferior results, this paper proposes an improved matching procedure based on cross-checking and template image matching. The experimental results for several high-resolution remote sensing images from both the Moon and Mars, with illumination differences of 20°-180°, reveal that the proposed method retrieves about 40%-60% more matches than the classical SIFT method. The proposed method is of significance for matching or co-registration of planetary remote sensing images for their synergistic use in various applications. It also has the potential to be useful for flyby and rover images by integrating with the affine invariant feature detectors.

I-TASSER: fully automated protein structure prediction in CASP8.

PubMed

Zhang, Yang

2009-01-01

The I-TASSER algorithm for 3D protein structure prediction was tested in CASP8, with the procedure fully automated in both the Server and Human sections. The quality of the server models is close to that of human ones but the human predictions incorporate more diverse templates from other servers which improve the human predictions in some of the distant homology targets. For the first time, the sequence-based contact predictions from machine learning techniques are found helpful for both template-based modeling (TBM) and template-free modeling (FM). In TBM, although the accuracy of the sequence based contact predictions is on average lower than that from template-based ones, the novel contacts in the sequence-based predictions, which are complementary to the threading templates in the weakly or unaligned regions, are important to improve the global and local packing in these regions. Moreover, the newly developed atomic structural refinement algorithm was tested in CASP8 and found to improve the hydrogen-bonding networks and the overall TM-score, which is mainly due to its ability of removing steric clashes so that the models can be generated from cluster centroids. Nevertheless, one of the major issues of the I-TASSER pipeline is the model selection where the best models could not be appropriately recognized when the correct templates are detected only by the minority of the threading algorithms. There are also problems related with domain-splitting and mirror image recognition which mainly influences the performance of I-TASSER modeling in the FM-based structure predictions. Copyright 2009 Wiley-Liss, Inc.

Nodule Detection in a Lung Region that's Segmented with Using Genetic Cellular Neural Networks and 3D Template Matching with Fuzzy Rule Based Thresholding

PubMed Central

Osman, Onur; Ucan, Osman N.

2008-01-01

Objective The purpose of this study was to develop a new method for automated lung nodule detection in serial section CT images with using the characteristics of the 3D appearance of the nodules that distinguish themselves from the vessels. Materials and Methods Lung nodules were detected in four steps. First, to reduce the number of region of interests (ROIs) and the computation time, the lung regions of the CTs were segmented using Genetic Cellular Neural Networks (G-CNN). Then, for each lung region, ROIs were specified with using the 8 directional search; +1 or -1 values were assigned to each voxel. The 3D ROI image was obtained by combining all the 2-Dimensional (2D) ROI images. A 3D template was created to find the nodule-like structures on the 3D ROI image. Convolution of the 3D ROI image with the proposed template strengthens the shapes that are similar to those of the template and it weakens the other ones. Finally, fuzzy rule based thresholding was applied and the ROI's were found. To test the system's efficiency, we used 16 cases with a total of 425 slices, which were taken from the Lung Image Database Consortium (LIDC) dataset. Results The computer aided diagnosis (CAD) system achieved 100% sensitivity with 13.375 FPs per case when the nodule thickness was greater than or equal to 5.625 mm. Conclusion Our results indicate that the detection performance of our algorithm is satisfactory, and this may well improve the performance of computer-aided detection of lung nodules. PMID:18253070

Surface smoothing and template partitioning for cranial implant CAD

NASA Astrophysics Data System (ADS)

Min, Kyoung-june; Dean, David

2005-04-01

Employing patient-specific prefabricated implants can be an effective treatment for large cranial defects (i.e., > 25 cm2). We have previously demonstrated the use of Computer Aided Design (CAD) software that starts with the patient"s 3D head CT-scan. A template is accurately matched to the pre-detected skull defect margin. For unilateral cranial defects the template is derived from a left-to-right mirrored skull image. However, two problems arise: (1) slice edge artifacts generated during isosurface polygonalization are inherited by the final implant; and (2) partitioning (i.e., cookie-cutting) the implant surface from the mirrored skull image usually results in curvature discontinuities across the interface between the patient"s defect and the implant. To solve these problems, we introduce a novel space curve-to-surface partitioning algorithm following a ray-casting surface re-sampling and smoothing procedure. Specifically, the ray-cast re-sampling is followed by bilinear interpolation and low-pass filtering. The resulting surface has a highly regular grid-like topological structure of quadrilaterally arranged triangles. Then, we replace the regions to be partitioned with predefined sets of triangular elements thereby cutting the template surface to accurately fit the defect margin at high resolution and without surface curvature discontinuities. Comparisons of the CAD implants for five patients against the manually generated implant that the patient actually received show an average implant-patient gap of 0.45mm for the former and 2.96mm for the latter. Also, average maximum normalized curvature of interfacing surfaces was found to be smoother, 0.043, for the former than the latter, 0.097. This indicates that the CAD implants would provide a significantly better fit.

An ensemble approach to protein fold classification by integration of template-based assignment and support vector machine classifier.

PubMed

Xia, Jiaqi; Peng, Zhenling; Qi, Dawei; Mu, Hongbo; Yang, Jianyi

2017-03-15

Protein fold classification is a critical step in protein structure prediction. There are two possible ways to classify protein folds. One is through template-based fold assignment and the other is ab-initio prediction using machine learning algorithms. Combination of both solutions to improve the prediction accuracy was never explored before. We developed two algorithms, HH-fold and SVM-fold for protein fold classification. HH-fold is a template-based fold assignment algorithm using the HHsearch program. SVM-fold is a support vector machine-based ab-initio classification algorithm, in which a comprehensive set of features are extracted from three complementary sequence profiles. These two algorithms are then combined, resulting to the ensemble approach TA-fold. We performed a comprehensive assessment for the proposed methods by comparing with ab-initio methods and template-based threading methods on six benchmark datasets. An accuracy of 0.799 was achieved by TA-fold on the DD dataset that consists of proteins from 27 folds. This represents improvement of 5.4-11.7% over ab-initio methods. After updating this dataset to include more proteins in the same folds, the accuracy increased to 0.971. In addition, TA-fold achieved >0.9 accuracy on a large dataset consisting of 6451 proteins from 184 folds. Experiments on the LE dataset show that TA-fold consistently outperforms other threading methods at the family, superfamily and fold levels. The success of TA-fold is attributed to the combination of template-based fold assignment and ab-initio classification using features from complementary sequence profiles that contain rich evolution information. http://yanglab.nankai.edu.cn/TA-fold/. yangjy@nankai.edu.cn or mhb-506@163.com. Supplementary data are available at Bioinformatics online. © The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com

Auditing Practice Style Variation in Pediatric Inpatient Asthma Care.

PubMed

Silber, Jeffrey H; Rosenbaum, Paul R; Wang, Wei; Ludwig, Justin M; Calhoun, Shawna; Guevara, James P; Zorc, Joseph J; Zeigler, Ashley; Even-Shoshan, Orit

2016-09-01

Asthma is the most prevalent chronic illness among children, remaining a leading cause of pediatric hospitalizations and representing a major financial burden to many health care systems. To implement a new auditing process examining whether differences in hospital practice style may be associated with potential resource savings or inefficiencies in treating pediatric asthma admissions. A retrospective matched-cohort design study, matched for asthma severity, compared practice patterns for patients admitted to Children's Hospital Association hospitals contributing data to the Pediatric Hospital Information System (PHIS) database. With 3 years of PHIS data on 48 887 children, an asthma template was constructed consisting of representative children hospitalized for asthma between April 1, 2011, and March 31, 2014. The template was matched with either a 1:1, 2:1, or 3:1 ratio at each of 37 tertiary care children's hospitals, depending on available sample size. Treatment at each PHIS hospital. Cost, length of stay, and intensive care unit (ICU) utilization. After matching patients (n = 9100; mean [SD] age, 7.1 [3.6] years; 3418 [37.6%] females) to the template (n = 100, mean [SD] age, 7.2 [3.7] years; 37 [37.0%] females), there was no significant difference in observable patient characteristics at the 37 hospitals meeting the matching criteria. Despite similar characteristics of the patients, we observed large and significant variation in use of the ICUs as well as in length of stay and cost. For the same template-matched populations, comparing utilization between the 12.5th percentile (lower eighth) and 87.5th percentile (upper eighth) of hospitals, median cost varied by 87% ($3157 vs $5912 per patient; P < .001); total hospital length of stay varied by 47% (1.5 vs 2.2 days; P < .001); and ICU utilization was 254% higher (6.5% vs 23.0%; P < .001). Furthermore, the patterns of resource utilization by patient risk differed significantly across hospitals. For example, as patient risk increased one hospital displayed significantly increasing costs compared with their matched controls (comparative cost difference: lowest risk, -34.21%; highest risk, 53.27%; P < .001). In contrast, another hospital displayed significantly decreasing costs relative to their matched controls as patient risk increased (comparative cost difference: lowest risk, -10.12%; highest risk, -16.85%; P = .01). For children with asthma who had similar characteristics, we observed different hospital resource utilization; some values differed greatly, with important differences by initial patient risk. Through the template matching audit, hospitals and stakeholders can better understand where this excess variation occurs and can help to pinpoint practice styles that should be emulated or avoided.

A spline-based regression parameter set for creating customized DARTEL MRI brain templates from infancy to old age.

PubMed

Wilke, Marko

2018-02-01

This dataset contains the regression parameters derived by analyzing segmented brain MRI images (gray matter and white matter) from a large population of healthy subjects, using a multivariate adaptive regression splines approach. A total of 1919 MRI datasets ranging in age from 1-75 years from four publicly available datasets (NIH, C-MIND, fCONN, and IXI) were segmented using the CAT12 segmentation framework, writing out gray matter and white matter images normalized using an affine-only spatial normalization approach. These images were then subjected to a six-step DARTEL procedure, employing an iterative non-linear registration approach and yielding increasingly crisp intermediate images. The resulting six datasets per tissue class were then analyzed using multivariate adaptive regression splines, using the CerebroMatic toolbox. This approach allows for flexibly modelling smoothly varying trajectories while taking into account demographic (age, gender) as well as technical (field strength, data quality) predictors. The resulting regression parameters described here can be used to generate matched DARTEL or SHOOT templates for a given population under study, from infancy to old age. The dataset and the algorithm used to generate it are publicly available at https://irc.cchmc.org/software/cerebromatic.php.

SNBRFinder: A Sequence-Based Hybrid Algorithm for Enhanced Prediction of Nucleic Acid-Binding Residues.

PubMed

Yang, Xiaoxia; Wang, Jia; Sun, Jun; Liu, Rong

2015-01-01

Protein-nucleic acid interactions are central to various fundamental biological processes. Automated methods capable of reliably identifying DNA- and RNA-binding residues in protein sequence are assuming ever-increasing importance. The majority of current algorithms rely on feature-based prediction, but their accuracy remains to be further improved. Here we propose a sequence-based hybrid algorithm SNBRFinder (Sequence-based Nucleic acid-Binding Residue Finder) by merging a feature predictor SNBRFinderF and a template predictor SNBRFinderT. SNBRFinderF was established using the support vector machine whose inputs include sequence profile and other complementary sequence descriptors, while SNBRFinderT was implemented with the sequence alignment algorithm based on profile hidden Markov models to capture the weakly homologous template of query sequence. Experimental results show that SNBRFinderF was clearly superior to the commonly used sequence profile-based predictor and SNBRFinderT can achieve comparable performance to the structure-based template methods. Leveraging the complementary relationship between these two predictors, SNBRFinder reasonably improved the performance of both DNA- and RNA-binding residue predictions. More importantly, the sequence-based hybrid prediction reached competitive performance relative to our previous structure-based counterpart. Our extensive and stringent comparisons show that SNBRFinder has obvious advantages over the existing sequence-based prediction algorithms. The value of our algorithm is highlighted by establishing an easy-to-use web server that is freely accessible at http://ibi.hzau.edu.cn/SNBRFinder.

A multibiometric face recognition fusion framework with template protection

NASA Astrophysics Data System (ADS)

Chindaro, S.; Deravi, F.; Zhou, Z.; Ng, M. W. R.; Castro Neves, M.; Zhou, X.; Kelkboom, E.

2010-04-01

In this work we present a multibiometric face recognition framework based on combining information from 2D with 3D facial features. The 3D biometrics channel is protected by a privacy enhancing technology, which uses error correcting codes and cryptographic primitives to safeguard the privacy of the users of the biometric system at the same time enabling accurate matching through fusion with 2D. Experiments are conducted to compare the matching performance of such multibiometric systems with the individual biometric channels working alone and with unprotected multibiometric systems. The results show that the proposed hybrid system incorporating template protection, match and in some cases exceed the performance of corresponding unprotected equivalents, in addition to offering the additional privacy protection.

Multiple template-based image matching using alpha-rooted quaternion phase correlation

NASA Astrophysics Data System (ADS)

DelMarco, Stephen

2010-04-01

In computer vision applications, image matching performed on quality-degraded imagery is difficult due to image content distortion and noise effects. State-of-the art keypoint based matchers, such as SURF and SIFT, work very well on clean imagery. However, performance can degrade significantly in the presence of high noise and clutter levels. Noise and clutter cause the formation of false features which can degrade recognition performance. To address this problem, previously we developed an extension to the classical amplitude and phase correlation forms, which provides improved robustness and tolerance to image geometric misalignments and noise. This extension, called Alpha-Rooted Phase Correlation (ARPC), combines Fourier domain-based alpha-rooting enhancement with classical phase correlation. ARPC provides tunable parameters to control the alpha-rooting enhancement. These parameter values can be optimized to tradeoff between high narrow correlation peaks, and more robust wider, but smaller peaks. Previously, we applied ARPC in the radon transform domain for logo image recognition in the presence of rotational image misalignments. In this paper, we extend ARPC to incorporate quaternion Fourier transforms, thereby creating Alpha-Rooted Quaternion Phase Correlation (ARQPC). We apply ARQPC to the logo image recognition problem. We use ARQPC to perform multiple-reference logo template matching by representing multiple same-class reference templates as quaternion-valued images. We generate recognition performance results on publicly-available logo imagery, and compare recognition results to results generated from standard approaches. We show that small deviations in reference templates of sameclass logos can lead to improved recognition performance using the joint matching inherent in ARQPC.

Impact of Sensor Misplacement on Dynamic Time Warping Based Human Activity Recognition using Wearable Computers.

PubMed

Kale, Nimish; Lee, Jaeseong; Lotfian, Reza; Jafari, Roozbeh

2012-10-01

Daily living activity monitoring is important for early detection of the onset of many diseases and for improving quality of life especially in elderly. A wireless wearable network of inertial sensor nodes can be used to observe daily motions. Continuous stream of data generated by these sensor networks can be used to recognize the movements of interest. Dynamic Time Warping (DTW) is a widely used signal processing method for time-series pattern matching because of its robustness to variations in time and speed as opposed to other template matching methods. Despite this flexibility, for the application of activity recognition, DTW can only find the similarity between the template of a movement and the incoming samples, when the location and orientation of the sensor remains unchanged. Due to this restriction, small sensor misplacements can lead to a decrease in the classification accuracy. In this work, we adopt DTW distance as a feature for real-time detection of human daily activities like sit to stand in the presence of sensor misplacement. To measure this performance of DTW, we need to create a large number of sensor configurations while the sensors are rotated or misplaced. Creating a large number of closely spaced sensors is impractical. To address this problem, we use the marker based optical motion capture system and generate simulated inertial sensor data for different locations and orientations on the body. We study the performance of the DTW under these conditions to determine the worst-case sensor location variations that the algorithm can accommodate.

Learning-based meta-algorithm for MRI brain extraction.

PubMed

Shi, Feng; Wang, Li; Gilmore, John H; Lin, Weili; Shen, Dinggang

2011-01-01

Multiple-segmentation-and-fusion method has been widely used for brain extraction, tissue segmentation, and region of interest (ROI) localization. However, such studies are hindered in practice by their computational complexity, mainly coming from the steps of template selection and template-to-subject nonlinear registration. In this study, we address these two issues and propose a novel learning-based meta-algorithm for MRI brain extraction. Specifically, we first use exemplars to represent the entire template library, and assign the most similar exemplar to the test subject. Second, a meta-algorithm combining two existing brain extraction algorithms (BET and BSE) is proposed to conduct multiple extractions directly on test subject. Effective parameter settings for the meta-algorithm are learned from the training data and propagated to subject through exemplars. We further develop a level-set based fusion method to combine multiple candidate extractions together with a closed smooth surface, for obtaining the final result. Experimental results show that, with only a small portion of subjects for training, the proposed method is able to produce more accurate and robust brain extraction results, at Jaccard Index of 0.956 +/- 0.010 on total 340 subjects under 6-fold cross validation, compared to those by the BET and BSE even using their best parameter combinations.

Autonomous Vision Navigation for Spacecraft in Lunar Orbit

NASA Astrophysics Data System (ADS)

Bader, Nolan A.

NASA aims to achieve unprecedented navigational reliability for the first manned lunar mission of the Orion spacecraft in 2023. A technique for accomplishing this is to integrate autonomous feature tracking as an added means of improving position and velocity estimation. In this thesis, a template matching algorithm and optical sensor are tested onboard three simulated lunar trajectories using linear covariance techniques under various conditions. A preliminary characterization of the camera gives insight into its ability to determine azimuth and elevation angles to points on the surface of the Moon. A navigation performance analysis shows that an optical camera sensor can aid in decreasing position and velocity errors, particularly in a loss of communication scenario. Furthermore, it is found that camera quality and computational capability are driving factors affecting the performance of such a system.

A matrix-algebraic formulation of distributed-memory maximal cardinality matching algorithms in bipartite graphs

DOE PAGES

Azad, Ariful; Buluç, Aydın

2016-05-16

We describe parallel algorithms for computing maximal cardinality matching in a bipartite graph on distributed-memory systems. Unlike traditional algorithms that match one vertex at a time, our algorithms process many unmatched vertices simultaneously using a matrix-algebraic formulation of maximal matching. This generic matrix-algebraic framework is used to develop three efficient maximal matching algorithms with minimal changes. The newly developed algorithms have two benefits over existing graph-based algorithms. First, unlike existing parallel algorithms, cardinality of matching obtained by the new algorithms stays constant with increasing processor counts, which is important for predictable and reproducible performance. Second, relying on bulk-synchronous matrix operations,more » these algorithms expose a higher degree of parallelism on distributed-memory platforms than existing graph-based algorithms. We report high-performance implementations of three maximal matching algorithms using hybrid OpenMP-MPI and evaluate the performance of these algorithm using more than 35 real and randomly generated graphs. On real instances, our algorithms achieve up to 200 × speedup on 2048 cores of a Cray XC30 supercomputer. Even higher speedups are obtained on larger synthetically generated graphs where our algorithms show good scaling on up to 16,384 cores.« less

Implementing a C++ Version of the Joint Seismic-Geodetic Algorithm for Finite-Fault Detection and Slip Inversion for Earthquake Early Warning

NASA Astrophysics Data System (ADS)

Smith, D. E.; Felizardo, C.; Minson, S. E.; Boese, M.; Langbein, J. O.; Guillemot, C.; Murray, J. R.

2015-12-01

The earthquake early warning (EEW) systems in California and elsewhere can greatly benefit from algorithms that generate estimates of finite-fault parameters. These estimates could significantly improve real-time shaking calculations and yield important information for immediate disaster response. Minson et al. (2015) determined that combining FinDer's seismic-based algorithm (Böse et al., 2012) with BEFORES' geodetic-based algorithm (Minson et al., 2014) yields a more robust and informative joint solution than using either algorithm alone. FinDer examines the distribution of peak ground accelerations from seismic stations and determines the best finite-fault extent and strike from template matching. BEFORES employs a Bayesian framework to search for the best slip inversion over all possible fault geometries in terms of strike and dip. Using FinDer and BEFORES together generates estimates of finite-fault extent, strike, dip, preferred slip, and magnitude. To yield the quickest, most flexible, and open-source version of the joint algorithm, we translated BEFORES and FinDer from Matlab into C++. We are now developing a C++ Application Protocol Interface for these two algorithms to be connected to the seismic and geodetic data flowing from the EEW system. The interface that is being developed will also enable communication between the two algorithms to generate the joint solution of finite-fault parameters. Once this interface is developed and implemented, the next step will be to run test seismic and geodetic data through the system via the Earthworm module, Tank Player. This will allow us to examine algorithm performance on simulated data and past real events.

Using trend templates in a neonatal seizure algorithm improves detection of short seizures in a foetal ovine model.

PubMed

Zwanenburg, Alex; Andriessen, Peter; Jellema, Reint K; Niemarkt, Hendrik J; Wolfs, Tim G A M; Kramer, Boris W; Delhaas, Tammo

2015-03-01

Seizures below one minute in duration are difficult to assess correctly using seizure detection algorithms. We aimed to improve neonatal detection algorithm performance for short seizures through the use of trend templates for seizure onset and end. Bipolar EEG were recorded within a transiently asphyxiated ovine model at 0.7 gestational age, a common experimental model for studying brain development in humans of 30-34 weeks of gestation. Transient asphyxia led to electrographic seizures within 6-8 h. A total of 3159 seizures, 2386 shorter than one minute, were annotated in 1976 h-long EEG recordings from 17 foetal lambs. To capture EEG characteristics, five features, sensitive to seizures, were calculated and used to derive trend information. Feature values and trend information were used as input for support vector machine classification and subsequently post-processed. Performance metrics, calculated after post-processing, were compared between analyses with and without employing trend information. Detector performance was assessed after five-fold cross-validation conducted ten times with random splits. The use of trend templates for seizure onset and end in a neonatal seizure detection algorithm significantly improves the correct detection of short seizures using two-channel EEG recordings from 54.3% (52.6-56.1) to 59.5% (58.5-59.9) at FDR 2.0 (median (range); p < 0.001, Wilcoxon signed rank test). Using trend templates might therefore aid in detection of short seizures by EEG monitoring at the NICU.

A Matched Field Processing Framework for Coherent Detection Over Local and Regional Networks (Postprint)

DTIC Science & Technology

2011-12-30

the term " superresolution "). The single-phase matched field statistic for a given template was also demonstrated to be a viable detection statistic... Superresolution with seismic arrays using empirical matched field processing, Geophys. J. Int. 182: 1455–1477. Kim, K.-H. and Park, Y. (2010): The 20

An adaptive clustering algorithm for image matching based on corner feature

NASA Astrophysics Data System (ADS)

Wang, Zhe; Dong, Min; Mu, Xiaomin; Wang, Song

2018-04-01

The traditional image matching algorithm always can not balance the real-time and accuracy better, to solve the problem, an adaptive clustering algorithm for image matching based on corner feature is proposed in this paper. The method is based on the similarity of the matching pairs of vector pairs, and the adaptive clustering is performed on the matching point pairs. Harris corner detection is carried out first, the feature points of the reference image and the perceived image are extracted, and the feature points of the two images are first matched by Normalized Cross Correlation (NCC) function. Then, using the improved algorithm proposed in this paper, the matching results are clustered to reduce the ineffective operation and improve the matching speed and robustness. Finally, the Random Sample Consensus (RANSAC) algorithm is used to match the matching points after clustering. The experimental results show that the proposed algorithm can effectively eliminate the most wrong matching points while the correct matching points are retained, and improve the accuracy of RANSAC matching, reduce the computation load of whole matching process at the same time.

Automatic generation of endocardial surface meshes with 1-to-1 correspondence from cine-MR images

NASA Astrophysics Data System (ADS)

Su, Yi; Teo, S.-K.; Lim, C. W.; Zhong, L.; Tan, R. S.

2015-03-01

In this work, we develop an automatic method to generate a set of 4D 1-to-1 corresponding surface meshes of the left ventricle (LV) endocardial surface which are motion registered over the whole cardiac cycle. These 4D meshes have 1- to-1 point correspondence over the entire set, and is suitable for advanced computational processing, such as shape analysis, motion analysis and finite element modelling. The inputs to the method are the set of 3D LV endocardial surface meshes of the different frames/phases of the cardiac cycle. Each of these meshes is reconstructed independently from border-delineated MR images and they have no correspondence in terms of number of vertices/points and mesh connectivity. To generate point correspondence, the first frame of the LV mesh model is used as a template to be matched to the shape of the meshes in the subsequent phases. There are two stages in the mesh correspondence process: (1) a coarse matching phase, and (2) a fine matching phase. In the coarse matching phase, an initial rough matching between the template and the target is achieved using a radial basis function (RBF) morphing process. The feature points on the template and target meshes are automatically identified using a 16-segment nomenclature of the LV. In the fine matching phase, a progressive mesh projection process is used to conform the rough estimate to fit the exact shape of the target. In addition, an optimization-based smoothing process is used to achieve superior mesh quality and continuous point motion.

MIMO: an efficient tool for molecular interaction maps overlap

PubMed Central

2013-01-01

Background Molecular pathways represent an ensemble of interactions occurring among molecules within the cell and between cells. The identification of similarities between molecular pathways across organisms and functions has a critical role in understanding complex biological processes. For the inference of such novel information, the comparison of molecular pathways requires to account for imperfect matches (flexibility) and to efficiently handle complex network topologies. To date, these characteristics are only partially available in tools designed to compare molecular interaction maps. Results Our approach MIMO (Molecular Interaction Maps Overlap) addresses the first problem by allowing the introduction of gaps and mismatches between query and template pathways and permits -when necessary- supervised queries incorporating a priori biological information. It then addresses the second issue by relying directly on the rich graph topology described in the Systems Biology Markup Language (SBML) standard, and uses multidigraphs to efficiently handle multiple queries on biological graph databases. The algorithm has been here successfully used to highlight the contact point between various human pathways in the Reactome database. Conclusions MIMO offers a flexible and efficient graph-matching tool for comparing complex biological pathways. PMID:23672344

Topics in the Detection of Gravitational Waves from Compact Binary Inspirals

NASA Astrophysics Data System (ADS)

Kapadia, Shasvath Jagat

Orbiting compact binaries - such as binary black holes, binary neutron stars and neutron star-black hole binaries - are among the most promising sources of gravitational waves observable by ground-based interferometric detectors. Despite numerous sophisticated engineering techniques, the gravitational wave signals will be buried deep within noise generated by various instrumental and environmental processes, and need to be extracted via a signal processing technique referred to as matched filtering. Matched filtering requires large banks of signal templates that are faithful representations of the true gravitational waveforms produced by astrophysical binaries. The accurate and efficient production of templates is thus crucial to the success of signal processing and data analysis. To that end, the dissertation presents a numerical technique that calibrates existing analytical (Post-Newtonian) waveforms, which are relatively inexpensive, to more accurate fiducial waveforms that are computationally expensive to generate. The resulting waveform family is significantly more accurate than the analytical waveforms, without incurring additional computational costs of production. Certain kinds of transient background noise artefacts, called "glitches'', can masquerade as gravitational wave signals for short durations and throw-off the matched-filter algorithm. Identifying glitches from true gravitational wave signals is a highly non-trivial exercise in data analysis which has been attempted with varying degrees of success. We present here a machine-learning based approach that exploits the various attributes of glitches and signals within detector data to provide a classification scheme that is a significant improvement over previous methods. The dissertation concludes by investigating the possibility of detecting a non-linear DC imprint, called the Christodoulou memory, produced in the arms of ground-based interferometers by the recently detected gravitational waves. The memory, which is even smaller in amplitude than the primary (detected) gravitational waves, will almost certainly not be seen in the current detection event. Nevertheless, future space-based detectors will likely be sensitive enough to observe the memory.

Improving Pulse Rate Measurements during Random Motion Using a Wearable Multichannel Reflectance Photoplethysmograph.

PubMed

Warren, Kristen M; Harvey, Joshua R; Chon, Ki H; Mendelson, Yitzhak

2016-03-07

Photoplethysmographic (PPG) waveforms are used to acquire pulse rate (PR) measurements from pulsatile arterial blood volume. PPG waveforms are highly susceptible to motion artifacts (MA), limiting the implementation of PR measurements in mobile physiological monitoring devices. Previous studies have shown that multichannel photoplethysmograms can successfully acquire diverse signal information during simple, repetitive motion, leading to differences in motion tolerance across channels. In this paper, we investigate the performance of a custom-built multichannel forehead-mounted photoplethysmographic sensor under a variety of intense motion artifacts. We introduce an advanced multichannel template-matching algorithm that chooses the channel with the least motion artifact to calculate PR for each time instant. We show that for a wide variety of random motion, channels respond differently to motion artifacts, and the multichannel estimate outperforms single-channel estimates in terms of motion tolerance, signal quality, and PR errors. We have acquired 31 data sets consisting of PPG waveforms corrupted by random motion and show that the accuracy of PR measurements achieved was increased by up to 2.7 bpm when the multichannel-switching algorithm was compared to individual channels. The percentage of PR measurements with error ≤ 5 bpm during motion increased by 18.9% when the multichannel switching algorithm was compared to the mean PR from all channels. Moreover, our algorithm enables automatic selection of the best signal fidelity channel at each time point among the multichannel PPG data.

General Metropolis-Hastings jump diffusions for automatic target recognition in infrared scenes

NASA Astrophysics Data System (ADS)

Lanterman, Aaron D.; Miller, Michael I.; Snyder, Donald L.

1997-04-01

To locate and recognize ground-based targets in forward- looking IR (FLIR) images, 3D faceted models with associated pose parameters are formulated to accommodate the variability found in FLIR imagery. Taking a Bayesian approach, scenes are simulated from the emissive characteristics of the CAD models and compared with the collected data by a likelihood function based on sensor statistics. This likelihood is combined with a prior distribution defined over the set of possible scenes to form a posterior distribution. To accommodate scenes with variable numbers of targets, the posterior distribution is defined over parameter vectors of varying dimension. An inference algorithm based on Metropolis-Hastings jump- diffusion processes empirically samples from the posterior distribution, generating configurations of templates and transformations that match the collected sensor data with high probability. The jumps accommodate the addition and deletion of targets and the estimation of target identities; diffusions refine the hypotheses by drifting along the gradient of the posterior distribution with respect to the orientation and position parameters. Previous results on jumps strategies analogous to the Metropolis acceptance/rejection algorithm, with proposals drawn from the prior and accepted based on the likelihood, are extended to encompass general Metropolis-Hastings proposal densities. In particular, the algorithm proposes moves by drawing from the posterior distribution over computationally tractible subsets of the parameter space. The algorithm is illustrated by an implementation on a Silicon Graphics Onyx/Reality Engine.

A new star tracker concept for satellite attitude determination based on a multi-purpose panoramic camera

NASA Astrophysics Data System (ADS)

Opromolla, Roberto; Fasano, Giancarmine; Rufino, Giancarlo; Grassi, Michele; Pernechele, Claudio; Dionisio, Cesare

2017-11-01

This paper presents an innovative algorithm developed for attitude determination of a space platform. The algorithm exploits images taken from a multi-purpose panoramic camera equipped with hyper-hemispheric lens and used as star tracker. The sensor architecture is also original since state-of-the-art star trackers accurately image as many stars as possible within a narrow- or medium-size field-of-view, while the considered sensor observes an extremely large portion of the celestial sphere but its observation capabilities are limited by the features of the optical system. The proposed original approach combines algorithmic concepts, like template matching and point cloud registration, inherited from the computer vision and robotic research fields, to carry out star identification. The final aim is to provide a robust and reliable initial attitude solution (lost-in-space mode), with a satisfactory accuracy level in view of the multi-purpose functionality of the sensor and considering its limitations in terms of resolution and sensitivity. Performance evaluation is carried out within a simulation environment in which the panoramic camera operation is realistically reproduced, including perturbations in the imaged star pattern. Results show that the presented algorithm is able to estimate attitude with accuracy better than 1° with a success rate around 98% evaluated by densely covering the entire space of the parameters representing the camera pointing in the inertial space.

Classification of motor activities through derivative dynamic time warping applied on accelerometer data.

PubMed

Muscillo, Rossana; Conforto, Silvia; Schmid, Maurizio; Caselli, Paolo; D'Alessio, Tommaso

2007-01-01

In the context of tele-monitoring, great interest is presently devoted to physical activity, mainly of elderly or people with disabilities. In this context, many researchers studied the recognition of activities of daily living by using accelerometers. The present work proposes a novel algorithm for activity recognition that considers the variability in movement speed, by using dynamic programming. This objective is realized by means of a matching and recognition technique that determines the distance between the signal input and a set of previously defined templates. Two different approaches are here presented, one based on Dynamic Time Warping (DTW) and the other based on the Derivative Dynamic Time Warping (DDTW). The algorithm was applied to the recognition of gait, climbing and descending stairs, using a biaxial accelerometer placed on the shin. The results on DDTW, obtained by using only one sensor channel on the shin showed an average recognition score of 95%, higher than the values obtained with DTW (around 85%). Both DTW and DDTW consistently show higher classification rate than classical Linear Time Warping (LTW).

Automatic capture of attention by conceptually generated working memory templates.

PubMed

Sun, Sol Z; Shen, Jenny; Shaw, Mark; Cant, Jonathan S; Ferber, Susanne

2015-08-01

Many theories of attention propose that the contents of working memory (WM) can act as an attentional template, which biases processing in favor of perceptually similar inputs. While support has been found for this claim, it is unclear how attentional templates are generated when searching real-world environments. We hypothesized that in naturalistic settings, attentional templates are commonly generated from conceptual knowledge, an idea consistent with sensorimotor models of knowledge representation. Participants performed a visual search task in the delay period of a WM task, where the item in memory was either a colored disk or a word associated with a color concept (e.g., "Rose," associated with red). During search, we manipulated whether a singleton distractor in the array matched the contents of WM. Overall, we found that search times were impaired in the presence of a memory-matching distractor. Furthermore, the degree of impairment did not differ based on the contents of WM. Put differently, regardless of whether participants were maintaining a perceptually colored disk identical to the singleton distractor, or whether they were simply maintaining a word associated with the color of the distractor, the magnitude of attentional capture was the same. Our results suggest that attentional templates can be generated from conceptual knowledge, in the physical absence of the visual feature.

Testing sensory evidence against mnemonic templates

PubMed Central

Myers, Nicholas E; Rohenkohl, Gustavo; Wyart, Valentin; Woolrich, Mark W; Nobre, Anna C; Stokes, Mark G

2015-01-01

Most perceptual decisions require comparisons between current input and an internal template. Classic studies propose that templates are encoded in sustained activity of sensory neurons. However, stimulus encoding is itself dynamic, tracing a complex trajectory through activity space. Which part of this trajectory is pre-activated to reflect the template? Here we recorded magneto- and electroencephalography during a visual target-detection task, and used pattern analyses to decode template, stimulus, and decision-variable representation. Our findings ran counter to the dominant model of sustained pre-activation. Instead, template information emerged transiently around stimulus onset and quickly subsided. Cross-generalization between stimulus and template coding, indicating a shared neural representation, occurred only briefly. Our results are compatible with the proposal that template representation relies on a matched filter, transforming input into task-appropriate output. This proposal was consistent with a signed difference response at the perceptual decision stage, which can be explained by a simple neural model. DOI: http://dx.doi.org/10.7554/eLife.09000.001 PMID:26653854

Dendritic cell recognition using template matching based on one-dimensional (1D) Fourier descriptors (FD)

NASA Astrophysics Data System (ADS)

Muhd Suberi, Anis Azwani; Wan Zakaria, Wan Nurshazwani; Tomari, Razali; Lau, Mei Xia

2016-07-01

Identification of Dendritic Cell (DC) particularly in the cancer microenvironment is a unique disclosure since fighting tumor from the harnessing immune system has been a novel treatment under investigation. Nowadays, the staining procedure in sorting DC can affect their viability. In this paper, a computer aided system is proposed for automatic classification of DC in peripheral blood mononuclear cell (PBMC) images. Initially, the images undergo a few steps in preprocessing to remove uneven illumination and artifacts around the cells. In segmentation, morphological operators and Canny edge are implemented to isolate the cell shapes and extract the contours. Following that, information from the contours are extracted based on Fourier descriptors, derived from one dimensional (1D) shape signatures. Eventually, cells are classified as DC by comparing template matching (TM) of established template and target images. The results show that the proposed scheme is reliable and effective to recognize DC.

System and method for constructing filters for detecting signals whose frequency content varies with time

DOEpatents

Qian, Shie; Dunham, Mark E.

1996-01-01

A system and method for constructing a bank of filters which detect the presence of signals whose frequency content varies with time. The present invention includes a novel system and method for developing one or more time templates designed to match the received signals of interest and the bank of matched filters use the one or more time templates to detect the received signals. Each matched filter compares the received signal x(t) with a respective, unique time template that has been designed to approximate a form of the signals of interest. The robust time domain template is assumed to be of the order of w(t)=A(t)cos{2.pi..phi.(t)} and the present invention uses the trajectory of a joint time-frequency representation of x(t) as an approximation of the instantaneous frequency function {.phi.'(t). First, numerous data samples of the received signal x(t) are collected. A joint time frequency representation is then applied to represent the signal, preferably using the time frequency distribution series (also known as the Gabor spectrogram). The joint time-frequency transformation represents the analyzed signal energy at time t and frequency .function., P(t,f), which is a three-dimensional plot of time vs. frequency vs. signal energy. Then P(t,f) is reduced to a multivalued function f(t), a two dimensional plot of time vs. frequency, using a thresholding process. Curve fitting steps are then performed on the time/frequency plot, preferably using Levenberg-Marquardt curve fitting techniques, to derive a general instantaneous frequency function .phi.'(t) which best fits the multivalued function f(t), a trajectory of the joint time-frequency domain representation of x(t). Integrating .phi.'(t) along t yields .phi.(t), which is then inserted into the form of the time template equation. A suitable amplitude A(t) is also preferably determined. Once the time template has been determined, one or more filters are developed which each use a version or form of the time template.

Functional Programming with C++ Template Metaprograms

NASA Astrophysics Data System (ADS)

Porkoláb, Zoltán

Template metaprogramming is an emerging new direction of generative programming. With the clever definitions of templates we can force the C++ compiler to execute algorithms at compilation time. Among the application areas of template metaprograms are the expression templates, static interface checking, code optimization with adaption, language embedding and active libraries. However, as template metaprogramming was not an original design goal, the C++ language is not capable of elegant expression of metaprograms. The complicated syntax leads to the creation of code that is hard to write, understand and maintain. Although template metaprogramming has a strong relationship with functional programming, this is not reflected in the language syntax and existing libraries. In this paper we give a short and incomplete introduction to C++ templates and the basics of template metaprogramming. We will enlight the role of template metaprograms, and some important and widely used idioms. We give an overview of the possible application areas as well as debugging and profiling techniques. We suggest a pure functional style programming interface for C++ template metaprograms in the form of embedded Haskell code which is transformed to standard compliant C++ source.

View-Invariant Gait Recognition Through Genetic Template Segmentation

NASA Astrophysics Data System (ADS)

Isaac, Ebenezer R. H. P.; Elias, Susan; Rajagopalan, Srinivasan; Easwarakumar, K. S.

2017-08-01

Template-based model-free approach provides by far the most successful solution to the gait recognition problem in literature. Recent work discusses how isolating the head and leg portion of the template increase the performance of a gait recognition system making it robust against covariates like clothing and carrying conditions. However, most involve a manual definition of the boundaries. The method we propose, the genetic template segmentation (GTS), employs the genetic algorithm to automate the boundary selection process. This method was tested on the GEI, GEnI and AEI templates. GEI seems to exhibit the best result when segmented with our approach. Experimental results depict that our approach significantly outperforms the existing implementations of view-invariant gait recognition.

Application of composite dictionary multi-atom matching in gear fault diagnosis.

PubMed

Cui, Lingli; Kang, Chenhui; Wang, Huaqing; Chen, Peng

2011-01-01

The sparse decomposition based on matching pursuit is an adaptive sparse expression method for signals. This paper proposes an idea concerning a composite dictionary multi-atom matching decomposition and reconstruction algorithm, and the introduction of threshold de-noising in the reconstruction algorithm. Based on the structural characteristics of gear fault signals, a composite dictionary combining the impulse time-frequency dictionary and the Fourier dictionary was constituted, and a genetic algorithm was applied to search for the best matching atom. The analysis results of gear fault simulation signals indicated the effectiveness of the hard threshold, and the impulse or harmonic characteristic components could be separately extracted. Meanwhile, the robustness of the composite dictionary multi-atom matching algorithm at different noise levels was investigated. Aiming at the effects of data lengths on the calculation efficiency of the algorithm, an improved segmented decomposition and reconstruction algorithm was proposed, and the calculation efficiency of the decomposition algorithm was significantly enhanced. In addition it is shown that the multi-atom matching algorithm was superior to the single-atom matching algorithm in both calculation efficiency and algorithm robustness. Finally, the above algorithm was applied to gear fault engineering signals, and achieved good results.

Comparison of photo-matching algorithms commonly used for photographic capture-recapture studies.

PubMed

Matthé, Maximilian; Sannolo, Marco; Winiarski, Kristopher; Spitzen-van der Sluijs, Annemarieke; Goedbloed, Daniel; Steinfartz, Sebastian; Stachow, Ulrich

2017-08-01

Photographic capture-recapture is a valuable tool for obtaining demographic information on wildlife populations due to its noninvasive nature and cost-effectiveness. Recently, several computer-aided photo-matching algorithms have been developed to more efficiently match images of unique individuals in databases with thousands of images. However, the identification accuracy of these algorithms can severely bias estimates of vital rates and population size. Therefore, it is important to understand the performance and limitations of state-of-the-art photo-matching algorithms prior to implementation in capture-recapture studies involving possibly thousands of images. Here, we compared the performance of four photo-matching algorithms; Wild-ID, I3S Pattern+, APHIS, and AmphIdent using multiple amphibian databases of varying image quality. We measured the performance of each algorithm and evaluated the performance in relation to database size and the number of matching images in the database. We found that algorithm performance differed greatly by algorithm and image database, with recognition rates ranging from 100% to 22.6% when limiting the review to the 10 highest ranking images. We found that recognition rate degraded marginally with increased database size and could be improved considerably with a higher number of matching images in the database. In our study, the pixel-based algorithm of AmphIdent exhibited superior recognition rates compared to the other approaches. We recommend carefully evaluating algorithm performance prior to using it to match a complete database. By choosing a suitable matching algorithm, databases of sizes that are unfeasible to match "by eye" can be easily translated to accurate individual capture histories necessary for robust demographic estimates.

Biometric template transformation: a security analysis

NASA Astrophysics Data System (ADS)

Nagar, Abhishek; Nandakumar, Karthik; Jain, Anil K.

2010-01-01

One of the critical steps in designing a secure biometric system is protecting the templates of the users that are stored either in a central database or on smart cards. If a biometric template is compromised, it leads to serious security and privacy threats because unlike passwords, it is not possible for a legitimate user to revoke his biometric identifiers and switch to another set of uncompromised identifiers. One methodology for biometric template protection is the template transformation approach, where the template, consisting of the features extracted from the biometric trait, is transformed using parameters derived from a user specific password or key. Only the transformed template is stored and matching is performed directly in the transformed domain. In this paper, we formally investigate the security strength of template transformation techniques and define six metrics that facilitate a holistic security evaluation. Furthermore, we analyze the security of two wellknown template transformation techniques, namely, Biohashing and cancelable fingerprint templates based on the proposed metrics. Our analysis indicates that both these schemes are vulnerable to intrusion and linkage attacks because it is relatively easy to obtain either a close approximation of the original template (Biohashing) or a pre-image of the transformed template (cancelable fingerprints). We argue that the security strength of template transformation techniques must consider also consider the computational complexity of obtaining a complete pre-image of the transformed template in addition to the complexity of recovering the original biometric template.

A multi-pattern hash-binary hybrid algorithm for URL matching in the HTTP protocol.

PubMed

Zeng, Ping; Tan, Qingping; Meng, Xiankai; Shao, Zeming; Xie, Qinzheng; Yan, Ying; Cao, Wei; Xu, Jianjun

2017-01-01

In this paper, based on our previous multi-pattern uniform resource locator (URL) binary-matching algorithm called HEM, we propose an improved multi-pattern matching algorithm called MH that is based on hash tables and binary tables. The MH algorithm can be applied to the fields of network security, data analysis, load balancing, cloud robotic communications, and so on-all of which require string matching from a fixed starting position. Our approach effectively solves the performance problems of the classical multi-pattern matching algorithms. This paper explores ways to improve string matching performance under the HTTP protocol by using a hash method combined with a binary method that transforms the symbol-space matching problem into a digital-space numerical-size comparison and hashing problem. The MH approach has a fast matching speed, requires little memory, performs better than both the classical algorithms and HEM for matching fields in an HTTP stream, and it has great promise for use in real-world applications.

A multi-pattern hash-binary hybrid algorithm for URL matching in the HTTP protocol

PubMed Central

Tan, Qingping; Meng, Xiankai; Shao, Zeming; Xie, Qinzheng; Yan, Ying; Cao, Wei; Xu, Jianjun

2017-01-01

In this paper, based on our previous multi-pattern uniform resource locator (URL) binary-matching algorithm called HEM, we propose an improved multi-pattern matching algorithm called MH that is based on hash tables and binary tables. The MH algorithm can be applied to the fields of network security, data analysis, load balancing, cloud robotic communications, and so on—all of which require string matching from a fixed starting position. Our approach effectively solves the performance problems of the classical multi-pattern matching algorithms. This paper explores ways to improve string matching performance under the HTTP protocol by using a hash method combined with a binary method that transforms the symbol-space matching problem into a digital-space numerical-size comparison and hashing problem. The MH approach has a fast matching speed, requires little memory, performs better than both the classical algorithms and HEM for matching fields in an HTTP stream, and it has great promise for use in real-world applications. PMID:28399157

A flexible and robust approach for segmenting cell nuclei from 2D microscopy images using supervised learning and template matching

PubMed Central

Chen, Cheng; Wang, Wei; Ozolek, John A.; Rohde, Gustavo K.

2013-01-01

We describe a new supervised learning-based template matching approach for segmenting cell nuclei from microscopy images. The method uses examples selected by a user for building a statistical model which captures the texture and shape variations of the nuclear structures from a given dataset to be segmented. Segmentation of subsequent, unlabeled, images is then performed by finding the model instance that best matches (in the normalized cross correlation sense) local neighborhood in the input image. We demonstrate the application of our method to segmenting nuclei from a variety of imaging modalities, and quantitatively compare our results to several other methods. Quantitative results using both simulated and real image data show that, while certain methods may work well for certain imaging modalities, our software is able to obtain high accuracy across several imaging modalities studied. Results also demonstrate that, relative to several existing methods, the template-based method we propose presents increased robustness in the sense of better handling variations in illumination, variations in texture from different imaging modalities, providing more smooth and accurate segmentation borders, as well as handling better cluttered nuclei. PMID:23568787

Application of Template Matching for Improving Classification of Urban Railroad Point Clouds

PubMed Central

Arastounia, Mostafa; Oude Elberink, Sander

2016-01-01

This study develops an integrated data-driven and model-driven approach (template matching) that clusters the urban railroad point clouds into three classes of rail track, contact cable, and catenary cable. The employed dataset covers 630 m of the Dutch urban railroad corridors in which there are four rail tracks, two contact cables, and two catenary cables. The dataset includes only geometrical information (three dimensional (3D) coordinates of the points) with no intensity data and no RGB data. The obtained results indicate that all objects of interest are successfully classified at the object level with no false positives and no false negatives. The results also show that an average 97.3% precision and an average 97.7% accuracy at the point cloud level are achieved. The high precision and high accuracy of the rail track classification (both greater than 96%) at the point cloud level stems from the great impact of the employed template matching method on excluding the false positives. The cables also achieve quite high average precision (96.8%) and accuracy (98.4%) due to their high sampling and isolated position in the railroad corridor. PMID:27973452

A man-made object detection for underwater TV

NASA Astrophysics Data System (ADS)

Cheng, Binbin; Wang, Wenwu; Chen, Yao

2018-03-01

It is a great challenging task to complete an automatic search of objects underwater. Usually the forward looking sonar is used to find the target, and then the initial identification of the target is completed by the side-scan sonar, and finally the confirmation of the target is accomplished by underwater TV. This paper presents an efficient method for automatic extraction of man-made sensitive targets in underwater TV. Firstly, the image of underwater TV is simplified with taking full advantage of the prior knowledge of the target and the background; then template matching technology is used for target detection; finally the target is confirmed by extracting parallel lines on the target contour. The algorithm is formulated for real-time execution on limited-memory commercial-of-the-shelf platforms and is capable of detection objects in underwater TV.

Robust multiple cue fusion-based high-speed and nonrigid object tracking algorithm for short track speed skating

NASA Astrophysics Data System (ADS)

Liu, Chenguang; Cheng, Heng-Da; Zhang, Yingtao; Wang, Yuxuan; Xian, Min

2016-01-01

This paper presents a methodology for tracking multiple skaters in short track speed skating competitions. Nonrigid skaters move at high speed with severe occlusions happening frequently among them. The camera is panned quickly in order to capture the skaters in a large and dynamic scene. To automatically track the skaters and precisely output their trajectories becomes a challenging task in object tracking. We employ the global rink information to compensate camera motion and obtain the global spatial information of skaters, utilize random forest to fuse multiple cues and predict the blob of each skater, and finally apply a silhouette- and edge-based template-matching and blob-evolving method to labelling pixels to a skater. The effectiveness and robustness of the proposed method are verified through thorough experiments.

Humanoid assessing rehabilitative exercises.

PubMed

Simonov, M; Delconte, G

2015-01-01

This article is part of the Focus Theme of Methods of Information in Medicine on "New Methodologies for Patients Rehabilitation". The article presents the approach in which the rehabilitative exercise prepared by healthcare professional is encoded as formal knowledge and used by humanoid robot to assist patients without involving other care actors. The main objective is the use of humanoids in rehabilitative care. An example is pulmonary rehabilitation in COPD patients. Another goal is the automated judgment functionality to determine how the rehabilitation exercise matches the pre-programmed correct sequence. We use the Aldebaran Robotics' NAO humanoid to set up artificial cognitive application. Pre-programmed NAO induces elderly patient to undertake humanoid-driven rehabilitation exercise, but needs to evaluate the human actions against the correct template. Patient is observed using NAO's eyes. We use the Microsoft Kinect SDK to extract motion path from the humanoid's recorded video. We compare human- and humanoid-operated process sequences by using the Dynamic Time Warping (DTW) and test the prototype. This artificial cognitive software showcases the use of DTW algorithm to enable humanoids to judge in near real-time about the correctness of rehabilitative exercises performed by patients following the robot's indications. One could enable better sustainable rehabilitative care services in remote residential settings by combining intelligent applications piloting humanoids with the DTW pattern matching algorithm applied at run time to compare humanoid- and human-operated process sequences. In turn, it will lower the need of human care.

A deep convolutional neural network approach to single-particle recognition in cryo-electron microscopy.

PubMed

Zhu, Yanan; Ouyang, Qi; Mao, Youdong

2017-07-21

Single-particle cryo-electron microscopy (cryo-EM) has become a mainstream tool for the structural determination of biological macromolecular complexes. However, high-resolution cryo-EM reconstruction often requires hundreds of thousands of single-particle images. Particle extraction from experimental micrographs thus can be laborious and presents a major practical bottleneck in cryo-EM structural determination. Existing computational methods for particle picking often use low-resolution templates for particle matching, making them susceptible to reference-dependent bias. It is critical to develop a highly efficient template-free method for the automatic recognition of particle images from cryo-EM micrographs. We developed a deep learning-based algorithmic framework, DeepEM, for single-particle recognition from noisy cryo-EM micrographs, enabling automated particle picking, selection and verification in an integrated fashion. The kernel of DeepEM is built upon a convolutional neural network (CNN) composed of eight layers, which can be recursively trained to be highly "knowledgeable". Our approach exhibits an improved performance and accuracy when tested on the standard KLH dataset. Application of DeepEM to several challenging experimental cryo-EM datasets demonstrated its ability to avoid the selection of un-wanted particles and non-particles even when true particles contain fewer features. The DeepEM methodology, derived from a deep CNN, allows automated particle extraction from raw cryo-EM micrographs in the absence of a template. It demonstrates an improved performance, objectivity and accuracy. Application of this novel method is expected to free the labor involved in single-particle verification, significantly improving the efficiency of cryo-EM data processing.

A fast template periodogram

NASA Astrophysics Data System (ADS)

Hoffman, John; VanderPlas, Jake; Hartman, Joel; Bakos, Gáspár

2017-09-01

This proceedings contribution presents a novel, non-linear extension to the Lomb-Scargle periodogram that allows periodograms to be generated for arbitrary signal shapes. Such periodograms are already known as "template periodograms" or "periodic matched filters," but current implementations are computationally inefficient. The "fast template periodogram" presented here improves existing techniques by a factor of ˜a few for small test cases (O(10) observations), and over three orders of magnitude for lightcurves containing O(104) observations. The fast template periodogram scales asymptotically as O(HNf log HNf + H4Nf), where H denotes the number of harmonics required to adequately approximate the template and Nf is the number of trial frequencies. Existing implementations scale as O(NobsNf), where Nobs is the number of observations in the lightcurve. An open source Python implementation is available on GitHub.

The Role of Standardized and Study-specific Human Brain Diffusion Tensor Templates in Inter-subject Spatial Normalization

PubMed Central

Zhang, Shengwei; Arfanakis, Konstantinos

2012-01-01

Purpose To investigate the effect of standardized and study-specific human brain diffusion tensor templates on the accuracy of spatial normalization, without ignoring the important roles of data quality and registration algorithm effectiveness. Materials and Methods Two groups of diffusion tensor imaging (DTI) datasets, with and without visible artifacts, were normalized to two standardized diffusion tensor templates (IIT2, ICBM81) as well as study-specific templates, using three registration approaches. The accuracy of inter-subject spatial normalization was compared across templates, using the most effective registration technique for each template and group of data. Results It was demonstrated that, for DTI data with visible artifacts, the study-specific template resulted in significantly higher spatial normalization accuracy than standardized templates. However, for data without visible artifacts, the study-specific template and the standardized template of higher quality (IIT2) resulted in similar normalization accuracy. Conclusion For DTI data with visible artifacts, a carefully constructed study-specific template may achieve higher normalization accuracy than that of standardized templates. However, as DTI data quality improves, a high-quality standardized template may be more advantageous than a study-specific template, since in addition to high normalization accuracy, it provides a standard reference across studies, as well as automated localization/segmentation when accompanied by anatomical labels. PMID:23034880

Selection method of terrain matching area for TERCOM algorithm

NASA Astrophysics Data System (ADS)

Zhang, Qieqie; Zhao, Long

2017-10-01

The performance of terrain aided navigation is closely related to the selection of terrain matching area. The different matching algorithms have different adaptability to terrain. This paper mainly studies the adaptability to terrain of TERCOM algorithm, analyze the relation between terrain feature and terrain characteristic parameters by qualitative and quantitative methods, and then research the relation between matching probability and terrain characteristic parameters by the Monte Carlo method. After that, we propose a selection method of terrain matching area for TERCOM algorithm, and verify the method correctness with real terrain data by simulation experiment. Experimental results show that the matching area obtained by the method in this paper has the good navigation performance and the matching probability of TERCOM algorithm is great than 90%

Film grain synthesis and its application to re-graining

NASA Astrophysics Data System (ADS)

Schallauer, Peter; Mörzinger, Roland

2006-01-01

Digital film restoration and special effects compositing require more and more automatic procedures for movie regraining. Missing or inhomogeneous grain decreases perceived quality. For the purpose of grain synthesis an existing texture synthesis algorithm has been evaluated and optimized. We show that this algorithm can produce synthetic grain which is perceptually similar to a given grain template, which has high spatial and temporal variation and which can be applied to multi-spectral images. Furthermore a re-grain application framework is proposed, which synthesises based on an input grain template artificial grain and composites this together with the original image content. Due to its modular approach this framework supports manual as well as automatic re-graining applications. Two example applications are presented, one for re-graining an entire movie and one for fully automatic re-graining of image regions produced by restoration algorithms. Low computational cost of the proposed algorithms allows application in industrial grade software.

Markerless positional verification using template matching and triangulation of kV images acquired during irradiation for lung tumors treated in breath-hold

NASA Astrophysics Data System (ADS)

Hazelaar, Colien; Dahele, Max; Mostafavi, Hassan; van der Weide, Lineke; Slotman, Ben; Verbakel, Wilko

2018-06-01

Lung tumors treated in breath-hold are subject to inter- and intra-breath-hold variations, which makes tumor position monitoring during each breath-hold important. A markerless technique is desirable, but limited tumor visibility on kV images makes this challenging. We evaluated if template matching  +  triangulation of kV projection images acquired during breath-hold stereotactic treatments could determine 3D tumor position. Band-pass filtering and/or digital tomosynthesis (DTS) were used as image pre-filtering/enhancement techniques. On-board kV images continuously acquired during volumetric modulated arc irradiation of (i) a 3D-printed anthropomorphic thorax phantom with three lung tumors (n  =  6 stationary datasets, n  =  2 gradually moving), and (ii) four patients (13 datasets) were analyzed. 2D reference templates (filtered DRRs) were created from planning CT data. Normalized cross-correlation was used for 2D matching between templates and pre-filtered/enhanced kV images. For 3D verification, each registration was triangulated with multiple previous registrations. Generally applicable image processing/algorithm settings for lung tumors in breath-hold were identified. For the stationary phantom, the interquartile range of the 3D position vector was on average 0.25 mm for 12° DTS  +  band-pass filtering (average detected positions in 2D  =  99.7%, 3D  =  96.1%, and 3D excluding first 12° due to triangulation angle  =  99.9%) compared to 0.81 mm for band-pass filtering only (55.8/52.9/55.0%). For the moving phantom, RMS errors for the lateral/longitudinal/vertical direction after 12° DTS  +  band-pass filtering were 1.5/0.4/1.1 mm and 2.2/0.3/3.2 mm. For the clinical data, 2D position was determined for at least 93% of each dataset and 3D position excluding first 12° for at least 82% of each dataset using 12° DTS  +  band-pass filtering. Template matching  +  triangulation using DTS  +  band-pass filtered images could accurately determine the position of stationary lung tumors. However, triangulation was less accurate/reliable for targets with continuous, gradual displacement in the lateral and vertical directions. This technique is therefore currently most suited to detect/monitor offsets occurring between initial setup and the start of treatment, inter-breath-hold variations, and tumors with predominantly longitudinal motion.

Framework for adaptive multiscale analysis of nonhomogeneous point processes.

PubMed

Helgason, Hannes; Bartroff, Jay; Abry, Patrice

2011-01-01

We develop the methodology for hypothesis testing and model selection in nonhomogeneous Poisson processes, with an eye toward the application of modeling and variability detection in heart beat data. Modeling the process' non-constant rate function using templates of simple basis functions, we develop the generalized likelihood ratio statistic for a given template and a multiple testing scheme to model-select from a family of templates. A dynamic programming algorithm inspired by network flows is used to compute the maximum likelihood template in a multiscale manner. In a numerical example, the proposed procedure is nearly as powerful as the super-optimal procedures that know the true template size and true partition, respectively. Extensions to general history-dependent point processes is discussed.

Seismic Characterization of the Blue Mountain Geothermal Site

NASA Astrophysics Data System (ADS)

Templeton, D. C.; Matzel, E.; Cladouhos, T. T.

2017-12-01

All fluid injection activities have the potential to induce earthquakes by modifying the state of stress in the subsurface. In geothermal areas, small microearthquakes can be a beneficial outcome of these stress perturbations by providing direct subsurface information that can be used to better understand and manage the underground reservoir. These events can delineate the active portions of the subsurface that have slipped in response to pore fluid pressure changes or temperature changes during and after fluid injection. Here we investigate the seismic activity within the Blue Mountain Geothermal Power Plant located in Humboldt County, Nevada between December 2015 to May 2016. We compare the effectiveness of direct spatial-temporal cross-correlation templates with Matched Field Processing (MFP) derived templates and compare these results with earthquake detection results from a traditional STA/LTA algorithm. Preliminary results show significant clustering of microearthquakes, most probably influenced by plant operations. The significant increase in data availability that advanced earthquake detection methods can provide improves the statistical analyses of induced seismicity sequences, reveal critical information about the ongoing evolution of the subsurface reservoir, and better informs the construction of models for hazard assessments. This work performed under the auspices of the U.S. Department of Energy by Lawrence Livermore National Laboratory under Contract DE-AC52-07NA27344.

Improved artificial bee colony algorithm based gravity matching navigation method.

PubMed

Gao, Wei; Zhao, Bo; Zhou, Guang Tao; Wang, Qiu Ying; Yu, Chun Yang

2014-07-18

Gravity matching navigation algorithm is one of the key technologies for gravity aided inertial navigation systems. With the development of intelligent algorithms, the powerful search ability of the Artificial Bee Colony (ABC) algorithm makes it possible to be applied to the gravity matching navigation field. However, existing search mechanisms of basic ABC algorithms cannot meet the need for high accuracy in gravity aided navigation. Firstly, proper modifications are proposed to improve the performance of the basic ABC algorithm. Secondly, a new search mechanism is presented in this paper which is based on an improved ABC algorithm using external speed information. At last, modified Hausdorff distance is introduced to screen the possible matching results. Both simulations and ocean experiments verify the feasibility of the method, and results show that the matching rate of the method is high enough to obtain a precise matching position.

Improved Artificial Bee Colony Algorithm Based Gravity Matching Navigation Method

PubMed Central

Gao, Wei; Zhao, Bo; Zhou, Guang Tao; Wang, Qiu Ying; Yu, Chun Yang

2014-01-01

Gravity matching navigation algorithm is one of the key technologies for gravity aided inertial navigation systems. With the development of intelligent algorithms, the powerful search ability of the Artificial Bee Colony (ABC) algorithm makes it possible to be applied to the gravity matching navigation field. However, existing search mechanisms of basic ABC algorithms cannot meet the need for high accuracy in gravity aided navigation. Firstly, proper modifications are proposed to improve the performance of the basic ABC algorithm. Secondly, a new search mechanism is presented in this paper which is based on an improved ABC algorithm using external speed information. At last, modified Hausdorff distance is introduced to screen the possible matching results. Both simulations and ocean experiments verify the feasibility of the method, and results show that the matching rate of the method is high enough to obtain a precise matching position. PMID:25046019

Research on sparse feature matching of improved RANSAC algorithm

NASA Astrophysics Data System (ADS)

Kong, Xiangsi; Zhao, Xian

2018-04-01

In this paper, a sparse feature matching method based on modified RANSAC algorithm is proposed to improve the precision and speed. Firstly, the feature points of the images are extracted using the SIFT algorithm. Then, the image pair is matched roughly by generating SIFT feature descriptor. At last, the precision of image matching is optimized by the modified RANSAC algorithm,. The RANSAC algorithm is improved from three aspects: instead of the homography matrix, this paper uses the fundamental matrix generated by the 8 point algorithm as the model; the sample is selected by a random block selecting method, which ensures the uniform distribution and the accuracy; adds sequential probability ratio test(SPRT) on the basis of standard RANSAC, which cut down the overall running time of the algorithm. The experimental results show that this method can not only get higher matching accuracy, but also greatly reduce the computation and improve the matching speed.

The Role of Color in Search Templates for Real-world Target Objects.

PubMed

Nako, Rebecca; Smith, Tim J; Eimer, Martin

2016-11-01

During visual search, target representations (attentional templates) control the allocation of attention to template-matching objects. The activation of new attentional templates can be prompted by verbal or pictorial target specifications. We measured the N2pc component of the ERP as a temporal marker of attentional target selection to determine the role of color signals in search templates for real-world search target objects that are set up in response to word or picture cues. On each trial run, a word cue (e.g., "apple") was followed by three search displays that contained the cued target object among three distractors. The selection of the first target was based on the word cue only, whereas selection of the two subsequent targets could be controlled by templates set up after the first visual presentation of the target (picture cue). In different trial runs, search displays either contained objects in their natural colors or monochromatic objects. These two display types were presented in different blocks (Experiment 1) or in random order within each block (Experiment 2). RTs were faster, and target N2pc components emerged earlier for the second and third display of each trial run relative to the first display, demonstrating that pictures are more effective than word cues in guiding search. N2pc components were triggered more rapidly for targets in the second and third display in trial runs with colored displays. This demonstrates that when visual target attributes are fully specified by picture cues, the additional presence of color signals in target templates facilitates the speed with which attention is allocated to template-matching objects. No such selection benefits for colored targets were found when search templates were set up in response to word cues. Experiment 2 showed that color templates activated by word cues can even impair the attentional selection of noncolored targets. Results provide new insights into the status of color during the guidance of visual search for real-world target objects. Color is a powerful guiding feature when the precise visual properties of these objects are known but seems to be less important when search targets are specified by word cues.

NoRMCorre: An online algorithm for piecewise rigid motion correction of calcium imaging data.

PubMed

Pnevmatikakis, Eftychios A; Giovannucci, Andrea

2017-11-01

Motion correction is a challenging pre-processing problem that arises early in the analysis pipeline of calcium imaging data sequences. The motion artifacts in two-photon microscopy recordings can be non-rigid, arising from the finite time of raster scanning and non-uniform deformations of the brain medium. We introduce an algorithm for fast Non-Rigid Motion Correction (NoRMCorre) based on template matching. NoRMCorre operates by splitting the field of view (FOV) into overlapping spatial patches along all directions. The patches are registered at a sub-pixel resolution for rigid translation against a regularly updated template. The estimated alignments are subsequently up-sampled to create a smooth motion field for each frame that can efficiently approximate non-rigid artifacts in a piecewise-rigid manner. Existing approaches either do not scale well in terms of computational performance or are targeted to non-rigid artifacts arising just from the finite speed of raster scanning, and thus cannot correct for non-rigid motion observable in datasets from a large FOV. NoRMCorre can be run in an online mode resulting in comparable to or even faster than real time motion registration of streaming data. We evaluate its performance with simple yet intuitive metrics and compare against other non-rigid registration methods on simulated data and in vivo two-photon calcium imaging datasets. Open source Matlab and Python code is also made available. The proposed method and accompanying code can be useful for solving large scale image registration problems in calcium imaging, especially in the presence of non-rigid deformations. Copyright © 2017 The Author(s). Published by Elsevier B.V. All rights reserved.

Automated Threshold Selection for Template-Based Sonar Target Detection

DTIC Science & Technology

2017-08-01

test based on the distribution of the matched filter correlations. From the matched filter output we evaluate target sized areas and surrounding...synthetic aperture sonar data that were part of the evaluation . Figure 3 shows a nearly uniform seafloor. Figure 4 is more complex, with

A Nearest Neighbor Classifier Employing Critical Boundary Vectors for Efficient On-Chip Template Reduction.

PubMed

Xia, Wenjun; Mita, Yoshio; Shibata, Tadashi

2016-05-01

Aiming at efficient data condensation and improving accuracy, this paper presents a hardware-friendly template reduction (TR) method for the nearest neighbor (NN) classifiers by introducing the concept of critical boundary vectors. A hardware system is also implemented to demonstrate the feasibility of using an field-programmable gate array (FPGA) to accelerate the proposed method. Initially, k -means centers are used as substitutes for the entire template set. Then, to enhance the classification performance, critical boundary vectors are selected by a novel learning algorithm, which is completed within a single iteration. Moreover, to remove noisy boundary vectors that can mislead the classification in a generalized manner, a global categorization scheme has been explored and applied to the algorithm. The global characterization automatically categorizes each classification problem and rapidly selects the boundary vectors according to the nature of the problem. Finally, only critical boundary vectors and k -means centers are used as the new template set for classification. Experimental results for 24 data sets show that the proposed algorithm can effectively reduce the number of template vectors for classification with a high learning speed. At the same time, it improves the accuracy by an average of 2.17% compared with the traditional NN classifiers and also shows greater accuracy than seven other TR methods. We have shown the feasibility of using a proof-of-concept FPGA system of 256 64-D vectors to accelerate the proposed method on hardware. At a 50-MHz clock frequency, the proposed system achieves a 3.86 times higher learning speed than on a 3.4-GHz PC, while consuming only 1% of the power of that used by the PC.

Rapid and Robust Cross-Correlation-Based Seismic Signal Identification Using an Approximate Nearest Neighbor Method

DOE PAGES

Tibi, Rigobert; Young, Christopher; Gonzales, Antonio; ...

2017-07-04

The matched filtering technique that uses the cross correlation of a waveform of interest with archived signals from a template library has proven to be a powerful tool for detecting events in regions with repeating seismicity. However, waveform correlation is computationally expensive and therefore impractical for large template sets unless dedicated distributed computing hardware and software are used. In this paper, we introduce an approximate nearest neighbor (ANN) approach that enables the use of very large template libraries for waveform correlation. Our method begins with a projection into a reduced dimensionality space, based on correlation with a randomized subset ofmore » the full template archive. Searching for a specified number of nearest neighbors for a query waveform is accomplished by iteratively comparing it with the neighbors of its immediate neighbors. We used the approach to search for matches to each of ~2300 analyst-reviewed signal detections reported in May 2010 for the International Monitoring System station MKAR. The template library in this case consists of a data set of more than 200,000 analyst-reviewed signal detections for the same station from February 2002 to July 2016 (excluding May 2010). Of these signal detections, 73% are teleseismic first P and 17% regional phases (Pn, Pg, Sn, and Lg). Finally, the analyses performed on a standard desktop computer show that the proposed ANN approach performs a search of the large template libraries about 25 times faster than the standard full linear search and achieves recall rates greater than 80%, with the recall rate increasing for higher correlation thresholds.« less

Rapid and Robust Cross-Correlation-Based Seismic Signal Identification Using an Approximate Nearest Neighbor Method

DOE Office of Scientific and Technical Information (OSTI.GOV)

Tibi, Rigobert; Young, Christopher; Gonzales, Antonio

The matched filtering technique that uses the cross correlation of a waveform of interest with archived signals from a template library has proven to be a powerful tool for detecting events in regions with repeating seismicity. However, waveform correlation is computationally expensive and therefore impractical for large template sets unless dedicated distributed computing hardware and software are used. In this paper, we introduce an approximate nearest neighbor (ANN) approach that enables the use of very large template libraries for waveform correlation. Our method begins with a projection into a reduced dimensionality space, based on correlation with a randomized subset ofmore » the full template archive. Searching for a specified number of nearest neighbors for a query waveform is accomplished by iteratively comparing it with the neighbors of its immediate neighbors. We used the approach to search for matches to each of ~2300 analyst-reviewed signal detections reported in May 2010 for the International Monitoring System station MKAR. The template library in this case consists of a data set of more than 200,000 analyst-reviewed signal detections for the same station from February 2002 to July 2016 (excluding May 2010). Of these signal detections, 73% are teleseismic first P and 17% regional phases (Pn, Pg, Sn, and Lg). Finally, the analyses performed on a standard desktop computer show that the proposed ANN approach performs a search of the large template libraries about 25 times faster than the standard full linear search and achieves recall rates greater than 80%, with the recall rate increasing for higher correlation thresholds.« less

Automatic tracking of arbitrarily shaped implanted markers in kilovoltage projection images: A feasibility study

PubMed Central

Regmi, Rajesh; Lovelock, D. Michael; Hunt, Margie; Zhang, Pengpeng; Pham, Hai; Xiong, Jianping; Yorke, Ellen D.; Goodman, Karyn A.; Rimner, Andreas; Mostafavi, Hassan; Mageras, Gig S.

2014-01-01

Purpose: Certain types of commonly used fiducial markers take on irregular shapes upon implantation in soft tissue. This poses a challenge for methods that assume a predefined shape of markers when automatically tracking such markers in kilovoltage (kV) radiographs. The authors have developed a method of automatically tracking regularly and irregularly shaped markers using kV projection images and assessed its potential for detecting intrafractional target motion during rotational treatment. Methods: Template-based matching used a normalized cross-correlation with simplex minimization. Templates were created from computed tomography (CT) images for phantom studies and from end-expiration breath-hold planning CT for patient studies. The kV images were processed using a Sobel filter to enhance marker visibility. To correct for changes in intermarker relative positions between simulation and treatment that can introduce errors in automatic matching, marker offsets in three dimensions were manually determined from an approximately orthogonal pair of kV images. Two studies in anthropomorphic phantom were carried out, one using a gold cylindrical marker representing regular shape, another using a Visicoil marker representing irregular shape. Automatic matching of templates to cone beam CT (CBCT) projection images was performed to known marker positions in phantom. In patient data, automatic matching was compared to manual matching as an approximate ground truth. Positional discrepancy between automatic and manual matching of less than 2 mm was assumed as the criterion for successful tracking. Tracking success rates were examined in kV projection images from 22 CBCT scans of four pancreas, six gastroesophageal junction, and one lung cancer patients. Each patient had at least one irregularly shaped radiopaque marker implanted in or near the tumor. In addition, automatic tracking was tested in intrafraction kV images of three lung cancer patients with irregularly shaped markers during 11 volumetric modulated arc treatments. Purpose-built software developed at our institution was used to create marker templates and track the markers embedded in kV images. Results: Phantom studies showed mean ± standard deviation measurement uncertainty of automatic registration to be 0.14 ± 0.07 mm and 0.17 ± 0.08 mm for Visicoil and gold cylindrical markers, respectively. The mean success rate of automatic tracking with CBCT projections (11 frames per second, fps) of pancreas, gastroesophageal junction, and lung cancer patients was 100%, 99.1% (range 98%–100%), and 100%, respectively. With intrafraction images (approx. 0.2 fps) of lung cancer patients, the success rate was 98.2% (range 97%–100%), and 94.3% (range 93%–97%) using templates from 1.25 mm and 2.5 mm slice spacing CT scans, respectively. Correction of intermarker relative position was found to improve the success rate in two out of eight patients analyzed. Conclusions: The proposed method can track arbitrary marker shapes in kV images using templates generated from a breath-hold CT acquired at simulation. The studies indicate its feasibility for tracking tumor motion during rotational treatment. Investigation of the causes of misregistration suggests that its rate of incidence can be reduced with higher frequency of image acquisition, templates made from smaller CT slice spacing, and correction of changes in intermarker relative positions when they occur. PMID:24989384

Automatic tracking of arbitrarily shaped implanted markers in kilovoltage projection images: A feasibility study

DOE Office of Scientific and Technical Information (OSTI.GOV)

Regmi, Rajesh; Lovelock, D. Michael; Hunt, Margie

Purpose: Certain types of commonly used fiducial markers take on irregular shapes upon implantation in soft tissue. This poses a challenge for methods that assume a predefined shape of markers when automatically tracking such markers in kilovoltage (kV) radiographs. The authors have developed a method of automatically tracking regularly and irregularly shaped markers using kV projection images and assessed its potential for detecting intrafractional target motion during rotational treatment. Methods: Template-based matching used a normalized cross-correlation with simplex minimization. Templates were created from computed tomography (CT) images for phantom studies and from end-expiration breath-hold planning CT for patient studies. Themore » kV images were processed using a Sobel filter to enhance marker visibility. To correct for changes in intermarker relative positions between simulation and treatment that can introduce errors in automatic matching, marker offsets in three dimensions were manually determined from an approximately orthogonal pair of kV images. Two studies in anthropomorphic phantom were carried out, one using a gold cylindrical marker representing regular shape, another using a Visicoil marker representing irregular shape. Automatic matching of templates to cone beam CT (CBCT) projection images was performed to known marker positions in phantom. In patient data, automatic matching was compared to manual matching as an approximate ground truth. Positional discrepancy between automatic and manual matching of less than 2 mm was assumed as the criterion for successful tracking. Tracking success rates were examined in kV projection images from 22 CBCT scans of four pancreas, six gastroesophageal junction, and one lung cancer patients. Each patient had at least one irregularly shaped radiopaque marker implanted in or near the tumor. In addition, automatic tracking was tested in intrafraction kV images of three lung cancer patients with irregularly shaped markers during 11 volumetric modulated arc treatments. Purpose-built software developed at our institution was used to create marker templates and track the markers embedded in kV images. Results: Phantom studies showed mean ± standard deviation measurement uncertainty of automatic registration to be 0.14 ± 0.07 mm and 0.17 ± 0.08 mm for Visicoil and gold cylindrical markers, respectively. The mean success rate of automatic tracking with CBCT projections (11 frames per second, fps) of pancreas, gastroesophageal junction, and lung cancer patients was 100%, 99.1% (range 98%–100%), and 100%, respectively. With intrafraction images (approx. 0.2 fps) of lung cancer patients, the success rate was 98.2% (range 97%–100%), and 94.3% (range 93%–97%) using templates from 1.25 mm and 2.5 mm slice spacing CT scans, respectively. Correction of intermarker relative position was found to improve the success rate in two out of eight patients analyzed. Conclusions: The proposed method can track arbitrary marker shapes in kV images using templates generated from a breath-hold CT acquired at simulation. The studies indicate its feasibility for tracking tumor motion during rotational treatment. Investigation of the causes of misregistration suggests that its rate of incidence can be reduced with higher frequency of image acquisition, templates made from smaller CT slice spacing, and correction of changes in intermarker relative positions when they occur.« less

A collision detection algorithm for telerobotic arms

NASA Technical Reports Server (NTRS)

Tran, Doan Minh; Bartholomew, Maureen Obrien

1991-01-01

The telerobotic manipulator's collision detection algorithm is described. Its applied structural model of the world environment and template representation of objects is evaluated. Functional issues that are required for the manipulator to operate in a more complex and realistic environment are discussed.

A coarse to fine minutiae-based latent palmprint matching.

PubMed

Liu, Eryun; Jain, Anil K; Tian, Jie

2013-10-01

With the availability of live-scan palmprint technology, high resolution palmprint recognition has started to receive significant attention in forensics and law enforcement. In forensic applications, latent palmprints provide critical evidence as it is estimated that about 30 percent of the latents recovered at crime scenes are those of palms. Most of the available high-resolution palmprint matching algorithms essentially follow the minutiae-based fingerprint matching strategy. Considering the large number of minutiae (about 1,000 minutiae in a full palmprint compared to about 100 minutiae in a rolled fingerprint) and large area of foreground region in full palmprints, novel strategies need to be developed for efficient and robust latent palmprint matching. In this paper, a coarse to fine matching strategy based on minutiae clustering and minutiae match propagation is designed specifically for palmprint matching. To deal with the large number of minutiae, a local feature-based minutiae clustering algorithm is designed to cluster minutiae into several groups such that minutiae belonging to the same group have similar local characteristics. The coarse matching is then performed within each cluster to establish initial minutiae correspondences between two palmprints. Starting with each initial correspondence, a minutiae match propagation algorithm searches for mated minutiae in the full palmprint. The proposed palmprint matching algorithm has been evaluated on a latent-to-full palmprint database consisting of 446 latents and 12,489 background full prints. The matching results show a rank-1 identification accuracy of 79.4 percent, which is significantly higher than the 60.8 percent identification accuracy of a state-of-the-art latent palmprint matching algorithm on the same latent database. The average computation time of our algorithm for a single latent-to-full match is about 141 ms for genuine match and 50 ms for impostor match, on a Windows XP desktop system with 2.2-GHz CPU and 1.00-GB RAM. The computation time of our algorithm is an order of magnitude faster than a previously published state-of-the-art-algorithm.

Geomagnetic matching navigation algorithm based on robust estimation

NASA Astrophysics Data System (ADS)

Xie, Weinan; Huang, Liping; Qu, Zhenshen; Wang, Zhenhuan

2017-08-01

The outliers in the geomagnetic survey data seriously affect the precision of the geomagnetic matching navigation and badly disrupt its reliability. A novel algorithm which can eliminate the outliers influence is investigated in this paper. First, the weight function is designed and its principle of the robust estimation is introduced. By combining the relation equation between the matching trajectory and the reference trajectory with the Taylor series expansion for geomagnetic information, a mathematical expression of the longitude, latitude and heading errors is acquired. The robust target function is obtained by the weight function and the mathematical expression. Then the geomagnetic matching problem is converted to the solutions of nonlinear equations. Finally, Newton iteration is applied to implement the novel algorithm. Simulation results show that the matching error of the novel algorithm is decreased to 7.75% compared to the conventional mean square difference (MSD) algorithm, and is decreased to 18.39% to the conventional iterative contour matching algorithm when the outlier is 40nT. Meanwhile, the position error of the novel algorithm is 0.017° while the other two algorithms fail to match when the outlier is 400nT.

A distributed-memory approximation algorithm for maximum weight perfect bipartite matching

DOE Office of Scientific and Technical Information (OSTI.GOV)

Azad, Ariful; Buluc, Aydin; Li, Xiaoye S.

We design and implement an efficient parallel approximation algorithm for the problem of maximum weight perfect matching in bipartite graphs, i.e. the problem of finding a set of non-adjacent edges that covers all vertices and has maximum weight. This problem differs from the maximum weight matching problem, for which scalable approximation algorithms are known. It is primarily motivated by finding good pivots in scalable sparse direct solvers before factorization where sequential implementations of maximum weight perfect matching algorithms, such as those available in MC64, are widely used due to the lack of scalable alternatives. To overcome this limitation, we proposemore » a fully parallel distributed memory algorithm that first generates a perfect matching and then searches for weightaugmenting cycles of length four in parallel and iteratively augments the matching with a vertex disjoint set of such cycles. For most practical problems the weights of the perfect matchings generated by our algorithm are very close to the optimum. An efficient implementation of the algorithm scales up to 256 nodes (17,408 cores) on a Cray XC40 supercomputer and can solve instances that are too large to be handled by a single node using the sequential algorithm.« less

Automated robust registration of grossly misregistered whole-slide images with varying stains

NASA Astrophysics Data System (ADS)

Litjens, G.; Safferling, K.; Grabe, N.

2016-03-01

Cancer diagnosis and pharmaceutical research increasingly depend on the accurate quantification of cancer biomarkers. Identification of biomarkers is usually performed through immunohistochemical staining of cancer sections on glass slides. However, combination of multiple biomarkers from a wide variety of immunohistochemically stained slides is a tedious process in traditional histopathology due to the switching of glass slides and re-identification of regions of interest by pathologists. Digital pathology now allows us to apply image registration algorithms to digitized whole-slides to align the differing immunohistochemical stains automatically. However, registration algorithms need to be robust to changes in color due to differing stains and severe changes in tissue content between slides. In this work we developed a robust registration methodology to allow for fast coarse alignment of multiple immunohistochemical stains to the base hematyoxylin and eosin stained image. We applied HSD color model conversion to obtain a less stain color dependent representation of the whole-slide images. Subsequently, optical density thresholding and connected component analysis were used to identify the relevant regions for registration. Template matching using normalized mutual information was applied to provide initial translation and rotation parameters, after which a cost function-driven affine registration was performed. The algorithm was validated using 40 slides from 10 prostate cancer patients, with landmark registration error as a metric. Median landmark registration error was around 180 microns, which indicates performance is adequate for practical application. None of the registrations failed, indicating the robustness of the algorithm.

Efficient Approximation Algorithms for Weighted $b$-Matching

DOE Office of Scientific and Technical Information (OSTI.GOV)

Khan, Arif; Pothen, Alex; Mostofa Ali Patwary, Md.

2016-01-01

We describe a half-approximation algorithm, b-Suitor, for computing a b-Matching of maximum weight in a graph with weights on the edges. b-Matching is a generalization of the well-known Matching problem in graphs, where the objective is to choose a subset of M edges in the graph such that at most a specified number b(v) of edges in M are incident on each vertex v. Subject to this restriction we maximize the sum of the weights of the edges in M. We prove that the b-Suitor algorithm computes the same b-Matching as the one obtained by the greedy algorithm for themore » problem. We implement the algorithm on serial and shared-memory parallel processors, and compare its performance against a collection of approximation algorithms that have been proposed for the Matching problem. Our results show that the b-Suitor algorithm outperforms the Greedy and Locally Dominant edge algorithms by one to two orders of magnitude on a serial processor. The b-Suitor algorithm has a high degree of concurrency, and it scales well up to 240 threads on a shared memory multiprocessor. The b-Suitor algorithm outperforms the Locally Dominant edge algorithm by a factor of fourteen on 16 cores of an Intel Xeon multiprocessor.« less

Analysis and improvement of the quantum image matching

NASA Astrophysics Data System (ADS)

Dang, Yijie; Jiang, Nan; Hu, Hao; Zhang, Wenyin

2017-11-01

We investigate the quantum image matching algorithm proposed by Jiang et al. (Quantum Inf Process 15(9):3543-3572, 2016). Although the complexity of this algorithm is much better than the classical exhaustive algorithm, there may be an error in it: After matching the area between two images, only the pixel at the upper left corner of the matched area played part in following steps. That is to say, the paper only matched one pixel, instead of an area. If more than one pixels in the big image are the same as the one at the upper left corner of the small image, the algorithm will randomly measure one of them, which causes the error. In this paper, an improved version is presented which takes full advantage of the whole matched area to locate a small image in a big image. The theoretical analysis indicates that the network complexity is higher than the previous algorithm, but it is still far lower than the classical algorithm. Hence, this algorithm is still efficient.

Minutiae Matching with Privacy Protection Based on the Combination of Garbled Circuit and Homomorphic Encryption

PubMed Central

Li, Mengxing; Zhao, Jian; Yang, Mei; Kang, Lijun; Wu, Lili

2014-01-01

Biometrics plays an important role in authentication applications since they are strongly linked to holders. With an increasing growth of e-commerce and e-government, one can expect that biometric-based authentication systems are possibly deployed over the open networks in the near future. However, due to its openness, the Internet poses a great challenge to the security and privacy of biometric authentication. Biometric data cannot be revoked, so it is of paramount importance that biometric data should be handled in a secure way. In this paper we present a scheme achieving privacy-preserving fingerprint authentication between two parties, in which fingerprint minutiae matching algorithm is completed in the encrypted domain. To improve the efficiency, we exploit homomorphic encryption as well as garbled circuits to design the protocol. Our goal is to provide protection for the security of template in storage and data privacy of two parties in transaction. The experimental results show that the proposed authentication protocol runs efficiently. Therefore, the protocol can run over open networks and help to alleviate the concerns on security and privacy of biometric applications over the open networks. PMID:24711729

Minutiae matching with privacy protection based on the combination of garbled circuit and homomorphic encryption.

PubMed

Li, Mengxing; Feng, Quan; Zhao, Jian; Yang, Mei; Kang, Lijun; Wu, Lili

2014-01-01

Biometrics plays an important role in authentication applications since they are strongly linked to holders. With an increasing growth of e-commerce and e-government, one can expect that biometric-based authentication systems are possibly deployed over the open networks in the near future. However, due to its openness, the Internet poses a great challenge to the security and privacy of biometric authentication. Biometric data cannot be revoked, so it is of paramount importance that biometric data should be handled in a secure way. In this paper we present a scheme achieving privacy-preserving fingerprint authentication between two parties, in which fingerprint minutiae matching algorithm is completed in the encrypted domain. To improve the efficiency, we exploit homomorphic encryption as well as garbled circuits to design the protocol. Our goal is to provide protection for the security of template in storage and data privacy of two parties in transaction. The experimental results show that the proposed authentication protocol runs efficiently. Therefore, the protocol can run over open networks and help to alleviate the concerns on security and privacy of biometric applications over the open networks.

Separating Gravitational Wave Signals from Instrument Artifacts

NASA Technical Reports Server (NTRS)

Littenberg, Tyson B.; Cornish, Neil J.

2010-01-01

Central to the gravitational wave detection problem is the challenge of separating features in the data produced by astrophysical sources from features produced by the detector. Matched filtering provides an optimal solution for Gaussian noise, but in practice, transient noise excursions or "glitches" complicate the analysis. Detector diagnostics and coincidence tests can be used to veto many glitches which may otherwise be misinterpreted as gravitational wave signals. The glitches that remain can lead to long tails in the matched filter search statistics and drive up the detection threshold. Here we describe a Bayesian approach that incorporates a more realistic model for the instrument noise allowing for fluctuating noise levels that vary independently across frequency bands, and deterministic "glitch fitting" using wavelets as "glitch templates", the number of which is determined by a trans-dimensional Markov chain Monte Carlo algorithm. We demonstrate the method's effectiveness on simulated data containing low amplitude gravitational wave signals from inspiraling binary black hole systems, and simulated non-stationary and non-Gaussian noise comprised of a Gaussian component with the standard LIGO/Virgo spectrum, and injected glitches of various amplitude, prevalence, and variety. Glitch fitting allows us to detect significantly weaker signals than standard techniques.

Synthetic aperture radar target detection, feature extraction, and image formation techniques

NASA Technical Reports Server (NTRS)

Li, Jian

1994-01-01

This report presents new algorithms for target detection, feature extraction, and image formation with the synthetic aperture radar (SAR) technology. For target detection, we consider target detection with SAR and coherent subtraction. We also study how the image false alarm rates are related to the target template false alarm rates when target templates are used for target detection. For feature extraction from SAR images, we present a computationally efficient eigenstructure-based 2D-MODE algorithm for two-dimensional frequency estimation. For SAR image formation, we present a robust parametric data model for estimating high resolution range signatures of radar targets and for forming high resolution SAR images.

Shedding light on some possible remedies against watermark desynchronization: a case study

NASA Astrophysics Data System (ADS)

Barni, Mauro

2005-03-01

Watermark de-synchronization is perhaps the most dangerous attack against the great majority of watermarking systems proposed so far. Exhaustive search and template matching are two of the most popular solution against it, however several doubts exist about their effectiveness. As a matter of fact, a controversial point in digital watermarking is whether these techniques are of any help to cope with watermark de-synchronization introduced by geometric attacks. On one side, watermark synchronization through exhaustive search dramatically increases the false detection probability. On the other side, for the template matching approach the probability of a synchronization error must be taken into account, thus deteriorating significantly the performance of the system. It is the scope of this paper to shed some light on the above points. To do so we focus on a very simple case study, whereby we show that as long as the size of the search space (the cardinality of the geometric attack) increases polynomially with the length of the to-be-marked host feature sequence, both methods provide an effective solution to the de-synchronization problem. Interestingly, and rather surprisingly, we also show that Exhaustive Search Detection (ESD) always outperforms Template Matching Detection (TMD), though the general behavior of the two schemes is rather similar.

Dense Matching Comparison Between Census and a Convolutional Neural Network Algorithm for Plant Reconstruction

NASA Astrophysics Data System (ADS)

Xia, Y.; Tian, J.; d'Angelo, P.; Reinartz, P.

2018-05-01

3D reconstruction of plants is hard to implement, as the complex leaf distribution highly increases the difficulty level in dense matching. Semi-Global Matching has been successfully applied to recover the depth information of a scene, but may perform variably when different matching cost algorithms are used. In this paper two matching cost computation algorithms, Census transform and an algorithm using a convolutional neural network, are tested for plant reconstruction based on Semi-Global Matching. High resolution close-range photogrammetric images from a handheld camera are used for the experiment. The disparity maps generated based on the two selected matching cost methods are comparable with acceptable quality, which shows the good performance of Census and the potential of neural networks to improve the dense matching.

Vehicle detection and orientation estimation using the radon transform

NASA Astrophysics Data System (ADS)

Pelapur, Rengarajan; Bunyak, Filiz; Palaniappan, Kannappan; Seetharaman, Gunasekaran

2013-05-01

Determining the location and orientation of vehicles in satellite and airborne imagery is a challenging task given the density of cars and other vehicles and complexity of the environment in urban scenes almost anywhere in the world. We have developed a robust and accurate method for detecting vehicles using a template-based directional chamfer matching, combined with vehicle orientation estimation based on a refined segmentation, followed by a Radon transform based profile variance peak analysis approach. The same algorithm was applied to both high resolution satellite imagery and wide area aerial imagery and initial results show robustness to illumination changes and geometric appearance distortions. Nearly 80% of the orientation angle estimates for 1585 vehicles across both satellite and aerial imagery were accurate to within 15? of the ground truth. In the case of satellite imagery alone, nearly 90% of the objects have an estimated error within +/-1.0° of the ground truth.

Vision based object pose estimation for mobile robots

NASA Technical Reports Server (NTRS)

Wu, Annie; Bidlack, Clint; Katkere, Arun; Feague, Roy; Weymouth, Terry

1994-01-01

Mobile robot navigation using visual sensors requires that a robot be able to detect landmarks and obtain pose information from a camera image. This paper presents a vision system for finding man-made markers of known size and calculating the pose of these markers. The algorithm detects and identifies the markers using a weighted pattern matching template. Geometric constraints are then used to calculate the position of the markers relative to the robot. The selection of geometric constraints comes from the typical pose of most man-made signs, such as the sign standing vertical and the dimensions of known size. This system has been tested successfully on a wide range of real images. Marker detection is reliable, even in cluttered environments, and under certain marker orientations, estimation of the orientation has proven accurate to within 2 degrees, and distance estimation to within 0.3 meters.

Hybrid petacomputing meets cosmology: The Roadrunner Universe project

NASA Astrophysics Data System (ADS)

Habib, Salman; Pope, Adrian; Lukić, Zarija; Daniel, David; Fasel, Patricia; Desai, Nehal; Heitmann, Katrin; Hsu, Chung-Hsing; Ankeny, Lee; Mark, Graham; Bhattacharya, Suman; Ahrens, James

2009-07-01

The target of the Roadrunner Universe project at Los Alamos National Laboratory is a set of very large cosmological N-body simulation runs on the hybrid supercomputer Roadrunner, the world's first petaflop platform. Roadrunner's architecture presents opportunities and difficulties characteristic of next-generation supercomputing. We describe a new code designed to optimize performance and scalability by explicitly matching the underlying algorithms to the machine architecture, and by using the physics of the problem as an essential aid in this process. While applications will differ in specific exploits, we believe that such a design process will become increasingly important in the future. The Roadrunner Universe project code, MC3 (Mesh-based Cosmology Code on the Cell), uses grid and direct particle methods to balance the capabilities of Roadrunner's conventional (Opteron) and accelerator (Cell BE) layers. Mirrored particle caches and spectral techniques are used to overcome communication bandwidth limitations and possible difficulties with complicated particle-grid interaction templates.

Closed-loop optical neural stimulation based on a 32-channel low-noise recording system with online spike sorting

NASA Astrophysics Data System (ADS)

Nguyen, T. K. T.; Navratilova, Z.; Cabral, H.; Wang, L.; Gielen, G.; Battaglia, F. P.; Bartic, C.

2014-08-01

Objective. Closed-loop operation of neuro-electronic systems is desirable for both scientific and clinical (neuroprosthesis) applications. Integrating optical stimulation with recording capability further enhances the selectivity of neural stimulation. We have developed a system enabling the local delivery of optical stimuli and the simultaneous electrical measuring of the neural activities in a closed-loop approach. Approach. The signal analysis is performed online through the implementation of a template matching algorithm. The system performance is demonstrated with the recorded data and in awake rats. Main results. Specifically, the neural activities are simultaneously recorded, detected, classified online (through spike sorting) from 32 channels, and used to trigger a light emitting diode light source using generated TTL signals. Significance. A total processing time of 8 ms is achieved, suitable for optogenetic studies of brain mechanisms online.

Modular preoperative planning software for computer-aided oral implantology and the application of a novel stereolithographic template: a pilot study.

PubMed

Chen, Xiaojun; Yuan, Jianbing; Wang, Chengtao; Huang, Yuanliang; Kang, Lu

2010-09-01

In the field of oral implantology, there is a trend toward computer-aided implant surgery, especially the application of computerized tomography (CT)-derived surgical templates. However, because of relatively unsatisfactory match between the templates and receptor sites, conventional surgical templates may not be accurate enough for the severely resorbed edentulous cases during the procedure of transferring the preoperative plan to the actual surgery. The purpose of this study is to introduce a novel bone-tooth-combined-supported surgical guide, which is designed by utilizing a special modular software and fabricated via stereolithography technique using both laser scanning and CT imaging, thus improving the fit accuracy and reliability. A modular preoperative planning software was developed for computer-aided oral implantology. With the introduction of dynamic link libraries and some well-known free, open-source software libraries such as Visualization Toolkit (Kitware, Inc., New York, USA) and Insight Toolkit (Kitware, Inc.) a plug-in evolutive software architecture was established, allowing for expandability, accessibility, and maintainability in our system. To provide a link between the preoperative plan and the actual surgery, a novel bone-tooth-combined-supported surgical template was fabricated, utilizing laser scanning, image registration, and rapid prototyping. Clinical studies were conducted on four partially edentulous cases to make a comparison with the conventional bone-supported templates. The fixation was more stable than tooth-supported templates because laser scanning technology obtained detailed dentition information, which brought about the unique topography between the match surface of the templates and the adjacent teeth. The average distance deviations at the coronal and apical point of the implant were 0.66 mm (range: 0.3-1.2) and 0.86 mm (range: 0.4-1.2), and the average angle deviation was 1.84 degrees (range: 0.6-2.8 degrees ). This pilot study proves that the novel combined-supported templates are superior to the conventional ones. However, more clinical cases will be conducted to demonstrate their feasibility and reliability.

Megathrust Earthquake Swarms Contemporaneous to Slow Slip and Non-Volcanic Tremor in Southern Mexico, Detected and Analyzed through a Template Matching Approach

NASA Astrophysics Data System (ADS)

Holtkamp, S.; Brudzinski, M. R.; Cabral-Cano, E.; Arciniega-Ceballos, A.

2012-12-01

An outstanding question in geophysics is the degree to which the newly discovered types of slow fault slip are related to their destructive cousin - the earthquake. Here, we utilize a local network along the Oaxacan segment of the Middle American subduction zone to investigate the potential relationship between slow slip, non-volcanic tremor (NVT), and earthquakes along the subduction megathrust. We have developed a multi-station "template matching" waveform cross correlation technique which is able to detect and locate events several orders of magnitude smaller than would be possible using more traditional techniques. Also, our template matching procedure is capable of consistently locate events which occur during periods of increased background activity (e.g., during productive NVT, loud cultural noise, or after larger earthquakes) because the multi-station detector is finely tuned to events with similar hypocentral location and focal mechanism. The local network in the Oaxaca region allows us to focus on documented megathrust earthquake swarms, which we focus on because slow slip is hypothesized to be the cause for earthquake swarms in some tectonic environments. We identify a productive earthquake swarm in July 2006 (~600 similar earthquakes detected), which occurred during a week-long episode of productive tremor and slow slip. Families of events in this sequence were also active during larger and longer slow slip events, which provides a potential link between slow slip in the transition zone and earthquakes at the downdip end of the seismogenic portion of the megathrust. Because template matching techniques only detect similar signals, detected waveforms can be stacked together to produce higher signal to noise ratios or cross correlated against each other to produce precise relative phase arrival times. We are using the refined signals to look for evidence of expansion or propagation of hypocenters during these earthquake swarms, which could be used as a test for determining their underlying processes (e.g., fluid diffusion or slow slip).

An eFTD-VP framework for efficiently generating patient-specific anatomically detailed facial soft tissue FE mesh for craniomaxillofacial surgery simulation

PubMed Central

Zhang, Xiaoyan; Kim, Daeseung; Shen, Shunyao; Yuan, Peng; Liu, Siting; Tang, Zhen; Zhang, Guangming; Zhou, Xiaobo; Gateno, Jaime

2017-01-01

Accurate surgical planning and prediction of craniomaxillofacial surgery outcome requires simulation of soft tissue changes following osteotomy. This can only be achieved by using an anatomically detailed facial soft tissue model. The current state-of-the-art of model generation is not appropriate to clinical applications due to the time-intensive nature of manual segmentation and volumetric mesh generation. The conventional patient-specific finite element (FE) mesh generation methods are to deform a template FE mesh to match the shape of a patient based on registration. However, these methods commonly produce element distortion. Additionally, the mesh density for patients depends on that of the template model. It could not be adjusted to conduct mesh density sensitivity analysis. In this study, we propose a new framework of patient-specific facial soft tissue FE mesh generation. The goal of the developed method is to efficiently generate a high-quality patient-specific hexahedral FE mesh with adjustable mesh density while preserving the accuracy in anatomical structure correspondence. Our FE mesh is generated by eFace template deformation followed by volumetric parametrization. First, the patient-specific anatomically detailed facial soft tissue model (including skin, mucosa, and muscles) is generated by deforming an eFace template model. The adaptation of the eFace template model is achieved by using a hybrid landmark-based morphing and dense surface fitting approach followed by a thin-plate spline interpolation. Then, high-quality hexahedral mesh is constructed by using volumetric parameterization. The user can control the resolution of hexahedron mesh to best reflect clinicians’ need. Our approach was validated using 30 patient models and 4 visible human datasets. The generated patient-specific FE mesh showed high surface matching accuracy, element quality, and internal structure matching accuracy. They can be directly and effectively used for clinical simulation of facial soft tissue change. PMID:29027022

An eFTD-VP framework for efficiently generating patient-specific anatomically detailed facial soft tissue FE mesh for craniomaxillofacial surgery simulation.

PubMed

Zhang, Xiaoyan; Kim, Daeseung; Shen, Shunyao; Yuan, Peng; Liu, Siting; Tang, Zhen; Zhang, Guangming; Zhou, Xiaobo; Gateno, Jaime; Liebschner, Michael A K; Xia, James J

2018-04-01

Accurate surgical planning and prediction of craniomaxillofacial surgery outcome requires simulation of soft tissue changes following osteotomy. This can only be achieved by using an anatomically detailed facial soft tissue model. The current state-of-the-art of model generation is not appropriate to clinical applications due to the time-intensive nature of manual segmentation and volumetric mesh generation. The conventional patient-specific finite element (FE) mesh generation methods are to deform a template FE mesh to match the shape of a patient based on registration. However, these methods commonly produce element distortion. Additionally, the mesh density for patients depends on that of the template model. It could not be adjusted to conduct mesh density sensitivity analysis. In this study, we propose a new framework of patient-specific facial soft tissue FE mesh generation. The goal of the developed method is to efficiently generate a high-quality patient-specific hexahedral FE mesh with adjustable mesh density while preserving the accuracy in anatomical structure correspondence. Our FE mesh is generated by eFace template deformation followed by volumetric parametrization. First, the patient-specific anatomically detailed facial soft tissue model (including skin, mucosa, and muscles) is generated by deforming an eFace template model. The adaptation of the eFace template model is achieved by using a hybrid landmark-based morphing and dense surface fitting approach followed by a thin-plate spline interpolation. Then, high-quality hexahedral mesh is constructed by using volumetric parameterization. The user can control the resolution of hexahedron mesh to best reflect clinicians' need. Our approach was validated using 30 patient models and 4 visible human datasets. The generated patient-specific FE mesh showed high surface matching accuracy, element quality, and internal structure matching accuracy. They can be directly and effectively used for clinical simulation of facial soft tissue change.

Full-Waveform Envelope Templates for Low Magnitude Discrimination and Yield Estimation at Local and Regional Distances with Application to the North Korean Nuclear Tests

NASA Astrophysics Data System (ADS)

Yoo, S. H.

2017-12-01

Monitoring seismologists have successfully used seismic coda for event discrimination and yield estimation for over a decade. In practice seismologists typically analyze long-duration, S-coda signals with high signal-to-noise ratios (SNR) at regional and teleseismic distances, since the single back-scattering model reasonably predicts decay of the late coda. However, seismic monitoring requirements are shifting towards smaller, locally recorded events that exhibit low SNR and short signal lengths. To be successful at characterizing events recorded at local distances, we must utilize the direct-phase arrivals, as well as the earlier part of the coda, which is dominated by multiple forward scattering. To remedy this problem, we have developed a new hybrid method known as full-waveform envelope template matching to improve predicted envelope fits over the entire waveform and account for direct-wave and early coda complexity. We accomplish this by including a multiple forward-scattering approximation in the envelope modeling of the early coda. The new hybrid envelope templates are designed to fit local and regional full waveforms and produce low-variance amplitude estimates, which will improve yield estimation and discrimination between earthquakes and explosions. To demonstrate the new technique, we applied our full-waveform envelope template-matching method to the six known North Korean (DPRK) underground nuclear tests and four aftershock events following the September 2017 test. We successfully discriminated the event types and estimated the yield for all six nuclear tests. We also applied the same technique to the 2015 Tianjin explosions in China, and another suspected low-yield explosion at the DPRK test site on May 12, 2010. Our results show that the new full-waveform envelope template-matching method significantly improves upon longstanding single-scattering coda prediction techniques. More importantly, the new method allows monitoring seismologists to extend coda-based techniques to lower magnitude thresholds and low-yield local explosions.

Development of a stereo analysis algorithm for generating topographic maps using interactive techniques of the MPP

NASA Technical Reports Server (NTRS)

Strong, James P.

1987-01-01

A local area matching algorithm was developed on the Massively Parallel Processor (MPP). It is an iterative technique that first matches coarse or low resolution areas and at each iteration performs matches of higher resolution. Results so far show that when good matches are possible in the two images, the MPP algorithm matches corresponding areas as well as a human observer. To aid in developing this algorithm, a control or shell program was developed for the MPP that allows interactive experimentation with various parameters and procedures to be used in the matching process. (This would not be possible without the high speed of the MPP). With the system, optimal techniques can be developed for different types of matching problems.

Single-camera three-dimensional tracking of natural particulate and zooplankton

NASA Astrophysics Data System (ADS)

Troutman, Valerie A.; Dabiri, John O.

2018-07-01

We develop and characterize an image processing algorithm to adapt single-camera defocusing digital particle image velocimetry (DDPIV) for three-dimensional (3D) particle tracking velocimetry (PTV) of natural particulates, such as those present in the ocean. The conventional DDPIV technique is extended to facilitate tracking of non-uniform, non-spherical particles within a volume depth an order of magnitude larger than current single-camera applications (i.e. 10 cm  ×  10 cm  ×  24 cm depth) by a dynamic template matching method. This 2D cross-correlation method does not rely on precise determination of the centroid of the tracked objects. To accommodate the broad range of particle number densities found in natural marine environments, the performance of the measurement technique at higher particle densities has been improved by utilizing the time-history of tracked objects to inform 3D reconstruction. The developed processing algorithms were analyzed using synthetically generated images of flow induced by Hill’s spherical vortex, and the capabilities of the measurement technique were demonstrated empirically through volumetric reconstructions of the 3D trajectories of particles and highly non-spherical, 5 mm zooplankton.

Easy-DHPSF open-source software for three-dimensional localization of single molecules with precision beyond the optical diffraction limit.

PubMed

Lew, Matthew D; von Diezmann, Alexander R S; Moerner, W E

2013-02-25

Automated processing of double-helix (DH) microscope images of single molecules (SMs) streamlines the protocol required to obtain super-resolved three-dimensional (3D) reconstructions of ultrastructures in biological samples by single-molecule active control microscopy. Here, we present a suite of MATLAB subroutines, bundled with an easy-to-use graphical user interface (GUI), that facilitates 3D localization of single emitters (e.g. SMs, fluorescent beads, or quantum dots) with precisions of tens of nanometers in multi-frame movies acquired using a wide-field DH epifluorescence microscope. The algorithmic approach is based upon template matching for SM recognition and least-squares fitting for 3D position measurement, both of which are computationally expedient and precise. Overlapping images of SMs are ignored, and the precision of least-squares fitting is not as high as maximum likelihood-based methods. However, once calibrated, the algorithm can fit 15-30 molecules per second on a 3 GHz Intel Core 2 Duo workstation, thereby producing a 3D super-resolution reconstruction of 100,000 molecules over a 20×20×2 μm field of view (processing 128×128 pixels × 20000 frames) in 75 min.

Approximate string matching algorithms for limited-vocabulary OCR output correction

NASA Astrophysics Data System (ADS)

Lasko, Thomas A.; Hauser, Susan E.

2000-12-01

Five methods for matching words mistranslated by optical character recognition to their most likely match in a reference dictionary were tested on data from the archives of the National Library of Medicine. The methods, including an adaptation of the cross correlation algorithm, the generic edit distance algorithm, the edit distance algorithm with a probabilistic substitution matrix, Bayesian analysis, and Bayesian analysis on an actively thinned reference dictionary were implemented and their accuracy rates compared. Of the five, the Bayesian algorithm produced the most correct matches (87%), and had the advantage of producing scores that have a useful and practical interpretation.

Best chirplet chain: Near-optimal detection of gravitational wave chirps

NASA Astrophysics Data System (ADS)

Chassande-Mottin, Éric; Pai, Archana

2006-02-01

The list of putative sources of gravitational waves possibly detected by the ongoing worldwide network of large scale interferometers has been continuously growing in the last years. For some of them, the detection is made difficult by the lack of a complete information about the expected signal. We concentrate on the case where the expected gravitational wave (GW) is a quasiperiodic frequency modulated signal i.e., a chirp. In this article, we address the question of detecting an a priori unknown GW chirp. We introduce a general chirp model and claim that it includes all physically realistic GW chirps. We produce a finite grid of template waveforms which samples the resulting set of possible chirps. If we follow the classical approach (used for the detection of inspiralling binary chirps, for instance), we would build a bank of quadrature matched filters comparing the data to each of the templates of this grid. The detection would then be achieved by thresholding the output, the maximum giving the individual which best fits the data. In the present case, this exhaustive search is not tractable because of the very large number of templates in the grid. We show that the exhaustive search can be reformulated (using approximations) as a pattern search in the time-frequency plane. This motivates an approximate but feasible alternative solution which is clearly linked to the optimal one. The time-frequency representation and pattern search algorithm are fully determined by the reformulation. This contrasts with the other time-frequency based methods presented in the literature for the same problem, where these choices are justified by “ad hoc” arguments. In particular, the time-frequency representation has to be unitary. Finally, we assess the performance, robustness and computational cost of the proposed method with several benchmarks using simulated data.

Score-Level Fusion of Phase-Based and Feature-Based Fingerprint Matching Algorithms

NASA Astrophysics Data System (ADS)

Ito, Koichi; Morita, Ayumi; Aoki, Takafumi; Nakajima, Hiroshi; Kobayashi, Koji; Higuchi, Tatsuo

This paper proposes an efficient fingerprint recognition algorithm combining phase-based image matching and feature-based matching. In our previous work, we have already proposed an efficient fingerprint recognition algorithm using Phase-Only Correlation (POC), and developed commercial fingerprint verification units for access control applications. The use of Fourier phase information of fingerprint images makes it possible to achieve robust recognition for weakly impressed, low-quality fingerprint images. This paper presents an idea of improving the performance of POC-based fingerprint matching by combining it with feature-based matching, where feature-based matching is introduced in order to improve recognition efficiency for images with nonlinear distortion. Experimental evaluation using two different types of fingerprint image databases demonstrates efficient recognition performance of the combination of the POC-based algorithm and the feature-based algorithm.

A Study of Lane Detection Algorithm for Personal Vehicle

NASA Astrophysics Data System (ADS)

Kobayashi, Kazuyuki; Watanabe, Kajiro; Ohkubo, Tomoyuki; Kurihara, Yosuke

By the word “Personal vehicle”, we mean a simple and lightweight vehicle expected to emerge as personal ground transportation devices. The motorcycle, electric wheelchair, motor-powered bicycle, etc. are examples of the personal vehicle and have been developed as the useful for transportation for a personal use. Recently, a new types of intelligent personal vehicle called the Segway has been developed which is controlled and stabilized by using on-board intelligent multiple sensors. The demand for needs for such personal vehicles are increasing, 1) to enhance human mobility, 2) to support mobility for elderly person, 3) reduction of environmental burdens. Since rapidly growing personal vehicles' market, a number of accidents caused by human error is also increasing. The accidents are caused by it's drive ability. To enhance or support drive ability as well as to prevent accidents, intelligent assistance is necessary. One of most important elemental functions for personal vehicle is robust lane detection. In this paper, we develop a robust lane detection method for personal vehicle at outdoor environments. The proposed lane detection method employing a 360 degree omni directional camera and unique robust image processing algorithm. In order to detect lanes, combination of template matching technique and Hough transform are employed. The validity of proposed lane detection algorithm is confirmed by actual developed vehicle at various type of sunshined outdoor conditions.

Vision-Based Haptic Feedback for Remote Micromanipulation in-SEM Environment

NASA Astrophysics Data System (ADS)

Bolopion, Aude; Dahmen, Christian; Stolle, Christian; Haliyo, Sinan; Régnier, Stéphane; Fatikow, Sergej

2012-07-01

This article presents an intuitive environment for remote micromanipulation composed of both haptic feedback and virtual reconstruction of the scene. To enable nonexpert users to perform complex teleoperated micromanipulation tasks, it is of utmost importance to provide them with information about the 3-D relative positions of the objects and the tools. Haptic feedback is an intuitive way to transmit such information. Since position sensors are not available at this scale, visual feedback is used to derive information about the scene. In this work, three different techniques are implemented, evaluated, and compared to derive the object positions from scanning electron microscope images. The modified correlation matching with generated template algorithm is accurate and provides reliable detection of objects. To track the tool, a marker-based approach is chosen since fast detection is required for stable haptic feedback. Information derived from these algorithms is used to propose an intuitive remote manipulation system that enables users situated in geographically distant sites to benefit from specific equipments, such as SEMs. Stability of the haptic feedback is ensured by the minimization of the delays, the computational efficiency of vision algorithms, and the proper tuning of the haptic coupling. Virtual guides are proposed to avoid any involuntary collisions between the tool and the objects. This approach is validated by a teleoperation involving melamine microspheres with a diameter of less than 2 μ m between Paris, France and Oldenburg, Germany.

A comparison of 12 algorithms for matching on the propensity score.

PubMed

Austin, Peter C

2014-03-15

Propensity-score matching is increasingly being used to reduce the confounding that can occur in observational studies examining the effects of treatments or interventions on outcomes. We used Monte Carlo simulations to examine the following algorithms for forming matched pairs of treated and untreated subjects: optimal matching, greedy nearest neighbor matching without replacement, and greedy nearest neighbor matching without replacement within specified caliper widths. For each of the latter two algorithms, we examined four different sub-algorithms defined by the order in which treated subjects were selected for matching to an untreated subject: lowest to highest propensity score, highest to lowest propensity score, best match first, and random order. We also examined matching with replacement. We found that (i) nearest neighbor matching induced the same balance in baseline covariates as did optimal matching; (ii) when at least some of the covariates were continuous, caliper matching tended to induce balance on baseline covariates that was at least as good as the other algorithms; (iii) caliper matching tended to result in estimates of treatment effect with less bias compared with optimal and nearest neighbor matching; (iv) optimal and nearest neighbor matching resulted in estimates of treatment effect with negligibly less variability than did caliper matching; (v) caliper matching had amongst the best performance when assessed using mean squared error; (vi) the order in which treated subjects were selected for matching had at most a modest effect on estimation; and (vii) matching with replacement did not have superior performance compared with caliper matching without replacement. © 2013 The Authors. Statistics in Medicine published by John Wiley & Sons, Ltd.

A comparison of 12 algorithms for matching on the propensity score

PubMed Central

Austin, Peter C

2014-01-01

Propensity-score matching is increasingly being used to reduce the confounding that can occur in observational studies examining the effects of treatments or interventions on outcomes. We used Monte Carlo simulations to examine the following algorithms for forming matched pairs of treated and untreated subjects: optimal matching, greedy nearest neighbor matching without replacement, and greedy nearest neighbor matching without replacement within specified caliper widths. For each of the latter two algorithms, we examined four different sub-algorithms defined by the order in which treated subjects were selected for matching to an untreated subject: lowest to highest propensity score, highest to lowest propensity score, best match first, and random order. We also examined matching with replacement. We found that (i) nearest neighbor matching induced the same balance in baseline covariates as did optimal matching; (ii) when at least some of the covariates were continuous, caliper matching tended to induce balance on baseline covariates that was at least as good as the other algorithms; (iii) caliper matching tended to result in estimates of treatment effect with less bias compared with optimal and nearest neighbor matching; (iv) optimal and nearest neighbor matching resulted in estimates of treatment effect with negligibly less variability than did caliper matching; (v) caliper matching had amongst the best performance when assessed using mean squared error; (vi) the order in which treated subjects were selected for matching had at most a modest effect on estimation; and (vii) matching with replacement did not have superior performance compared with caliper matching without replacement. © 2013 The Authors. Statistics in Medicine published by John Wiley & Sons, Ltd. PMID:24123228

SPHERE: SPherical Harmonic Elastic REgistration of HARDI Data

PubMed Central

Yap, Pew-Thian; Chen, Yasheng; An, Hongyu; Yang, Yang; Gilmore, John H.; Lin, Weili

2010-01-01

In contrast to the more common Diffusion Tensor Imaging (DTI), High Angular Resolution Diffusion Imaging (HARDI) allows superior delineation of angular microstructures of brain white matter, and makes possible multiple-fiber modeling of each voxel for better characterization of brain connectivity. However, the complex orientation information afforded by HARDI makes registration of HARDI images more complicated than scalar images. In particular, the question of how much orientation information is needed for satisfactory alignment has not been sufficiently addressed. Low order orientation representation is generally more robust than high order representation, although the latter provides more information for correct alignment of fiber pathways. However, high order representation, when naïvely utilized, might not necessarily be conducive to improving registration accuracy since similar structures with significant orientation differences prior to proper alignment might be mistakenly taken as non-matching structures. We present in this paper a HARDI registration algorithm, called SPherical Harmonic Elastic REgistration (SPHERE), which in a principled means hierarchically extracts orientation information from HARDI data for structural alignment. The image volumes are first registered using robust, relatively direction invariant features derived from the Orientation Distribution Function (ODF), and the alignment is then further refined using spherical harmonic (SH) representation with gradually increasing orders. This progression from non-directional, single-directional to multi-directional representation provides a systematic means of extracting directional information given by diffusion-weighted imaging. Coupled with a template-subject-consistent soft-correspondence-matching scheme, this approach allows robust and accurate alignment of HARDI data. Experimental results show marked increase in accuracy over a state-of-the-art DTI registration algorithm. PMID:21147231

On Parallel Push-Relabel based Algorithms for Bipartite Maximum Matching

DOE Office of Scientific and Technical Information (OSTI.GOV)

Langguth, Johannes; Azad, Md Ariful; Halappanavar, Mahantesh

2014-07-01

We study multithreaded push-relabel based algorithms for computing maximum cardinality matching in bipartite graphs. Matching is a fundamental combinatorial (graph) problem with applications in a wide variety of problems in science and engineering. We are motivated by its use in the context of sparse linear solvers for computing maximum transversal of a matrix. We implement and test our algorithms on several multi-socket multicore systems and compare their performance to state-of-the-art augmenting path-based serial and parallel algorithms using a testset comprised of a wide range of real-world instances. Building on several heuristics for enhancing performance, we demonstrate good scaling for themore » parallel push-relabel algorithm. We show that it is comparable to the best augmenting path-based algorithms for bipartite matching. To the best of our knowledge, this is the first extensive study of multithreaded push-relabel based algorithms. In addition to a direct impact on the applications using matching, the proposed algorithmic techniques can be extended to preflow-push based algorithms for computing maximum flow in graphs.« less

Multiple template-based fluoroscopic tracking of lung tumor mass without implanted fiducial markers

NASA Astrophysics Data System (ADS)

Cui, Ying; Dy, Jennifer G.; Sharp, Gregory C.; Alexander, Brian; Jiang, Steve B.

2007-10-01

Precise lung tumor localization in real time is particularly important for some motion management techniques, such as respiratory gating or beam tracking with a dynamic multi-leaf collimator, due to the reduced clinical tumor volume (CTV) to planning target volume (PTV) margin and/or the escalated dose. There might be large uncertainties in deriving tumor position from external respiratory surrogates. While tracking implanted fiducial markers has sufficient accuracy, this procedure may not be widely accepted due to the risk of pneumothorax. Previously, we have developed a technique to generate gating signals from fluoroscopic images without implanted fiducial markers using a template matching method (Berbeco et al 2005 Phys. Med. Biol. 50 4481-90, Cui et al 2007 Phys. Med. Biol. 52 741-55). In this paper, we present an extension of this method to multiple-template matching for directly tracking the lung tumor mass in fluoroscopy video. The basic idea is as follows: (i) during the patient setup session, a pair of orthogonal fluoroscopic image sequences are taken and processed off-line to generate a set of reference templates that correspond to different breathing phases and tumor positions; (ii) during treatment delivery, fluoroscopic images are continuously acquired and processed; (iii) the similarity between each reference template and the processed incoming image is calculated; (iv) the tumor position in the incoming image is then estimated by combining the tumor centroid coordinates in reference templates with proper weights based on the measured similarities. With different handling of image processing and similarity calculation, two such multiple-template tracking techniques have been developed: one based on motion-enhanced templates and Pearson's correlation score while the other based on eigen templates and mean-squared error. The developed techniques have been tested on six sequences of fluoroscopic images from six lung cancer patients against the reference tumor positions manually determined by a radiation oncologist. The tumor centroid coordinates automatically detected using both methods agree well with the manually marked reference locations. The eigenspace tracking method performs slightly better than the motion-enhanced method, with average localization errors less than 2 pixels (1 mm) and the error at a 95% confidence level of about 2-4 pixels (1-2 mm). This work demonstrates the feasibility of direct tracking of a lung tumor mass in fluoroscopic images without implanted fiducial markers using multiple reference templates.

Matching organic libraries with protein-substructures

NASA Astrophysics Data System (ADS)

Preissner, R.; Goede, A.; Rother, K.; Osterkamp, F.; Koert, U.; Froemmel, C.

2001-09-01

We present a general approach which allows automatic identification of sub-structures in proteins that resemble given three-dimensional templates. This paper documents its success with non-peptide templates such as β-turn mimetics. We considered well-tested turn-mimetics such as the bicyclic turned dipeptide (BTD), spiro lactam (Spiro) and the 2,5-disubstituded tetrahydrofuran (THF), a new furan-derivative which was recently developed and characterized. The detected geometric similarity between the templates and the protein patches corresponds to r.m.s.-values of 0.3 Å for more than 80% of the constituting atoms, which is typical for active site comparisons of homologous proteins. This fast automatic procedure might be of biomedical value for finding special mimicking leads for particular protein sub-structures as well as for template-assembled synthetic protein (TASP) design.

SDIA: A dynamic situation driven information fusion algorithm for cloud environment

NASA Astrophysics Data System (ADS)

Guo, Shuhang; Wang, Tong; Wang, Jian

2017-09-01

Information fusion is an important issue in information integration domain. In order to form an extensive information fusion technology under the complex and diverse situations, a new information fusion algorithm is proposed. Firstly, a fuzzy evaluation model of tag utility was proposed that can be used to count the tag entropy. Secondly, a ubiquitous situation tag tree model is proposed to define multidimensional structure of information situation. Thirdly, the similarity matching between the situation models is classified into three types: the tree inclusion, the tree embedding, and the tree compatibility. Next, in order to reduce the time complexity of the tree compatible matching algorithm, a fast and ordered tree matching algorithm is proposed based on the node entropy, which is used to support the information fusion by ubiquitous situation. Since the algorithm revolve from the graph theory of disordered tree matching algorithm, it can improve the information fusion present recall rate and precision rate in the situation. The information fusion algorithm is compared with the star and the random tree matching algorithm, and the difference between the three algorithms is analyzed in the view of isomorphism, which proves the innovation and applicability of the algorithm.

Image matching for digital close-range stereo photogrammetry based on constraints of Delaunay triangulated network and epipolar-line

NASA Astrophysics Data System (ADS)

Zhang, K.; Sheng, Y. H.; Li, Y. Q.; Han, B.; Liang, Ch.; Sha, W.

2006-10-01

In the field of digital photogrammetry and computer vision, the determination of conjugate points in a stereo image pair, referred to as "image matching," is the critical step to realize automatic surveying and recognition. Traditional matching methods encounter some problems in the digital close-range stereo photogrammetry, because the change of gray-scale or texture is not obvious in the close-range stereo images. The main shortcoming of traditional matching methods is that geometric information of matching points is not fully used, which will lead to wrong matching results in regions with poor texture. To fully use the geometry and gray-scale information, a new stereo image matching algorithm is proposed in this paper considering the characteristics of digital close-range photogrammetry. Compared with the traditional matching method, the new algorithm has three improvements on image matching. Firstly, shape factor, fuzzy maths and gray-scale projection are introduced into the design of synthetical matching measure. Secondly, the topology connecting relations of matching points in Delaunay triangulated network and epipolar-line are used to decide matching order and narrow the searching scope of conjugate point of the matching point. Lastly, the theory of parameter adjustment with constraint is introduced into least square image matching to carry out subpixel level matching under epipolar-line constraint. The new algorithm is applied to actual stereo images of a building taken by digital close-range photogrammetric system. The experimental result shows that the algorithm has a higher matching speed and matching accuracy than pyramid image matching algorithm based on gray-scale correlation.

Scalable Nearest Neighbor Algorithms for High Dimensional Data.

PubMed

Muja, Marius; Lowe, David G

2014-11-01

For many computer vision and machine learning problems, large training sets are key for good performance. However, the most computationally expensive part of many computer vision and machine learning algorithms consists of finding nearest neighbor matches to high dimensional vectors that represent the training data. We propose new algorithms for approximate nearest neighbor matching and evaluate and compare them with previous algorithms. For matching high dimensional features, we find two algorithms to be the most efficient: the randomized k-d forest and a new algorithm proposed in this paper, the priority search k-means tree. We also propose a new algorithm for matching binary features by searching multiple hierarchical clustering trees and show it outperforms methods typically used in the literature. We show that the optimal nearest neighbor algorithm and its parameters depend on the data set characteristics and describe an automated configuration procedure for finding the best algorithm to search a particular data set. In order to scale to very large data sets that would otherwise not fit in the memory of a single machine, we propose a distributed nearest neighbor matching framework that can be used with any of the algorithms described in the paper. All this research has been released as an open source library called fast library for approximate nearest neighbors (FLANN), which has been incorporated into OpenCV and is now one of the most popular libraries for nearest neighbor matching.

Spectral matching technology for light-emitting diode-based jaundice photodynamic therapy device

NASA Astrophysics Data System (ADS)

Gan, Ru-ting; Guo, Zhen-ning; Lin, Jie-ben

2015-02-01

The objective of this paper is to obtain the spectrum of light-emitting diode (LED)-based jaundice photodynamic therapy device (JPTD), the bilirubin absorption spectrum in vivo was regarded as target spectrum. According to the spectral constructing theory, a simple genetic algorithm as the spectral matching algorithm was first proposed in this study. The optimal combination ratios of LEDs were obtained, and the required LEDs number was then calculated. Meanwhile, the algorithm was compared with the existing spectral matching algorithms. The results show that this algorithm runs faster with higher efficiency, the switching time consumed is 2.06 s, and the fitting spectrum is very similar to the target spectrum with 98.15% matching degree. Thus, blue LED-based JPTD can replace traditional blue fluorescent tube, the spectral matching technology that has been put forward can be applied to the light source spectral matching for jaundice photodynamic therapy and other medical phototherapy.

Comparison of statistical algorithms for detecting homogeneous river reaches along a longitudinal continuum

NASA Astrophysics Data System (ADS)

Leviandier, Thierry; Alber, A.; Le Ber, F.; Piégay, H.

2012-02-01

Seven methods designed to delineate homogeneous river segments, belonging to four families, namely — tests of homogeneity, contrast enhancing, spatially constrained classification, and hidden Markov models — are compared, firstly on their principles, then on a case study, and on theoretical templates. These templates contain patterns found in the case study but not considered in the standard assumptions of statistical methods, such as gradients and curvilinear structures. The influence of data resolution, noise and weak satisfaction of the assumptions underlying the methods is investigated. The control of the number of reaches obtained in order to achieve meaningful comparisons is discussed. No method is found that outperforms all the others on all trials. However, the methods with sequential algorithms (keeping at order n + 1 all breakpoints found at order n) fail more often than those running complete optimisation at any order. The Hubert-Kehagias method and Hidden Markov Models are the most successful at identifying subpatterns encapsulated within the templates. Ergodic Hidden Markov Models are, moreover, liable to exhibit transition areas.

Phi-s correlation and dynamic time warping - Two methods for tracking ice floes in SAR images

NASA Technical Reports Server (NTRS)

Mcconnell, Ross; Kober, Wolfgang; Kwok, Ronald; Curlander, John C.; Pang, Shirley S.

1991-01-01

The authors present two algorithms for performing shape matching on ice floe boundaries in SAR (synthetic aperture radar) images. These algorithms quickly produce a set of ice motion and rotation vectors that can be used to guide a pixel value correlator. The algorithms match a shape descriptor known as the Phi-s curve. The first algorithm uses normalized correlation to match the Phi-s curves, while the second uses dynamic programming to compute an elastic match that better accommodates ice floe deformation. Some empirical data on the performance of the algorithms on Seasat SAR images are presented.

SKL algorithm based fabric image matching and retrieval

NASA Astrophysics Data System (ADS)

Cao, Yichen; Zhang, Xueqin; Ma, Guojian; Sun, Rongqing; Dong, Deping

2017-07-01

Intelligent computer image processing technology provides convenience and possibility for designers to carry out designs. Shape analysis can be achieved by extracting SURF feature. However, high dimension of SURF feature causes to lower matching speed. To solve this problem, this paper proposed a fast fabric image matching algorithm based on SURF K-means and LSH algorithm. By constructing the bag of visual words on K-Means algorithm, and forming feature histogram of each image, the dimension of SURF feature is reduced at the first step. Then with the help of LSH algorithm, the features are encoded and the dimension is further reduced. In addition, the indexes of each image and each class of image are created, and the number of matching images is decreased by LSH hash bucket. Experiments on fabric image database show that this algorithm can speed up the matching and retrieval process, the result can satisfy the requirement of dress designers with accuracy and speed.

Process Materialization Using Templates and Rules to Design Flexible Process Models

NASA Astrophysics Data System (ADS)

Kumar, Akhil; Yao, Wen

The main idea in this paper is to show how flexible processes can be designed by combining generic process templates and business rules. We instantiate a process by applying rules to specific case data, and running a materialization algorithm. The customized process instance is then executed in an existing workflow engine. We present an architecture and also give an algorithm for process materialization. The rules are written in a logic-based language like Prolog. Our focus is on capturing deeper process knowledge and achieving a holistic approach to robust process design that encompasses control flow, resources and data, as well as makes it easier to accommodate changes to business policy.

A fingerprint key binding algorithm based on vector quantization and error correction

NASA Astrophysics Data System (ADS)

Li, Liang; Wang, Qian; Lv, Ke; He, Ning

2012-04-01

In recent years, researches on seamless combination cryptosystem with biometric technologies, e.g. fingerprint recognition, are conducted by many researchers. In this paper, we propose a binding algorithm of fingerprint template and cryptographic key to protect and access the key by fingerprint verification. In order to avoid the intrinsic fuzziness of variant fingerprints, vector quantization and error correction technique are introduced to transform fingerprint template and then bind with key, after a process of fingerprint registration and extracting global ridge pattern of fingerprint. The key itself is secure because only hash value is stored and it is released only when fingerprint verification succeeds. Experimental results demonstrate the effectiveness of our ideas.

Image Registration Algorithm Based on Parallax Constraint and Clustering Analysis

NASA Astrophysics Data System (ADS)

Wang, Zhe; Dong, Min; Mu, Xiaomin; Wang, Song

2018-01-01

To resolve the problem of slow computation speed and low matching accuracy in image registration, a new image registration algorithm based on parallax constraint and clustering analysis is proposed. Firstly, Harris corner detection algorithm is used to extract the feature points of two images. Secondly, use Normalized Cross Correlation (NCC) function to perform the approximate matching of feature points, and the initial feature pair is obtained. Then, according to the parallax constraint condition, the initial feature pair is preprocessed by K-means clustering algorithm, which is used to remove the feature point pairs with obvious errors in the approximate matching process. Finally, adopt Random Sample Consensus (RANSAC) algorithm to optimize the feature points to obtain the final feature point matching result, and the fast and accurate image registration is realized. The experimental results show that the image registration algorithm proposed in this paper can improve the accuracy of the image matching while ensuring the real-time performance of the algorithm.

Broadband moth-eye antireflection coatings on silicon

NASA Astrophysics Data System (ADS)

Sun, Chih-Hung; Jiang, Peng; Jiang, Bin

2008-02-01

We report a bioinspired templating technique for fabricating broadband antireflection coatings that mimic antireflective moth eyes. Wafer-scale, subwavelength-structured nipple arrays are directly patterned on silicon using spin-coated silica colloidal monolayers as etching masks. The templated gratings exhibit excellent broadband antireflection properties and the normal-incidence specular reflection matches with the theoretical prediction using a rigorous coupled-wave analysis (RCWA) model. We further demonstrate that two common simulation methods, RCWA and thin-film multilayer models, generate almost identical prediction for the templated nipple arrays. This simple bottom-up technique is compatible with standard microfabrication, promising for reducing the manufacturing cost of crystalline silicon solar cells.

Radar images analysis for scattering surfaces characterization

NASA Astrophysics Data System (ADS)

Piazza, Enrico

1998-10-01

According to the different problems and techniques related to the detection and recognition of airplanes and vehicles moving on the Airport surface, the present work mainly deals with the processing of images gathered by a high-resolution radar sensor. The radar images used to test the investigated algorithms are relative to sequence of images obtained in some field experiments carried out by the Electronic Engineering Department of the University of Florence. The radar is the Ka band radar operating in the'Leonardo da Vinci' Airport in Fiumicino (Rome). The images obtained from the radar scan converter are digitized and putted in x, y, (pixel) co- ordinates. For a correct matching of the images, these are corrected in true geometrical co-ordinates (meters) on the basis of fixed points on an airport map. Correlating the airplane 2-D multipoint template with actual radar images, the value of the signal in the points involved in the template can be extracted. Results for a lot of observation show a typical response for the main section of the fuselage and the wings. For the fuselage, the back-scattered echo is low at the prow, became larger near the center on the aircraft and than it decrease again toward the tail. For the wings the signal is growing with a pretty regular slope from the fuselage to the tips, where the signal is the strongest.

Control system of hexacopter using color histogram footprint and convolutional neural network

NASA Astrophysics Data System (ADS)

Ruliputra, R. N.; Darma, S.

2017-07-01

The development of unmanned aerial vehicles (UAV) has been growing rapidly in recent years. The use of logic thinking which is implemented into the program algorithms is needed to make a smart system. By using visual input from a camera, UAV is able to fly autonomously by detecting a target. However, some weaknesses arose as usage in the outdoor environment might change the target's color intensity. Color histogram footprint overcomes the problem because it divides color intensity into separate bins that make the detection tolerant to the slight change of color intensity. Template matching compare its detection result with a template of the reference image to determine the target position and use it to position the vehicle in the middle of the target with visual feedback control based on Proportional-Integral-Derivative (PID) controller. Color histogram footprint method localizes the target by calculating the back projection of its histogram. It has an average success rate of 77 % from a distance of 1 meter. It can position itself in the middle of the target by using visual feedback control with an average positioning time of 73 seconds. After the hexacopter is in the middle of the target, Convolutional Neural Networks (CNN) classifies a number contained in the target image to determine a task depending on the classified number, either landing, yawing, or return to launch. The recognition result shows an optimum success rate of 99.2 %.

Open set recognition of aircraft in aerial imagery using synthetic template models

NASA Astrophysics Data System (ADS)

Bapst, Aleksander B.; Tran, Jonathan; Koch, Mark W.; Moya, Mary M.; Swahn, Robert

2017-05-01

Fast, accurate and robust automatic target recognition (ATR) in optical aerial imagery can provide game-changing advantages to military commanders and personnel. ATR algorithms must reject non-targets with a high degree of confidence in a world with an infinite number of possible input images. Furthermore, they must learn to recognize new targets without requiring massive data collections. Whereas most machine learning algorithms classify data in a closed set manner by mapping inputs to a fixed set of training classes, open set recognizers incorporate constraints that allow for inputs to be labelled as unknown. We have adapted two template-based open set recognizers to use computer generated synthetic images of military aircraft as training data, to provide a baseline for military-grade ATR: (1) a frequentist approach based on probabilistic fusion of extracted image features, and (2) an open set extension to the one-class support vector machine (SVM). These algorithms both use histograms of oriented gradients (HOG) as features as well as artificial augmentation of both real and synthetic image chips to take advantage of minimal training data. Our results show that open set recognizers trained with synthetic data and tested with real data can successfully discriminate real target inputs from non-targets. However, there is still a requirement for some knowledge of the real target in order to calibrate the relationship between synthetic template and target score distributions. We conclude by proposing algorithm modifications that may improve the ability of synthetic data to represent real data.

Face biometrics with renewable templates

NASA Astrophysics Data System (ADS)

van der Veen, Michiel; Kevenaar, Tom; Schrijen, Geert-Jan; Akkermans, Ton H.; Zuo, Fei

2006-02-01

In recent literature, privacy protection technologies for biometric templates were proposed. Among these is the so-called helper-data system (HDS) based on reliable component selection. In this paper we integrate this approach with face biometrics such that we achieve a system in which the templates are privacy protected, and multiple templates can be derived from the same facial image for the purpose of template renewability. Extracting binary feature vectors forms an essential step in this process. Using the FERET and Caltech databases, we show that this quantization step does not significantly degrade the classification performance compared to, for example, traditional correlation-based classifiers. The binary feature vectors are integrated in the HDS leading to a privacy protected facial recognition algorithm with acceptable FAR and FRR, provided that the intra-class variation is sufficiently small. This suggests that a controlled enrollment procedure with a sufficient number of enrollment measurements is required.

Inhibitory motor control based on complex stopping goals relies on the same brain network as simple stopping

PubMed Central

Wessel, Jan R.; Aron, Adam R.

2014-01-01

Much research has modeled action-stopping using the stop-signal task (SST), in which an impending response has to be stopped when an explicit stop-signal occurs. A limitation of the SST is that real-world action-stopping rarely involves explicit stop-signals. Instead, the stopping-system engages when environmental features match more complex stopping goals. For example, when stepping into the street, one monitors path, velocity, size, and types of objects; and only stops if there is a vehicle approaching. Here, we developed a task in which participants compared the visual features of a multidimensional go-stimulus to a complex stopping-template, and stopped their go-response if all features matched the template. We used independent component analysis of EEG data to show that the same motor inhibition brain network that explains action-stopping in the SST also implements motor inhibition in the complex-stopping task. Furthermore, we found that partial feature overlap between go-stimulus and stopping-template lead to motor slowing, which also corresponded with greater stopping-network activity. This shows that the same brain system for action-stopping to explicit stop-signals is recruited to slow or stop behavior when stimuli match a complex stopping goal. The results imply a generalizability of the brain’s network for simple action-stopping to more ecologically valid scenarios. PMID:25270603

An improved low-frequency earthquakes catalogue in the vicinity of the late-interseismic central Alpine Fault, Southern Alps, New Zealand

NASA Astrophysics Data System (ADS)

Baratin, Laura-May; Chamberlain, Calum J.; Townend, John; Savage, Martha K.

2017-04-01

Characterising the seismicity associated with slow deformation in the vicinity of the Alpine Fault may provide constraints on the state of stress of this major transpressive margin prior to a large (≥M8) earthquake. Here, we use recently detected tectonic tremor and low-frequency earthquakes (LFEs) to examine how slow tectonic deformation is loading the Alpine Fault toward an anticipated large rupture. We initially work with a continous seismic dataset collected between 2009 and 2012 from an array of short-period seismometers, the Southern Alps Microearthquake Borehole Array. Fourteen primary LFE templates, found through visual inspection within previously identified tectonic tremor, are used in an iterative matched-filter and stacking routine. This method allows the detection of similar signals and establishes LFE families with common locations. We thus generate a 36 month catalogue of 10718 LFEs. The detections are then combined for each LFE family using phase-weighted stacking to yield a signal with the highest possible signal to noise ratio. We found phase-weighted stacking to be successful in increasing the number of LFE detections by roughly 20%. Phase-weighted stacking also provides cleaner phase arrivals of apparently impulsive nature allowing more precise phase picks. We then compute non-linear earthquake locations using a 3D velocity model and find LFEs to occur below the seismogenic zone at depths of 18-34 km, locating on or near the proposed deep extent of the Alpine Fault. To gain insight into deep fault slip behaviour, a detailed study of the spatial-temporal evolution of LFEs is required. We thus generate a more extensive catalogue of LFEs spanning the years 2009 to 2016 using a different technique to detect LFEs more efficiently. This time 638 synthetic waveforms are used as primary templates in the match-filter routine. Of those, 38 templates yield no detections over our 7-yr study period. The remaining 600 templates end up detecting between 370 and 730 events each totalling ˜310 000 detections. We then focus on only keeping the detections that robustly stack (i.e. representing real LFEs) for each synthetic template hence creating new LFE templates. From there, we rerun the match-filter routine with our new LFE templates. Finally, each LFE template and its subsequent detections form a LFE family, itself associated with a single source. Initial testing shows that this technique paired up with phase-weighted stacking increases the number of LFE families and overall detected events roughly thirtyfold. Our next step is to study in detail the spatial and temporal activity of our LFEs. This new catalogue should provide new insight into the deep central Alpine Fault structure and its slip behaviour.

Compact hybrid optoelectrical unit for image processing and recognition

NASA Astrophysics Data System (ADS)

Cheng, Gang; Jin, Guofan; Wu, Minxian; Liu, Haisong; He, Qingsheng; Yuan, ShiFu

1998-07-01

In this paper a compact opto-electric unit (CHOEU) for digital image processing and recognition is proposed. The central part of CHOEU is an incoherent optical correlator, which is realized with a SHARP QA-1200 8.4 inch active matrix TFT liquid crystal display panel which is used as two real-time spatial light modulators for both the input image and reference template. CHOEU can do two main processing works. One is digital filtering; the other is object matching. Using CHOEU an edge-detection operator is realized to extract the edges from the input images. Then the reprocessed images are sent into the object recognition unit for identifying the important targets. A novel template- matching method is proposed for gray-tome image recognition. A positive and negative cycle-encoding method is introduced to realize the absolute difference measurement pixel- matching on a correlator structure simply. The system has god fault-tolerance ability for rotation distortion, Gaussian noise disturbance or information losing. The experiments are given at the end of this paper.

JANE: efficient mapping of prokaryotic ESTs and variable length sequence reads on related template genomes

PubMed Central

2009-01-01

Background ESTs or variable sequence reads can be available in prokaryotic studies well before a complete genome is known. Use cases include (i) transcriptome studies or (ii) single cell sequencing of bacteria. Without suitable software their further analysis and mapping would have to await finalization of the corresponding genome. Results The tool JANE rapidly maps ESTs or variable sequence reads in prokaryotic sequencing and transcriptome efforts to related template genomes. It provides an easy-to-use graphics interface for information retrieval and a toolkit for EST or nucleotide sequence function prediction. Furthermore, we developed for rapid mapping an enhanced sequence alignment algorithm which reassembles and evaluates high scoring pairs provided from the BLAST algorithm. Rapid assembly on and replacement of the template genome by sequence reads or mapped ESTs is achieved. This is illustrated (i) by data from Staphylococci as well as from a Blattabacteria sequencing effort, (ii) mapping single cell sequencing reads is shown for poribacteria to sister phylum representative Rhodopirellula Baltica SH1. The algorithm has been implemented in a web-server accessible at http://jane.bioapps.biozentrum.uni-wuerzburg.de. Conclusion Rapid prokaryotic EST mapping or mapping of sequence reads is achieved applying JANE even without knowing the cognate genome sequence. PMID:19943962

[A plane-based hand-eye calibration method for surgical robots].

PubMed

Zeng, Bowei; Meng, Fanle; Ding, Hui; Liu, Wenbo; Wu, Di; Wang, Guangzhi

2017-04-01

In order to calibrate the hand-eye transformation of the surgical robot and laser range finder (LRF), a calibration algorithm based on a planar template was designed. A mathematical model of the planar template had been given and the approach to address the equations had been derived. Aiming at the problems of the measurement error in a practical system, we proposed a new algorithm for selecting coplanar data. This algorithm can effectively eliminate considerable measurement error data to improve the calibration accuracy. Furthermore, three orthogonal planes were used to improve the calibration accuracy, in which a nonlinear optimization for hand-eye calibration was used. With the purpose of verifying the calibration precision, we used the LRF to measure some fixed points in different directions and a cuboid's surfaces. Experimental results indicated that the precision of a single planar template method was (1.37±0.24) mm, and that of the three orthogonal planes method was (0.37±0.05) mm. Moreover, the mean FRE of three-dimensional (3D) points was 0.24 mm and mean TRE was 0.26 mm. The maximum angle measurement error was 0.4 degree. Experimental results show that the method presented in this paper is effective with high accuracy and can meet the requirements of surgical robot precise location.

A study on low-cost, high-accuracy, and real-time stereo vision algorithms for UAV power line inspection

NASA Astrophysics Data System (ADS)

Wang, Hongyu; Zhang, Baomin; Zhao, Xun; Li, Cong; Lu, Cunyue

2018-04-01

Conventional stereo vision algorithms suffer from high levels of hardware resource utilization due to algorithm complexity, or poor levels of accuracy caused by inadequacies in the matching algorithm. To address these issues, we have proposed a stereo range-finding technique that produces an excellent balance between cost, matching accuracy and real-time performance, for power line inspection using UAV. This was achieved through the introduction of a special image preprocessing algorithm and a weighted local stereo matching algorithm, as well as the design of a corresponding hardware architecture. Stereo vision systems based on this technique have a lower level of resource usage and also a higher level of matching accuracy following hardware acceleration. To validate the effectiveness of our technique, a stereo vision system based on our improved algorithms were implemented using the Spartan 6 FPGA. In comparative experiments, it was shown that the system using the improved algorithms outperformed the system based on the unimproved algorithms, in terms of resource utilization and matching accuracy. In particular, Block RAM usage was reduced by 19%, and the improved system was also able to output range-finding data in real time.

SU-E-T-446: Group-Sparsity Based Angle Generation Method for Beam Angle Optimization

DOE Office of Scientific and Technical Information (OSTI.GOV)

Gao, H

2015-06-15

Purpose: This work is to develop the effective algorithm for beam angle optimization (BAO), with the emphasis on enabling further improvement from existing treatment-dependent templates based on clinical knowledge and experience. Methods: The proposed BAO algorithm utilizes a priori beam angle templates as the initial guess, and iteratively generates angular updates for this initial set, namely angle generation method, with improved dose conformality that is quantitatively measured by the objective function. That is, during each iteration, we select “the test angle” in the initial set, and use group-sparsity based fluence map optimization to identify “the candidate angle” for updating “themore » test angle”, for which all the angles in the initial set except “the test angle”, namely “the fixed set”, are set free, i.e., with no group-sparsity penalty, and the rest of angles including “the test angle” during this iteration are in “the working set”. And then “the candidate angle” is selected with the smallest objective function value from the angles in “the working set” with locally maximal group sparsity, and replaces “the test angle” if “the fixed set” with “the candidate angle” has a smaller objective function value by solving the standard fluence map optimization (with no group-sparsity regularization). Similarly other angles in the initial set are in turn selected as “the test angle” for angular updates and this chain of updates is iterated until no further new angular update is identified for a full loop. Results: The tests using the MGH public prostate dataset demonstrated the effectiveness of the proposed BAO algorithm. For example, the optimized angular set from the proposed BAO algorithm was better the MGH template. Conclusion: A new BAO algorithm is proposed based on the angle generation method via group sparsity, with improved dose conformality from the given template. Hao Gao was partially supported by the NSFC (#11405105), the 973 Program (#2015CB856000) and the Shanghai Pujiang Talent Program (#14PJ1404500)« less

Detection and analysis of microseismic events using a Matched Filtering Algorithm (MFA)

NASA Astrophysics Data System (ADS)

Caffagni, Enrico; Eaton, David W.; Jones, Joshua P.; van der Baan, Mirko

2016-07-01

A new Matched Filtering Algorithm (MFA) is proposed for detecting and analysing microseismic events recorded by downhole monitoring of hydraulic fracturing. This method requires a set of well-located template (`parent') events, which are obtained using conventional microseismic processing and selected on the basis of high signal-to-noise (S/N) ratio and representative spatial distribution of the recorded microseismicity. Detection and extraction of `child' events are based on stacked, multichannel cross-correlation of the continuous waveform data, using the parent events as reference signals. The location of a child event relative to its parent is determined using an automated process, by rotation of the multicomponent waveforms into the ray-centred co-ordinates of the parent and maximizing the energy of the stacked amplitude envelope within a search volume around the parent's hypocentre. After correction for geometrical spreading and attenuation, the relative magnitude of the child event is obtained automatically using the ratio of stacked envelope peak with respect to its parent. Since only a small number of parent events require interactive analysis such as picking P- and S-wave arrivals, the MFA approach offers the potential for significant reduction in effort for downhole microseismic processing. Our algorithm also facilitates the analysis of single-phase child events, that is, microseismic events for which only one of the S- or P-wave arrivals is evident due to unfavourable S/N conditions. A real-data example using microseismic monitoring data from four stages of an open-hole slickwater hydraulic fracture treatment in western Canada demonstrates that a sparse set of parents (in this case, 4.6 per cent of the originally located events) yields a significant (more than fourfold increase) in the number of located events compared with the original catalogue. Moreover, analysis of the new MFA catalogue suggests that this approach leads to more robust interpretation of the induced microseismicity and novel insights into dynamic rupture processes based on the average temporal (foreshock-aftershock) relationship of child events to parents.

Processing the Bouguer anomaly map of Biga and the surrounding area by the cellular neural network: application to the southwestern Marmara region

NASA Astrophysics Data System (ADS)

Aydogan, D.

2007-04-01

An image processing technique called the cellular neural network (CNN) approach is used in this study to locate geological features giving rise to gravity anomalies such as faults or the boundary of two geologic zones. CNN is a stochastic image processing technique based on template optimization using the neighborhood relationships of cells. These cells can be characterized by a functional block diagram that is typical of neural network theory. The functionality of CNN is described in its entirety by a number of small matrices (A, B and I) called the cloning template. CNN can also be considered to be a nonlinear convolution of these matrices. This template describes the strength of the nearest neighbor interconnections in the network. The recurrent perceptron learning algorithm (RPLA) is used in optimization of cloning template. The CNN and standard Canny algorithms were first tested on two sets of synthetic gravity data with the aim of checking the reliability of the proposed approach. The CNN method was compared with classical derivative techniques by applying the cross-correlation method (CC) to the same anomaly map as this latter approach can detect some features that are difficult to identify on the Bouguer anomaly maps. This approach was then applied to the Bouguer anomaly map of Biga and its surrounding area, in Turkey. Structural features in the area between Bandirma, Biga, Yenice and Gonen in the southwest Marmara region are investigated by applying the CNN and CC to the Bouguer anomaly map. Faults identified by these algorithms are generally in accordance with previously mapped surface faults. These examples show that the geologic boundaries can be detected from Bouguer anomaly maps using the cloning template approach. A visual evaluation of the outputs of the CNN and CC approaches is carried out, and the results are compared with each other. This approach provides quantitative solutions based on just a few assumptions, which makes the method more powerful than the classical methods.

77 FR 59444 - Self-Regulatory Organizations; Chicago Board Options Exchange, Incorporated; Notice of Filing and...

Federal Register 2010, 2011, 2012, 2013, 2014

2012-09-27

... provides a ``menu'' of matching algorithms to choose from when executing incoming electronic orders. The menu format allows the Exchange to utilize different matching algorithms on a class-by-class basis. The menu includes, among other choices, the ultimate matching algorithm (``UMA''), as well as price-time...

Context-Sensitive Grammar Transform: Compression and Pattern Matching

NASA Astrophysics Data System (ADS)

Maruyama, Shirou; Tanaka, Youhei; Sakamoto, Hiroshi; Takeda, Masayuki

A framework of context-sensitive grammar transform for speeding-up compressed pattern matching (CPM) is proposed. A greedy compression algorithm with the transform model is presented as well as a Knuth-Morris-Pratt (KMP)-type compressed pattern matching algorithm. The compression ratio is a match for gzip and Re-Pair, and the search speed of our CPM algorithm is almost twice faster than the KMP-type CPM algorithm on Byte-Pair-Encoding by Shibata et al.[18], and in the case of short patterns, faster than the Boyer-Moore-Horspool algorithm with the stopper encoding by Rautio et al.[14], which is regarded as one of the best combinations that allows a practically fast search.

Optimizing Approximate Weighted Matching on Nvidia Kepler K40

DOE Office of Scientific and Technical Information (OSTI.GOV)

Naim, Md; Manne, Fredrik; Halappanavar, Mahantesh

Matching is a fundamental graph problem with numerous applications in science and engineering. While algorithms for computing optimal matchings are difficult to parallelize, approximation algorithms on the other hand generally compute high quality solutions and are amenable to parallelization. In this paper, we present efficient implementations of the current best algorithm for half-approximate weighted matching, the Suitor algorithm, on Nvidia Kepler K-40 platform. We develop four variants of the algorithm that exploit hardware features to address key challenges for a GPU implementation. We also experiment with different combinations of work assigned to a warp. Using an exhaustive set ofmore » $269$ inputs, we demonstrate that the new implementation outperforms the previous best GPU algorithm by $10$ to $$100\\times$$ for over $100$ instances, and from $100$ to $$1000\\times$$ for $15$ instances. We also demonstrate up to $$20\\times$$ speedup relative to $2$ threads, and up to $$5\\times$$ relative to $16$ threads on Intel Xeon platform with $16$ cores for the same algorithm. The new algorithms and implementations provided in this paper will have a direct impact on several applications that repeatedly use matching as a key compute kernel. Further, algorithm designs and insights provided in this paper will benefit other researchers implementing graph algorithms on modern GPU architectures.« less

A parallel approximate string matching under Levenshtein distance on graphics processing units using warp-shuffle operations

PubMed Central

Ho, ThienLuan; Oh, Seung-Rohk

2017-01-01

Approximate string matching with k-differences has a number of practical applications, ranging from pattern recognition to computational biology. This paper proposes an efficient memory-access algorithm for parallel approximate string matching with k-differences on Graphics Processing Units (GPUs). In the proposed algorithm, all threads in the same GPUs warp share data using warp-shuffle operation instead of accessing the shared memory. Moreover, we implement the proposed algorithm by exploiting the memory structure of GPUs to optimize its performance. Experiment results for real DNA packages revealed that the performance of the proposed algorithm and its implementation archived up to 122.64 and 1.53 times compared to that of sequential algorithm on CPU and previous parallel approximate string matching algorithm on GPUs, respectively. PMID:29016700

History matching by spline approximation and regularization in single-phase areal reservoirs

NASA Technical Reports Server (NTRS)

Lee, T. Y.; Kravaris, C.; Seinfeld, J.

1986-01-01

An automatic history matching algorithm is developed based on bi-cubic spline approximations of permeability and porosity distributions and on the theory of regularization to estimate permeability or porosity in a single-phase, two-dimensional real reservoir from well pressure data. The regularization feature of the algorithm is used to convert the ill-posed history matching problem into a well-posed problem. The algorithm employs the conjugate gradient method as its core minimization method. A number of numerical experiments are carried out to evaluate the performance of the algorithm. Comparisons with conventional (non-regularized) automatic history matching algorithms indicate the superiority of the new algorithm with respect to the parameter estimates obtained. A quasioptimal regularization parameter is determined without requiring a priori information on the statistical properties of the observations.

Stereo Image Dense Matching by Integrating Sift and Sgm Algorithm

NASA Astrophysics Data System (ADS)

Zhou, Y.; Song, Y.; Lu, J.

2018-05-01

Semi-global matching(SGM) performs the dynamic programming by treating the different path directions equally. It does not consider the impact of different path directions on cost aggregation, and with the expansion of the disparity search range, the accuracy and efficiency of the algorithm drastically decrease. This paper presents a dense matching algorithm by integrating SIFT and SGM. It takes the successful matching pairs matched by SIFT as control points to direct the path in dynamic programming with truncating error propagation. Besides, matching accuracy can be improved by using the gradient direction of the detected feature points to modify the weights of the paths in different directions. The experimental results based on Middlebury stereo data sets and CE-3 lunar data sets demonstrate that the proposed algorithm can effectively cut off the error propagation, reduce disparity search range and improve matching accuracy.

Optimization of Stereo Matching in 3D Reconstruction Based on Binocular Vision

NASA Astrophysics Data System (ADS)

Gai, Qiyang

2018-01-01

Stereo matching is one of the key steps of 3D reconstruction based on binocular vision. In order to improve the convergence speed and accuracy in 3D reconstruction based on binocular vision, this paper adopts the combination method of polar constraint and ant colony algorithm. By using the line constraint to reduce the search range, an ant colony algorithm is used to optimize the stereo matching feature search function in the proposed search range. Through the establishment of the stereo matching optimization process analysis model of ant colony algorithm, the global optimization solution of stereo matching in 3D reconstruction based on binocular vision system is realized. The simulation results show that by the combining the advantage of polar constraint and ant colony algorithm, the stereo matching range of 3D reconstruction based on binocular vision is simplified, and the convergence speed and accuracy of this stereo matching process are improved.

The Design of SimpleITK.

PubMed

Lowekamp, Bradley C; Chen, David T; Ibáñez, Luis; Blezek, Daniel

2013-01-01

SimpleITK is a new interface to the Insight Segmentation and Registration Toolkit (ITK) designed to facilitate rapid prototyping, education and scientific activities via high level programming languages. ITK is a templated C++ library of image processing algorithms and frameworks for biomedical and other applications, and it was designed to be generic, flexible and extensible. Initially, ITK provided a direct wrapping interface to languages such as Python and Tcl through the WrapITK system. Unlike WrapITK, which exposed ITK's complex templated interface, SimpleITK was designed to provide an easy to use and simplified interface to ITK's algorithms. It includes procedural methods, hides ITK's demand driven pipeline, and provides a template-less layer. Also SimpleITK provides practical conveniences such as binary distribution packages and overloaded operators. Our user-friendly design goals dictated a departure from the direct interface wrapping approach of WrapITK, toward a new facade class structure that only exposes the required functionality, hiding ITK's extensive template use. Internally SimpleITK utilizes a manual description of each filter with code-generation and advanced C++ meta-programming to provide the higher-level interface, bringing the capabilities of ITK to a wider audience. SimpleITK is licensed as open source software library under the Apache License Version 2.0 and more information about downloading it can be found at http://www.simpleitk.org.

Implementation of an IMU Aided Image Stacking Algorithm in a Digital Camera for Unmanned Aerial Vehicles

PubMed Central

Audi, Ahmad; Pierrot-Deseilligny, Marc; Meynard, Christophe

2017-01-01

Images acquired with a long exposure time using a camera embedded on UAVs (Unmanned Aerial Vehicles) exhibit motion blur due to the erratic movements of the UAV. The aim of the present work is to be able to acquire several images with a short exposure time and use an image processing algorithm to produce a stacked image with an equivalent long exposure time. Our method is based on the feature point image registration technique. The algorithm is implemented on the light-weight IGN (Institut national de l’information géographique) camera, which has an IMU (Inertial Measurement Unit) sensor and an SoC (System on Chip)/FPGA (Field-Programmable Gate Array). To obtain the correct parameters for the resampling of the images, the proposed method accurately estimates the geometrical transformation between the first and the N-th images. Feature points are detected in the first image using the FAST (Features from Accelerated Segment Test) detector, then homologous points on other images are obtained by template matching using an initial position benefiting greatly from the presence of the IMU sensor. The SoC/FPGA in the camera is used to speed up some parts of the algorithm in order to achieve real-time performance as our ultimate objective is to exclusively write the resulting image to save bandwidth on the storage device. The paper includes a detailed description of the implemented algorithm, resource usage summary, resulting processing time, resulting images and block diagrams of the described architecture. The resulting stacked image obtained for real surveys does not seem visually impaired. An interesting by-product of this algorithm is the 3D rotation estimated by a photogrammetric method between poses, which can be used to recalibrate in real time the gyrometers of the IMU. Timing results demonstrate that the image resampling part of this algorithm is the most demanding processing task and should also be accelerated in the FPGA in future work. PMID:28718788

Implementation of an IMU Aided Image Stacking Algorithm in a Digital Camera for Unmanned Aerial Vehicles.

PubMed

Audi, Ahmad; Pierrot-Deseilligny, Marc; Meynard, Christophe; Thom, Christian

2017-07-18

Images acquired with a long exposure time using a camera embedded on UAVs (Unmanned Aerial Vehicles) exhibit motion blur due to the erratic movements of the UAV. The aim of the present work is to be able to acquire several images with a short exposure time and use an image processing algorithm to produce a stacked image with an equivalent long exposure time. Our method is based on the feature point image registration technique. The algorithm is implemented on the light-weight IGN (Institut national de l'information géographique) camera, which has an IMU (Inertial Measurement Unit) sensor and an SoC (System on Chip)/FPGA (Field-Programmable Gate Array). To obtain the correct parameters for the resampling of the images, the proposed method accurately estimates the geometrical transformation between the first and the N -th images. Feature points are detected in the first image using the FAST (Features from Accelerated Segment Test) detector, then homologous points on other images are obtained by template matching using an initial position benefiting greatly from the presence of the IMU sensor. The SoC/FPGA in the camera is used to speed up some parts of the algorithm in order to achieve real-time performance as our ultimate objective is to exclusively write the resulting image to save bandwidth on the storage device. The paper includes a detailed description of the implemented algorithm, resource usage summary, resulting processing time, resulting images and block diagrams of the described architecture. The resulting stacked image obtained for real surveys does not seem visually impaired. An interesting by-product of this algorithm is the 3D rotation estimated by a photogrammetric method between poses, which can be used to recalibrate in real time the gyrometers of the IMU. Timing results demonstrate that the image resampling part of this algorithm is the most demanding processing task and should also be accelerated in the FPGA in future work.

Dynamic displacement measurement of large-scale structures based on the Lucas-Kanade template tracking algorithm

NASA Astrophysics Data System (ADS)

Guo, Jie; Zhu, Chang`an

2016-01-01

The development of optics and computer technologies enables the application of the vision-based technique that uses digital cameras to the displacement measurement of large-scale structures. Compared with traditional contact measurements, vision-based technique allows for remote measurement, has a non-intrusive characteristic, and does not necessitate mass introduction. In this study, a high-speed camera system is developed to complete the displacement measurement in real time. The system consists of a high-speed camera and a notebook computer. The high-speed camera can capture images at a speed of hundreds of frames per second. To process the captured images in computer, the Lucas-Kanade template tracking algorithm in the field of computer vision is introduced. Additionally, a modified inverse compositional algorithm is proposed to reduce the computing time of the original algorithm and improve the efficiency further. The modified algorithm can rapidly accomplish one displacement extraction within 1 ms without having to install any pre-designed target panel onto the structures in advance. The accuracy and the efficiency of the system in the remote measurement of dynamic displacement are demonstrated in the experiments on motion platform and sound barrier on suspension viaduct. Experimental results show that the proposed algorithm can extract accurate displacement signal and accomplish the vibration measurement of large-scale structures.

Fast adaptive diamond search algorithm for block-matching motion estimation using spatial correlation

NASA Astrophysics Data System (ADS)

Park, Sang-Gon; Jeong, Dong-Seok

2000-12-01

In this paper, we propose a fast adaptive diamond search algorithm (FADS) for block matching motion estimation. Many fast motion estimation algorithms reduce the computational complexity by the UESA (Unimodal Error Surface Assumption) where the matching error monotonically increases as the search moves away from the global minimum point. Recently, many fast BMAs (Block Matching Algorithms) make use of the fact that global minimum points in real world video sequences are centered at the position of zero motion. But these BMAs, especially in large motion, are easily trapped into the local minima and result in poor matching accuracy. So, we propose a new motion estimation algorithm using the spatial correlation among the neighboring blocks. We move the search origin according to the motion vectors of the spatially neighboring blocks and their MAEs (Mean Absolute Errors). The computer simulation shows that the proposed algorithm has almost the same computational complexity with DS (Diamond Search), but enhances PSNR. Moreover, the proposed algorithm gives almost the same PSNR as that of FS (Full Search), even for the large motion with half the computational load.

GALAHAD: 1. Pharmacophore identification by hypermolecular alignment of ligands in 3D

NASA Astrophysics Data System (ADS)

Richmond, Nicola J.; Abrams, Charlene A.; Wolohan, Philippa R. N.; Abrahamian, Edmond; Willett, Peter; Clark, Robert D.

2006-09-01

Alignment of multiple ligands based on shared pharmacophoric and pharmacosteric features is a long-recognized challenge in drug discovery and development. This is particularly true when the spatial overlap between structures is incomplete, in which case no good template molecule is likely to exist. Pair-wise rigid ligand alignment based on linear assignment (the LAMDA algorithm) has the potential to address this problem (Richmond et al. in J Mol Graph Model 23:199-209, 2004). Here we present the version of LAMDA embodied in the GALAHAD program, which carries out multi-way alignments by iterative construction of hypermolecules that retain the aggregate as well as the individual attributes of the ligands. We have also generalized the cost function from being purely atom-based to being one that operates on ionic, hydrogen bonding, hydrophobic and steric features. Finally, we have added the ability to generate useful partial-match 3D search queries from the hypermolecules obtained. By running frozen conformations through the GALAHAD program, one can utilize the extended version of LAMDA to generate pharmacophores and pharmacosteres that agree well with crystal structure alignments for a range of literature datasets, with minor adjustments of the default parameters generating even better models. Allowing for inclusion of partial match constraints in the queries yields pharmacophores that are consistently a superset of full-match pharmacophores identified in previous analyses, with the additional features representing points of potentially beneficial interaction with the target.

Conditional Random Field-Based Offline Map Matching for Indoor Environments

PubMed Central

Bataineh, Safaa; Bahillo, Alfonso; Díez, Luis Enrique; Onieva, Enrique; Bataineh, Ikram

2016-01-01

In this paper, we present an offline map matching technique designed for indoor localization systems based on conditional random fields (CRF). The proposed algorithm can refine the results of existing indoor localization systems and match them with the map, using loose coupling between the existing localization system and the proposed map matching technique. The purpose of this research is to investigate the efficiency of using the CRF technique in offline map matching problems for different scenarios and parameters. The algorithm was applied to several real and simulated trajectories of different lengths. The results were then refined and matched with the map using the CRF algorithm. PMID:27537892

Conditional Random Field-Based Offline Map Matching for Indoor Environments.

PubMed

Bataineh, Safaa; Bahillo, Alfonso; Díez, Luis Enrique; Onieva, Enrique; Bataineh, Ikram

2016-08-16

In this paper, we present an offline map matching technique designed for indoor localization systems based on conditional random fields (CRF). The proposed algorithm can refine the results of existing indoor localization systems and match them with the map, using loose coupling between the existing localization system and the proposed map matching technique. The purpose of this research is to investigate the efficiency of using the CRF technique in offline map matching problems for different scenarios and parameters. The algorithm was applied to several real and simulated trajectories of different lengths. The results were then refined and matched with the map using the CRF algorithm.

A Multi-Scale Settlement Matching Algorithm Based on ARG

NASA Astrophysics Data System (ADS)

Yue, Han; Zhu, Xinyan; Chen, Di; Liu, Lingjia

2016-06-01

Homonymous entity matching is an important part of multi-source spatial data integration, automatic updating and change detection. Considering the low accuracy of existing matching methods in dealing with matching multi-scale settlement data, an algorithm based on Attributed Relational Graph (ARG) is proposed. The algorithm firstly divides two settlement scenes at different scales into blocks by small-scale road network and constructs local ARGs in each block. Then, ascertains candidate sets by merging procedures and obtains the optimal matching pairs by comparing the similarity of ARGs iteratively. Finally, the corresponding relations between settlements at large and small scales are identified. At the end of this article, a demonstration is presented and the results indicate that the proposed algorithm is capable of handling sophisticated cases.

Multiple objects tracking with HOGs matching in circular windows

NASA Astrophysics Data System (ADS)

Miramontes-Jaramillo, Daniel; Kober, Vitaly; Díaz-Ramírez, Víctor H.

2014-09-01

In recent years tracking applications with development of new technologies like smart TVs, Kinect, Google Glass and Oculus Rift become very important. When tracking uses a matching algorithm, a good prediction algorithm is required to reduce the search area for each object to be tracked as well as processing time. In this work, we analyze the performance of different tracking algorithms based on prediction and matching for a real-time tracking multiple objects. The used matching algorithm utilizes histograms of oriented gradients. It carries out matching in circular windows, and possesses rotation invariance and tolerance to viewpoint and scale changes. The proposed algorithm is implemented in a personal computer with GPU, and its performance is analyzed in terms of processing time in real scenarios. Such implementation takes advantage of current technologies and helps to process video sequences in real-time for tracking several objects at the same time.

Computing Maximum Cardinality Matchings in Parallel on Bipartite Graphs via Tree-Grafting

DOE Office of Scientific and Technical Information (OSTI.GOV)

Azad, Ariful; Buluc, Aydn; Pothen, Alex

It is difficult to obtain high performance when computing matchings on parallel processors because matching algorithms explicitly or implicitly search for paths in the graph, and when these paths become long, there is little concurrency. In spite of this limitation, we present a new algorithm and its shared-memory parallelization that achieves good performance and scalability in computing maximum cardinality matchings in bipartite graphs. This algorithm searches for augmenting paths via specialized breadth-first searches (BFS) from multiple source vertices, hence creating more parallelism than single source algorithms. Algorithms that employ multiple-source searches cannot discard a search tree once no augmenting pathmore » is discovered from the tree, unlike algorithms that rely on single-source searches. We describe a novel tree-grafting method that eliminates most of the redundant edge traversals resulting from this property of multiple-source searches. We also employ the recent direction-optimizing BFS algorithm as a subroutine to discover augmenting paths faster. Our algorithm compares favorably with the current best algorithms in terms of the number of edges traversed, the average augmenting path length, and the number of iterations. Here, we provide a proof of correctness for our algorithm. Our NUMA-aware implementation is scalable to 80 threads of an Intel multiprocessor and to 240 threads on an Intel Knights Corner coprocessor. On average, our parallel algorithm runs an order of magnitude faster than the fastest algorithms available. The performance improvement is more significant on graphs with small matching number.« less

Computing Maximum Cardinality Matchings in Parallel on Bipartite Graphs via Tree-Grafting

DOE PAGES

Azad, Ariful; Buluc, Aydn; Pothen, Alex

2016-03-24

It is difficult to obtain high performance when computing matchings on parallel processors because matching algorithms explicitly or implicitly search for paths in the graph, and when these paths become long, there is little concurrency. In spite of this limitation, we present a new algorithm and its shared-memory parallelization that achieves good performance and scalability in computing maximum cardinality matchings in bipartite graphs. This algorithm searches for augmenting paths via specialized breadth-first searches (BFS) from multiple source vertices, hence creating more parallelism than single source algorithms. Algorithms that employ multiple-source searches cannot discard a search tree once no augmenting pathmore » is discovered from the tree, unlike algorithms that rely on single-source searches. We describe a novel tree-grafting method that eliminates most of the redundant edge traversals resulting from this property of multiple-source searches. We also employ the recent direction-optimizing BFS algorithm as a subroutine to discover augmenting paths faster. Our algorithm compares favorably with the current best algorithms in terms of the number of edges traversed, the average augmenting path length, and the number of iterations. Here, we provide a proof of correctness for our algorithm. Our NUMA-aware implementation is scalable to 80 threads of an Intel multiprocessor and to 240 threads on an Intel Knights Corner coprocessor. On average, our parallel algorithm runs an order of magnitude faster than the fastest algorithms available. The performance improvement is more significant on graphs with small matching number.« less

Automating Embedded Analysis Capabilities and Managing Software Complexity in Multiphysics Simulation, Part I: Template-Based Generic Programming

DOE PAGES

Pawlowski, Roger P.; Phipps, Eric T.; Salinger, Andrew G.

2012-01-01

An approach for incorporating embedded simulation and analysis capabilities in complex simulation codes through template-based generic programming is presented. This approach relies on templating and operator overloading within the C++ language to transform a given calculation into one that can compute a variety of additional quantities that are necessary for many state-of-the-art simulation and analysis algorithms. An approach for incorporating these ideas into complex simulation codes through general graph-based assembly is also presented. These ideas have been implemented within a set of packages in the Trilinos framework and are demonstrated on a simple problem from chemical engineering.

In induced reconstructions of Si(1 1 1) as superlattice matched epitaxial templates for InN growth

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kuyyalil, Jithesh; Tangi, Malleswararao; Shivaprasad, S.M., E-mail: smsprasad@jncasr.ac.in

Graphical abstract: Display Omitted Highlights: ► A novel growth method to form InN at low growth temperatures. ► Use of Si reconstruction as a growth template for group III nitrides. ► Band gap variation of InN – Moss–Burstein shift – non-parabolic conduction band for InN. ► Super lattice matching epitaxy of metal induced reconstructions with III–V unit cell. -- Abstract: Indium induced surface reconstructions of Si(1 1 1)-7 × 7 are used as templates to grow high quality InN. We grow InN on Si(1 1 1)-7 × 7, Si(1 1 1)-4 × 1-In and Si(1 1 1)-1 × 1-In reconstructedmore » surfaces and study the quality of the films formed using complementary characterization tools. InN grown on Si(1 1 1)-1 × 1-In reconstruction shows superior film quality with lowest band-edge emission having a narrow full width at half maximum, intense and narrow 0 0 0 2 X-ray diffraction, low surface roughness and carrier concentration an order lower than other samples. We attribute the high quality of the film formed at 300 °C to the integral matching of InN and super lattice dimensions, we also study the reasons for the band gap variation of InN in the literature. Present study demonstrates the proposed Superlattice Matched Epitaxy can be a general approach to grow good quality InN at much lower growth temperature on compatible In induced reconstructions of the Si surface.« less

Generating cancelable fingerprint templates.

PubMed

Ratha, Nalini K; Chikkerur, Sharat; Connell, Jonathan H; Bolle, Ruud M

2007-04-01

Biometrics-based authentication systems offer obvious usability advantages over traditional password and token-based authentication schemes. However, biometrics raises several privacy concerns. A biometric is permanently associated with a user and cannot be changed. Hence, if a biometric identifier is compromised, it is lost forever and possibly for every application where the biometric is used. Moreover, if the same biometric is used in multiple applications, a user can potentially be tracked from one application to the next by cross-matching biometric databases. In this paper, we demonstrate several methods to generate multiple cancelable identifiers from fingerprint images to overcome these problems. In essence, a user can be given as many biometric identifiers as needed by issuing a new transformation "key." The identifiers can be cancelled and replaced when compromised. We empirically compare the performance of several algorithms such as Cartesian, polar, and surface folding transformations of the minutiae positions. It is demonstrated through multiple experiments that we can achieve revocability and prevent cross-matching of biometric databases. It is also shown that the transforms are noninvertible by demonstrating that it is computationally as hard to recover the original biometric identifier from a transformed version as by randomly guessing. Based on these empirical results and a theoretical analysis we conclude that feature-level cancelable biometric construction is practicable in large biometric deployments.

Assessment of Homology Templates and an Anesthetic Binding Site within the γ-Aminobutyric Acid Receptor

PubMed Central

Bertaccini, Edward J.; Yoluk, Ozge; Lindahl, Erik R.; Trudell, James R.

2013-01-01

Background Anesthetics mediate portions of their activity via modulation of the γ-aminobutyric acid receptor (GABAaR). While its molecular structure remains unknown, significant progress has been made towards understanding its interactions with anesthetics via molecular modeling. Methods The structure of the torpedo acetylcholine receptor (nAChRα), the structures of the α4 and β2 subunits of the human nAChR, the structures of the eukaryotic glutamate-gated chloride channel (GluCl), and the prokaryotic pH sensing channels, from Gloeobacter violaceus and Erwinia chrysanthemi, were aligned with the SAlign and 3DMA algorithms. A multiple sequence alignment from these structures and those of the GABAaR was performed with ClustalW. The Modeler and Rosetta algorithms independently created three-dimensional constructs of the GABAaR from the GluCl template. The CDocker algorithm docked a congeneric series of propofol derivatives into the binding pocket and scored calculated binding affinities for correlation with known GABAaR potentiation EC50’s. Results Multiple structure alignments of templates revealed a clear consensus of residue locations relevant to anesthetic effects except for torpedo nAChR. Within the GABAaR models generated from GluCl, the residues notable for modulating anesthetic action within transmembrane segments 1, 2, and 3 converged on the intersubunit interface between alpha and beta subunits. Docking scores of a propofol derivative series into this binding site showed strong linear correlation with GABAaR potentiation EC50. Conclusion Consensus structural alignment based on homologous templates revealed an intersubunit anesthetic binding cavity within the transmembrane domain of the GABAaR, which showed correlation of ligand docking scores with experimentally measured GABAaR potentiation. PMID:23770602

Assessment of homology templates and an anesthetic binding site within the γ-aminobutyric acid receptor.

PubMed

Bertaccini, Edward J; Yoluk, Ozge; Lindahl, Erik R; Trudell, James R

2013-11-01

Anesthetics mediate portions of their activity via modulation of the γ-aminobutyric acid receptor (GABAaR). Although its molecular structure remains unknown, significant progress has been made toward understanding its interactions with anesthetics via molecular modeling. The structure of the torpedo acetylcholine receptor (nAChRα), the structures of the α4 and β2 subunits of the human nAChR, the structures of the eukaryotic glutamate-gated chloride channel (GluCl), and the prokaryotic pH-sensing channels, from Gloeobacter violaceus and Erwinia chrysanthemi, were aligned with the SAlign and 3DMA algorithms. A multiple sequence alignment from these structures and those of the GABAaR was performed with ClustalW. The Modeler and Rosetta algorithms independently created three-dimensional constructs of the GABAaR from the GluCl template. The CDocker algorithm docked a congeneric series of propofol derivatives into the binding pocket and scored calculated binding affinities for correlation with known GABAaR potentiation EC50s. Multiple structure alignments of templates revealed a clear consensus of residue locations relevant to anesthetic effects except for torpedo nAChR. Within the GABAaR models generated from GluCl, the residues notable for modulating anesthetic action within transmembrane segments 1, 2, and 3 converged on the intersubunit interface between α and β subunits. Docking scores of a propofol derivative series into this binding site showed strong linear correlation with GABAaR potentiation EC50. Consensus structural alignment based on homologous templates revealed an intersubunit anesthetic binding cavity within the transmembrane domain of the GABAaR, which showed a correlation of ligand docking scores with experimentally measured GABAaR potentiation.

17 CFR Appendix A to Part 38 - Guidance on Compliance With Designation Criteria

Code of Federal Regulations, 2011 CFR

2011-04-01

...-matching algorithm and order entry procedures. An application involving a trade-matching algorithm that is... algorithm. (b) A designated contract market's specifications on initial and periodic objective testing and...

17 CFR Appendix A to Part 38 - Guidance on Compliance With Designation Criteria

Code of Federal Regulations, 2012 CFR

2012-04-01

...-matching algorithm and order entry procedures. An application involving a trade-matching algorithm that is... algorithm. (b) A designated contract market's specifications on initial and periodic objective testing and...

SU-G-JeP3-01: A Method to Quantify Lung SBRT Target Localization Accuracy Based On Digitally Reconstructed Fluoroscopy

DOE Office of Scientific and Technical Information (OSTI.GOV)

Lafata, K; Ren, L; Cai, J

2016-06-15

Purpose: To develop a methodology based on digitally-reconstructed-fluoroscopy (DRF) to quantitatively assess target localization accuracy of lung SBRT, and to evaluate using both a dynamic digital phantom and a patient dataset. Methods: For each treatment field, a 10-phase DRF is generated based on the planning 4DCT. Each frame is pre-processed with a morphological top-hat filter, and corresponding beam apertures are projected to each detector plane. A template-matching algorithm based on cross-correlation is used to detect the tumor location in each frame. Tumor motion relative beam aperture is extracted in the superior-inferior direction based on each frame’s impulse response to themore » template, and the mean tumor position (MTP) is calculated as the average tumor displacement. The DRF template coordinates are then transferred to the corresponding MV-cine dataset, which is retrospectively filtered as above. The treatment MTP is calculated within each field’s projection space, relative to the DRF-defined template. The field’s localization error is defined as the difference between the DRF-derived-MTP (planning) and the MV-cine-derived-MTP (delivery). A dynamic digital phantom was used to assess the algorithm’s ability to detect intra-fractional changes in patient alignment, by simulating different spatial variations in the MV-cine and calculating the corresponding change in MTP. Inter-and-intra-fractional variation, IGRT accuracy, and filtering effects were investigated on a patient dataset. Results: Phantom results demonstrated a high accuracy in detecting both translational and rotational variation. The lowest localization error of the patient dataset was achieved at each fraction’s first field (mean=0.38mm), with Fx3 demonstrating a particularly strong correlation between intra-fractional motion-caused localization error and treatment progress. Filtering significantly improved tracking visibility in both the DRF and MV-cine images. Conclusion: We have developed and evaluated a methodology to quantify lung SBRT target localization accuracy based on digitally-reconstructed-fluoroscopy. Our approach may be useful in potentially reducing treatment margins to optimize lung SBRT outcomes. R01-184173.« less

Patch Based Synthesis of Whole Head MR Images: Application to EPI Distortion Correction.

PubMed

Roy, Snehashis; Chou, Yi-Yu; Jog, Amod; Butman, John A; Pham, Dzung L

2016-10-01

Different magnetic resonance imaging pulse sequences are used to generate image contrasts based on physical properties of tissues, which provide different and often complementary information about them. Therefore multiple image contrasts are useful for multimodal analysis of medical images. Often, medical image processing algorithms are optimized for particular image contrasts. If a desirable contrast is unavailable, contrast synthesis (or modality synthesis) methods try to "synthesize" the unavailable constrasts from the available ones. Most of the recent image synthesis methods generate synthetic brain images, while whole head magnetic resonance (MR) images can also be useful for many applications. We propose an atlas based patch matching algorithm to synthesize T 2 -w whole head (including brain, skull, eyes etc) images from T 1 -w images for the purpose of distortion correction of diffusion weighted MR images. The geometric distortion in diffusion MR images due to in-homogeneous B 0 magnetic field are often corrected by non-linearly registering the corresponding b = 0 image with zero diffusion gradient to an undistorted T 2 -w image. We show that our synthetic T 2 -w images can be used as a template in absence of a real T 2 -w image. Our patch based method requires multiple atlases with T 1 and T 2 to be registeLowRes to a given target T 1 . Then for every patch on the target, multiple similar looking matching patches are found on the atlas T 1 images and corresponding patches on the atlas T 2 images are combined to generate a synthetic T 2 of the target. We experimented on image data obtained from 44 patients with traumatic brain injury (TBI), and showed that our synthesized T 2 images produce more accurate distortion correction than a state-of-the-art registration based image synthesis method.

Unimodular sequence design under frequency hopping communication compatibility requirements

NASA Astrophysics Data System (ADS)

Ge, Peng; Cui, Guolong; Kong, Lingjiang; Yang, Jianyu

2016-12-01

The integrated design for both radar and anonymous communication has drawn more attention recently since wireless communication system appeals to enhance security and reliability. Given the frequency hopping (FH) communication system, an effective way to realize integrated design is to meet the spectrum compatibility between these two systems. The paper deals with a unimodular sequence design technique which considers optimizing both the spectrum compatibility and peak sidelobes levels (PSL) of auto-correlation function (ACF). The spectrum compatibility requirement realizes anonymous communication for the FH system and provides this system lower probability of intercept (LPI) since the spectrum of the FH system is hidden in that of the radar system. The proposed algorithm, named generalized fitting template (GFT) technique, converts the sequence optimization design problem to a iterative fitting process. In this process, the power spectrum density (PSD) and PSL behaviors of the generated sequences fit both PSD and PSL templates progressively. Two templates are established based on the spectrum compatibility requirement and the expected PSL. As noted, in order to ensure the communication security and reliability, spectrum compatibility requirement is given a higher priority to achieve in the GFT algorithm. This algorithm realizes this point by adjusting the weight adaptively between these two terms during the iteration process. The simulation results are analyzed in terms of bit error rate (BER), PSD, PSL, and signal-interference rate (SIR) for both the radar and FH systems. The performance of GFT is compared with SCAN, CAN, FRE, CYC, and MAT algorithms in the above aspects, which shows its good effectiveness.

MRI non-uniformity correction through interleaved bias estimation and B-spline deformation with a template.

PubMed

Fletcher, E; Carmichael, O; Decarli, C

2012-01-01

We propose a template-based method for correcting field inhomogeneity biases in magnetic resonance images (MRI) of the human brain. At each algorithm iteration, the update of a B-spline deformation between an unbiased template image and the subject image is interleaved with estimation of a bias field based on the current template-to-image alignment. The bias field is modeled using a spatially smooth thin-plate spline interpolation based on ratios of local image patch intensity means between the deformed template and subject images. This is used to iteratively correct subject image intensities which are then used to improve the template-to-image deformation. Experiments on synthetic and real data sets of images with and without Alzheimer's disease suggest that the approach may have advantages over the popular N3 technique for modeling bias fields and narrowing intensity ranges of gray matter, white matter, and cerebrospinal fluid. This bias field correction method has the potential to be more accurate than correction schemes based solely on intrinsic image properties or hypothetical image intensity distributions.

MRI Non-Uniformity Correction Through Interleaved Bias Estimation and B-Spline Deformation with a Template*

PubMed Central

Fletcher, E.; Carmichael, O.; DeCarli, C.

2013-01-01

We propose a template-based method for correcting field inhomogeneity biases in magnetic resonance images (MRI) of the human brain. At each algorithm iteration, the update of a B-spline deformation between an unbiased template image and the subject image is interleaved with estimation of a bias field based on the current template-to-image alignment. The bias field is modeled using a spatially smooth thin-plate spline interpolation based on ratios of local image patch intensity means between the deformed template and subject images. This is used to iteratively correct subject image intensities which are then used to improve the template-to-image deformation. Experiments on synthetic and real data sets of images with and without Alzheimer’s disease suggest that the approach may have advantages over the popular N3 technique for modeling bias fields and narrowing intensity ranges of gray matter, white matter, and cerebrospinal fluid. This bias field correction method has the potential to be more accurate than correction schemes based solely on intrinsic image properties or hypothetical image intensity distributions. PMID:23365843

Respiratory rate estimation during triage of children in hospitals.

PubMed

Shah, Syed Ahmar; Fleming, Susannah; Thompson, Matthew; Tarassenko, Lionel

2015-01-01

Accurate assessment of a child's health is critical for appropriate allocation of medical resources and timely delivery of healthcare in Emergency Departments. The accurate measurement of vital signs is a key step in the determination of the severity of illness and respiratory rate is currently the most difficult vital sign to measure accurately. Several previous studies have attempted to extract respiratory rate from photoplethysmogram (PPG) recordings. However, the majority have been conducted in controlled settings using PPG recordings from healthy subjects. In many studies, manual selection of clean sections of PPG recordings was undertaken before assessing the accuracy of the signal processing algorithms developed. Such selection procedures are not appropriate in clinical settings. A major limitation of AR modelling, previously applied to respiratory rate estimation, is an appropriate selection of model order. This study developed a novel algorithm that automatically estimates respiratory rate from a median spectrum constructed applying multiple AR models to processed PPG segments acquired with pulse oximetry using a finger probe. Good-quality sections were identified using a dynamic template-matching technique to assess PPG signal quality. The algorithm was validated on 205 children presenting to the Emergency Department at the John Radcliffe Hospital, Oxford, UK, with reference respiratory rates up to 50 breaths per minute estimated by paediatric nurses. At the time of writing, the authors are not aware of any other study that has validated respiratory rate estimation using data collected from over 200 children in hospitals during routine triage.

Adding a Zero-Crossing Count to Spectral Information in Template-Based Speech Recognition

DTIC Science & Technology

1982-01-01

incorporation of zero-crossing information into the spectral representation used in a template-matching system ( cIcADA ). An analysis of zero-crossing data for an...procedure to be used. The work described in this paper was done using the CICADA system developed at Carnegie-Mellon University [Alleva 81, Waibel 801... CICADA uses a representation based on a compression of the short-term spectrum according to a 16 coefficient mel scale. Let us consider the CICADA

Automated protein structure modeling in CASP9 by I-TASSER pipeline combined with QUARK-based ab initio folding and FG-MD-based structure refinement

PubMed Central

Xu, Dong; Zhang, Jian; Roy, Ambrish; Zhang, Yang

2011-01-01

I-TASSER is an automated pipeline for protein tertiary structure prediction using multiple threading alignments and iterative structure assembly simulations. In CASP9 experiments, two new algorithms, QUARK and FG-MD, were added to the I-TASSER pipeline for improving the structural modeling accuracy. QUARK is a de novo structure prediction algorithm used for structure modeling of proteins that lack detectable template structures. For distantly homologous targets, QUARK models are found useful as a reference structure for selecting good threading alignments and guiding the I-TASSER structure assembly simulations. FG-MD is an atomic-level structural refinement program that uses structural fragments collected from the PDB structures to guide molecular dynamics simulation and improve the local structure of predicted model, including hydrogen-bonding networks, torsion angles and steric clashes. Despite considerable progress in both the template-based and template-free structure modeling, significant improvements on protein target classification, domain parsing, model selection, and ab initio folding of beta-proteins are still needed to further improve the I-TASSER pipeline. PMID:22069036

Improving threading algorithms for remote homology modeling by combining fragment and template comparisons

PubMed Central

Zhou, Hongyi; Skolnick, Jeffrey

2010-01-01

In this work, we develop a method called FTCOM for assessing the global quality of protein structural models for targets of medium and hard difficulty (remote homology) produced by structure prediction approaches such as threading or ab initio structure prediction. FTCOM requires the Cα coordinates of full length models and assesses model quality based on fragment comparison and a score derived from comparison of the model to top threading templates. On a set of 361 medium/hard targets, FTCOM was applied to and assessed for its ability to improve upon the results from the SP3, SPARKS, PROSPECTOR_3, and PRO-SP3-TASSER threading algorithms. The average TM-score improves by 5%–10% for the first selected model by the new method over models obtained by the original selection procedure in the respective threading methods. Moreover the number of foldable targets (TM-score ≥0.4) increases from least 7.6% for SP3 to 54% for SPARKS. Thus, FTCOM is a promising approach to template selection. PMID:20455261

Vision-based method for detecting driver drowsiness and distraction in driver monitoring system

NASA Astrophysics Data System (ADS)

Jo, Jaeik; Lee, Sung Joo; Jung, Ho Gi; Park, Kang Ryoung; Kim, Jaihie

2011-12-01

Most driver-monitoring systems have attempted to detect either driver drowsiness or distraction, although both factors should be considered for accident prevention. Therefore, we propose a new driver-monitoring method considering both factors. We make the following contributions. First, if the driver is looking ahead, drowsiness detection is performed; otherwise, distraction detection is performed. Thus, the computational cost and eye-detection error can be reduced. Second, we propose a new eye-detection algorithm that combines adaptive boosting, adaptive template matching, and blob detection with eye validation, thereby reducing the eye-detection error and processing time significantly, which is hardly achievable using a single method. Third, to enhance eye-detection accuracy, eye validation is applied after initial eye detection, using a support vector machine based on appearance features obtained by principal component analysis (PCA) and linear discriminant analysis (LDA). Fourth, we propose a novel eye state-detection algorithm that combines appearance features obtained using PCA and LDA, with statistical features such as the sparseness and kurtosis of the histogram from the horizontal edge image of the eye. Experimental results showed that the detection accuracies of the eye region and eye states were 99 and 97%, respectively. Both driver drowsiness and distraction were detected with a success rate of 98%.

Meta-image navigation augmenters for GPS denied mountain navigation of small UAS

NASA Astrophysics Data System (ADS)

Wang, Teng; ćelik, Koray; Somani, Arun K.

2014-06-01

We present a novel approach to use mountain drainage patterns for GPS-Denied navigation of small unmanned aerial systems (UAS) such as the ScanEagle, utilizing a down-looking fixed focus monocular imager. Our proposal allows extension of missions to GPS-denied mountain areas, with no assumption of human-made geographic objects. We leverage the analogy between mountain drainage patterns, human arteriograms, and human fingerprints, to match local drainage patterns to Graphics Processing Unit (GPU) rendered parallax occlusion maps of geo-registered radar returns (GRRR). Details of our actual GPU algorithm is beyond the subject of this paper, and is planned as a future paper. The matching occurs in real-time, while GRRR data is loaded on-board the aircraft pre-mission, so as not to require a scanning aperture radar during the mission. For recognition purposes, we represent a given mountain area with a set of spatially distributed mountain minutiae, i.e., details found in the drainage patterns, so that conventional minutiae-based fingerprint matching approaches can be used to match real-time camera image against template images in the training set. We use medical arteriography processing techniques to extract the patterns. The minutiae-based representation of mountains is achieved by first exposing mountain ridges and valleys with a series of filters and then extracting mountain minutiae from these ridges/valleys. Our results are experimentally validated on actual terrain data and show the effectiveness of minutiae-based mountain representation method. Furthermore, we study how to select landmarks for UAS navigation based on the proposed mountain representation and give a set of examples to show its feasibility. This research was in part funded by Rockwell Collins Inc.

The protein structure prediction problem could be solved using the current PDB library

PubMed Central

Zhang, Yang; Skolnick, Jeffrey

2005-01-01

For single-domain proteins, we examine the completeness of the structures in the current Protein Data Bank (PDB) library for use in full-length model construction of unknown sequences. To address this issue, we employ a comprehensive benchmark set of 1,489 medium-size proteins that cover the PDB at the level of 35% sequence identity and identify templates by structure alignment. With homologous proteins excluded, we can always find similar folds to native with an average rms deviation (RMSD) from native of 2.5 Å with ≈82% alignment coverage. These template structures often contain a significant number of insertions/deletions. The tasser algorithm was applied to build full-length models, where continuous fragments are excised from the top-scoring templates and reassembled under the guide of an optimized force field, which includes consensus restraints taken from the templates and knowledge-based statistical potentials. For almost all targets (except for 2/1,489), the resultant full-length models have an RMSD to native below 6 Å (97% of them below 4 Å). On average, the RMSD of full-length models is 2.25 Å, with aligned regions improved from 2.5 Å to 1.88 Å, comparable with the accuracy of low-resolution experimental structures. Furthermore, starting from state-of-the-art structural alignments, we demonstrate a methodology that can consistently bring template-based alignments closer to native. These results are highly suggestive that the protein-folding problem can in principle be solved based on the current PDB library by developing efficient fold recognition algorithms that can recover such initial alignments. PMID:15653774

A 2D eye gaze estimation system with low-resolution webcam images

NASA Astrophysics Data System (ADS)

Ince, Ibrahim Furkan; Kim, Jin Woo

2011-12-01

In this article, a low-cost system for 2D eye gaze estimation with low-resolution webcam images is presented. Two algorithms are proposed for this purpose, one for the eye-ball detection with stable approximate pupil-center and the other one for the eye movements' direction detection. Eyeball is detected using deformable angular integral search by minimum intensity (DAISMI) algorithm. Deformable template-based 2D gaze estimation (DTBGE) algorithm is employed as a noise filter for deciding the stable movement decisions. While DTBGE employs binary images, DAISMI employs gray-scale images. Right and left eye estimates are evaluated separately. DAISMI finds the stable approximate pupil-center location by calculating the mass-center of eyeball border vertices to be employed for initial deformable template alignment. DTBGE starts running with initial alignment and updates the template alignment with resulting eye movements and eyeball size frame by frame. The horizontal and vertical deviation of eye movements through eyeball size is considered as if it is directly proportional with the deviation of cursor movements in a certain screen size and resolution. The core advantage of the system is that it does not employ the real pupil-center as a reference point for gaze estimation which is more reliable against corneal reflection. Visual angle accuracy is used for the evaluation and benchmarking of the system. Effectiveness of the proposed system is presented and experimental results are shown.

Nonuniformity correction for an infrared focal plane array based on diamond search block matching.

PubMed

Sheng-Hui, Rong; Hui-Xin, Zhou; Han-Lin, Qin; Rui, Lai; Kun, Qian

2016-05-01

In scene-based nonuniformity correction algorithms, artificial ghosting and image blurring degrade the correction quality severely. In this paper, an improved algorithm based on the diamond search block matching algorithm and the adaptive learning rate is proposed. First, accurate transform pairs between two adjacent frames are estimated by the diamond search block matching algorithm. Then, based on the error between the corresponding transform pairs, the gradient descent algorithm is applied to update correction parameters. During the process of gradient descent, the local standard deviation and a threshold are utilized to control the learning rate to avoid the accumulation of matching error. Finally, the nonuniformity correction would be realized by a linear model with updated correction parameters. The performance of the proposed algorithm is thoroughly studied with four real infrared image sequences. Experimental results indicate that the proposed algorithm can reduce the nonuniformity with less ghosting artifacts in moving areas and can also overcome the problem of image blurring in static areas.

A Novel Real-Time Reference Key Frame Scan Matching Method.

PubMed

Mohamed, Haytham; Moussa, Adel; Elhabiby, Mohamed; El-Sheimy, Naser; Sesay, Abu

2017-05-07

Unmanned aerial vehicles represent an effective technology for indoor search and rescue operations. Typically, most indoor missions' environments would be unknown, unstructured, and/or dynamic. Navigation of UAVs in such environments is addressed by simultaneous localization and mapping approach using either local or global approaches. Both approaches suffer from accumulated errors and high processing time due to the iterative nature of the scan matching method. Moreover, point-to-point scan matching is prone to outlier association processes. This paper proposes a low-cost novel method for 2D real-time scan matching based on a reference key frame (RKF). RKF is a hybrid scan matching technique comprised of feature-to-feature and point-to-point approaches. This algorithm aims at mitigating errors accumulation using the key frame technique, which is inspired from video streaming broadcast process. The algorithm depends on the iterative closest point algorithm during the lack of linear features which is typically exhibited in unstructured environments. The algorithm switches back to the RKF once linear features are detected. To validate and evaluate the algorithm, the mapping performance and time consumption are compared with various algorithms in static and dynamic environments. The performance of the algorithm exhibits promising navigational, mapping results and very short computational time, that indicates the potential use of the new algorithm with real-time systems.

Characteristic extraction and matching algorithms of ballistic missile in near-space by hyperspectral image analysis

NASA Astrophysics Data System (ADS)

Lu, Li; Sheng, Wen; Liu, Shihua; Zhang, Xianzhi

2014-10-01

The ballistic missile hyperspectral data of imaging spectrometer from the near-space platform are generated by numerical method. The characteristic of the ballistic missile hyperspectral data is extracted and matched based on two different kinds of algorithms, which called transverse counting and quantization coding, respectively. The simulation results show that two algorithms extract the characteristic of ballistic missile adequately and accurately. The algorithm based on the transverse counting has the low complexity and can be implemented easily compared to the algorithm based on the quantization coding does. The transverse counting algorithm also shows the good immunity to the disturbance signals and speed up the matching and recognition of subsequent targets.

Parallel algorithm for determining motion vectors in ice floe images by matching edge features

NASA Technical Reports Server (NTRS)

Manohar, M.; Ramapriyan, H. K.; Strong, J. P.

1988-01-01

A parallel algorithm is described to determine motion vectors of ice floes using time sequences of images of the Arctic ocean obtained from the Synthetic Aperture Radar (SAR) instrument flown on-board the SEASAT spacecraft. Researchers describe a parallel algorithm which is implemented on the MPP for locating corresponding objects based on their translationally and rotationally invariant features. The algorithm first approximates the edges in the images by polygons or sets of connected straight-line segments. Each such edge structure is then reduced to a seed point. Associated with each seed point are the descriptions (lengths, orientations and sequence numbers) of the lines constituting the corresponding edge structure. A parallel matching algorithm is used to match packed arrays of such descriptions to identify corresponding seed points in the two images. The matching algorithm is designed such that fragmentation and merging of ice floes are taken into account by accepting partial matches. The technique has been demonstrated to work on synthetic test patterns and real image pairs from SEASAT in times ranging from .5 to 0.7 seconds for 128 x 128 images.

A Parallel Point Matching Algorithm for Landmark Based Image Registration Using Multicore Platform

PubMed Central

Yang, Lin; Gong, Leiguang; Zhang, Hong; Nosher, John L.; Foran, David J.

2013-01-01

Point matching is crucial for many computer vision applications. Establishing the correspondence between a large number of data points is a computationally intensive process. Some point matching related applications, such as medical image registration, require real time or near real time performance if applied to critical clinical applications like image assisted surgery. In this paper, we report a new multicore platform based parallel algorithm for fast point matching in the context of landmark based medical image registration. We introduced a non-regular data partition algorithm which utilizes the K-means clustering algorithm to group the landmarks based on the number of available processing cores, which optimize the memory usage and data transfer. We have tested our method using the IBM Cell Broadband Engine (Cell/B.E.) platform. The results demonstrated a significant speed up over its sequential implementation. The proposed data partition and parallelization algorithm, though tested only on one multicore platform, is generic by its design. Therefore the parallel algorithm can be extended to other computing platforms, as well as other point matching related applications. PMID:24308014

Accuracy and robustness evaluation in stereo matching

NASA Astrophysics Data System (ADS)

Nguyen, Duc M.; Hanca, Jan; Lu, Shao-Ping; Schelkens, Peter; Munteanu, Adrian

2016-09-01

Stereo matching has received a lot of attention from the computer vision community, thanks to its wide range of applications. Despite of the large variety of algorithms that have been proposed so far, it is not trivial to select suitable algorithms for the construction of practical systems. One of the main problems is that many algorithms lack sufficient robustness when employed in various operational conditions. This problem is due to the fact that most of the proposed methods in the literature are usually tested and tuned to perform well on one specific dataset. To alleviate this problem, an extensive evaluation in terms of accuracy and robustness of state-of-the-art stereo matching algorithms is presented. Three datasets (Middlebury, KITTI, and MPEG FTV) representing different operational conditions are employed. Based on the analysis, improvements over existing algorithms have been proposed. The experimental results show that our improved versions of cross-based and cost volume filtering algorithms outperform the original versions with large margins on Middlebury and KITTI datasets. In addition, the latter of the two proposed algorithms ranks itself among the best local stereo matching approaches on the KITTI benchmark. Under evaluations using specific settings for depth-image-based-rendering applications, our improved belief propagation algorithm is less complex than MPEG's FTV depth estimation reference software (DERS), while yielding similar depth estimation performance. Finally, several conclusions on stereo matching algorithms are also presented.

Centroid stabilization in alignment of FOA corner cube: designing of a matched filter

NASA Astrophysics Data System (ADS)

Awwal, Abdul; Wilhelmsen, Karl; Roberts, Randy; Leach, Richard; Miller Kamm, Victoria; Ngo, Tony; Lowe-Webb, Roger

2015-02-01

The current automation of image-based alignment of NIF high energy laser beams is providing the capability of executing multiple target shots per day. An important aspect of performing multiple shots in a day is to reduce additional time spent aligning specific beams due to perturbations in those beam images. One such alignment is beam centration through the second and third harmonic generating crystals in the final optics assembly (FOA), which employs two retro-reflecting corner cubes to represent the beam center. The FOA houses the frequency conversion crystals for third harmonic generation as the beams enters the target chamber. Beam-to-beam variations and systematic beam changes over time in the FOA corner-cube images can lead to a reduction in accuracy as well as increased convergence durations for the template based centroid detector. This work presents a systematic approach of maintaining FOA corner cube centroid templates so that stable position estimation is applied thereby leading to fast convergence of alignment control loops. In the matched filtering approach, a template is designed based on most recent images taken in the last 60 days. The results show that new filter reduces the divergence of the position estimation of FOA images.

Whatever you do, don't look at the...: Evaluating guidance by an exclusionary attentional template.

PubMed

Beck, Valerie M; Luck, Steven J; Hollingworth, Andrew

2018-04-01

People can use a target template consisting of one or more features to guide attention and gaze to matching objects in a search array. But can we also use feature information to guide attention away from known irrelevant items? Some studies found a benefit from foreknowledge of a distractor feature, whereas others found a cost. Importantly, previous work has largely relied on end-of-trial manual responses; it is unclear how feature-guided avoidance might unfold as candidate objects are inspected. In the current experiments, participants were cued with a distractor feature to avoid, then performed a visual search task while eye movements were recorded. Participants initially fixated a to-be-avoided object more frequently than predicted by chance, but they also demonstrated avoidance of cue-matching objects later in the trial. When provided more time between cue stimulus and search array, participants continued to be initially captured by a cued-color item. Furthermore, avoidance of cue-matching objects later in the trial was not contingent on initial capture by a cue-matching object. These results suggest that the conflicting findings in previous negative-cue experiments may be explained by a mixture of two independent processes: initial attentional capture by memory-matching items and later avoidance of known irrelevant items. (PsycINFO Database Record (c) 2018 APA, all rights reserved).

Sensor-Based Vibration Signal Feature Extraction Using an Improved Composite Dictionary Matching Pursuit Algorithm

PubMed Central

Cui, Lingli; Wu, Na; Wang, Wenjing; Kang, Chenhui

2014-01-01

This paper presents a new method for a composite dictionary matching pursuit algorithm, which is applied to vibration sensor signal feature extraction and fault diagnosis of a gearbox. Three advantages are highlighted in the new method. First, the composite dictionary in the algorithm has been changed from multi-atom matching to single-atom matching. Compared to non-composite dictionary single-atom matching, the original composite dictionary multi-atom matching pursuit (CD-MaMP) algorithm can achieve noise reduction in the reconstruction stage, but it cannot dramatically reduce the computational cost and improve the efficiency in the decomposition stage. Therefore, the optimized composite dictionary single-atom matching algorithm (CD-SaMP) is proposed. Second, the termination condition of iteration based on the attenuation coefficient is put forward to improve the sparsity and efficiency of the algorithm, which adjusts the parameters of the termination condition constantly in the process of decomposition to avoid noise. Third, composite dictionaries are enriched with the modulation dictionary, which is one of the important structural characteristics of gear fault signals. Meanwhile, the termination condition of iteration settings, sub-feature dictionary selections and operation efficiency between CD-MaMP and CD-SaMP are discussed, aiming at gear simulation vibration signals with noise. The simulation sensor-based vibration signal results show that the termination condition of iteration based on the attenuation coefficient enhances decomposition sparsity greatly and achieves a good effect of noise reduction. Furthermore, the modulation dictionary achieves a better matching effect compared to the Fourier dictionary, and CD-SaMP has a great advantage of sparsity and efficiency compared with the CD-MaMP. The sensor-based vibration signals measured from practical engineering gearbox analyses have further shown that the CD-SaMP decomposition and reconstruction algorithm is feasible and effective. PMID:25207870

Sensor-based vibration signal feature extraction using an improved composite dictionary matching pursuit algorithm.

PubMed

Cui, Lingli; Wu, Na; Wang, Wenjing; Kang, Chenhui

2014-09-09

This paper presents a new method for a composite dictionary matching pursuit algorithm, which is applied to vibration sensor signal feature extraction and fault diagnosis of a gearbox. Three advantages are highlighted in the new method. First, the composite dictionary in the algorithm has been changed from multi-atom matching to single-atom matching. Compared to non-composite dictionary single-atom matching, the original composite dictionary multi-atom matching pursuit (CD-MaMP) algorithm can achieve noise reduction in the reconstruction stage, but it cannot dramatically reduce the computational cost and improve the efficiency in the decomposition stage. Therefore, the optimized composite dictionary single-atom matching algorithm (CD-SaMP) is proposed. Second, the termination condition of iteration based on the attenuation coefficient is put forward to improve the sparsity and efficiency of the algorithm, which adjusts the parameters of the termination condition constantly in the process of decomposition to avoid noise. Third, composite dictionaries are enriched with the modulation dictionary, which is one of the important structural characteristics of gear fault signals. Meanwhile, the termination condition of iteration settings, sub-feature dictionary selections and operation efficiency between CD-MaMP and CD-SaMP are discussed, aiming at gear simulation vibration signals with noise. The simulation sensor-based vibration signal results show that the termination condition of iteration based on the attenuation coefficient enhances decomposition sparsity greatly and achieves a good effect of noise reduction. Furthermore, the modulation dictionary achieves a better matching effect compared to the Fourier dictionary, and CD-SaMP has a great advantage of sparsity and efficiency compared with the CD-MaMP. The sensor-based vibration signals measured from practical engineering gearbox analyses have further shown that the CD-SaMP decomposition and reconstruction algorithm is feasible and effective.

Nonrigid synthetic aperture radar and optical image coregistration by combining local rigid transformations using a Kohonen network.

PubMed

Salehpour, Mehdi; Behrad, Alireza

2017-10-01

This study proposes a new algorithm for nonrigid coregistration of synthetic aperture radar (SAR) and optical images. The proposed algorithm employs point features extracted by the binary robust invariant scalable keypoints algorithm and a new method called weighted bidirectional matching for initial correspondence. To refine false matches, we assume that the transformation between SAR and optical images is locally rigid. This property is used to refine false matches by assigning scores to matched pairs and clustering local rigid transformations using a two-layer Kohonen network. Finally, the thin plate spline algorithm and mutual information are used for nonrigid coregistration of SAR and optical images.

The Application of Virtex-II Pro FPGA in High-Speed Image Processing Technology of Robot Vision Sensor

NASA Astrophysics Data System (ADS)

Ren, Y. J.; Zhu, J. G.; Yang, X. Y.; Ye, S. H.

2006-10-01

The Virtex-II Pro FPGA is applied to the vision sensor tracking system of IRB2400 robot. The hardware platform, which undertakes the task of improving SNR and compressing data, is constructed by using the high-speed image processing of FPGA. The lower level image-processing algorithm is realized by combining the FPGA frame and the embedded CPU. The velocity of image processing is accelerated due to the introduction of FPGA and CPU. The usage of the embedded CPU makes it easily to realize the logic design of interface. Some key techniques are presented in the text, such as read-write process, template matching, convolution, and some modules are simulated too. In the end, the compare among the modules using this design, using the PC computer and using the DSP, is carried out. Because the high-speed image processing system core is a chip of FPGA, the function of which can renew conveniently, therefore, to a degree, the measure system is intelligent.

The fidelity of replication of the three-base-pair set adenine/thymine, hypoxanthine/cytosine and 6-thiopurine/5-methyl-2-pyrimidinone with T7 DNA polymerase

PubMed Central

2004-01-01

With the goal of constructing a genetic alphabet consisting of a set of three base pairs, the fidelity of replication of the three base pairs TH (5-methyl-2-pyrimidinone)/HS (6-thiopurine; thiohypoxanthine), C/H (hypoxanthine) and T/A was evaluated using T7 DNA polymerase, a polymerase with a strong 3′→5′ exonuclease activity. An evaluation of the suitability of a new base pair for replication should include both the contribution of the fidelity of a polymerase activity and the contribution of proofreading by a 3′→5′ exonuclease activity. Using a steady-state kinetics method that included the contribution of the 3′→5′ exonuclease activity, the fidelity of replication was determined. The method determined the ratio of the apparent rate constant for the addition of a deoxynucleotide to the primer across from a template base by the polymerase activity and the rate constant for removal of the added deoxynucleotide from the primer by the 3′→5′ exonuclease activity. This ratio was designated the eni (efficiency of net incorporation). The eni of the base pair C/H was equal to or greater than the eni of T/A. The eni of the base pair TH/HS was 0.1 times that of A/T for TH in the template and 0.01 times that of A/T for HS in the template. The ratio of the eni of a mismatched deoxynucleotide to the eni of a matched deoxynucleotide was a measure of the error frequency. The error frequencies were as follows: thymine or TH opposite a template hypoxanthine, 2×10−6; HS opposite a template cytosine, <3×10−4. The remaining 24 mismatched combinations of bases gave no detectable net incorporation. Two mismatches, hypoxanthine opposite a template thymine or a template TH, showed trace incorporation in the presence of a standard dNTP complementary to the next template base. T7 DNA polymerase extended the primer beyond each of the matched base pairs of the set. The level of fidelity of replication of the three base pairs with T7 DNA polymerase suggests that they are adequate for a three-base-pair alphabet for DNA replication. PMID:15078225

The Design of SimpleITK

PubMed Central

Lowekamp, Bradley C.; Chen, David T.; Ibáñez, Luis; Blezek, Daniel

2013-01-01

SimpleITK is a new interface to the Insight Segmentation and Registration Toolkit (ITK) designed to facilitate rapid prototyping, education and scientific activities via high level programming languages. ITK is a templated C++ library of image processing algorithms and frameworks for biomedical and other applications, and it was designed to be generic, flexible and extensible. Initially, ITK provided a direct wrapping interface to languages such as Python and Tcl through the WrapITK system. Unlike WrapITK, which exposed ITK's complex templated interface, SimpleITK was designed to provide an easy to use and simplified interface to ITK's algorithms. It includes procedural methods, hides ITK's demand driven pipeline, and provides a template-less layer. Also SimpleITK provides practical conveniences such as binary distribution packages and overloaded operators. Our user-friendly design goals dictated a departure from the direct interface wrapping approach of WrapITK, toward a new facade class structure that only exposes the required functionality, hiding ITK's extensive template use. Internally SimpleITK utilizes a manual description of each filter with code-generation and advanced C++ meta-programming to provide the higher-level interface, bringing the capabilities of ITK to a wider audience. SimpleITK is licensed as open source software library under the Apache License Version 2.0 and more information about downloading it can be found at http://www.simpleitk.org. PMID:24416015

Protein structure modeling for CASP10 by multiple layers of global optimization.

PubMed

Joo, Keehyoung; Lee, Juyong; Sim, Sangjin; Lee, Sun Young; Lee, Kiho; Heo, Seungryong; Lee, In-Ho; Lee, Sung Jong; Lee, Jooyoung

2014-02-01

In the template-based modeling (TBM) category of CASP10 experiment, we introduced a new protocol called protein modeling system (PMS) to generate accurate protein structures in terms of side-chains as well as backbone trace. In the new protocol, a global optimization algorithm, called conformational space annealing (CSA), is applied to the three layers of TBM procedure: multiple sequence-structure alignment, 3D chain building, and side-chain re-modeling. For 3D chain building, we developed a new energy function which includes new distance restraint terms of Lorentzian type (derived from multiple templates), and new energy terms that combine (physical) energy terms such as dynamic fragment assembly (DFA) energy, DFIRE statistical potential energy, hydrogen bonding term, etc. These physical energy terms are expected to guide the structure modeling especially for loop regions where no template structures are available. In addition, we developed a new quality assessment method based on random forest machine learning algorithm to screen templates, multiple alignments, and final models. For TBM targets of CASP10, we find that, due to the combination of three stages of CSA global optimizations and quality assessment, the modeling accuracy of PMS improves at each additional stage of the protocol. It is especially noteworthy that the side-chains of the final PMS models are far more accurate than the models in the intermediate steps. Copyright © 2013 Wiley Periodicals, Inc.

Automated sequence-specific protein NMR assignment using the memetic algorithm MATCH.

PubMed

Volk, Jochen; Herrmann, Torsten; Wüthrich, Kurt

2008-07-01

MATCH (Memetic Algorithm and Combinatorial Optimization Heuristics) is a new memetic algorithm for automated sequence-specific polypeptide backbone NMR assignment of proteins. MATCH employs local optimization for tracing partial sequence-specific assignments within a global, population-based search environment, where the simultaneous application of local and global optimization heuristics guarantees high efficiency and robustness. MATCH thus makes combined use of the two predominant concepts in use for automated NMR assignment of proteins. Dynamic transition and inherent mutation are new techniques that enable automatic adaptation to variable quality of the experimental input data. The concept of dynamic transition is incorporated in all major building blocks of the algorithm, where it enables switching between local and global optimization heuristics at any time during the assignment process. Inherent mutation restricts the intrinsically required randomness of the evolutionary algorithm to those regions of the conformation space that are compatible with the experimental input data. Using intact and artificially deteriorated APSY-NMR input data of proteins, MATCH performed sequence-specific resonance assignment with high efficiency and robustness.

An Empirical Evaluation of Five Circular Error Probable Estimation Techniques and a Method for Improving Them

DTIC Science & Technology

1993-03-10

template which runs a Romberg algorithm in the background to numerically integrate the BVN [12:257]. Appendix A als- lists the results from two other...for computing these values: a Taylor series expansion, the Romberg algorithm , and the CBN technique. Appendix A lists CEPpop. values for eleven...determining factor in this selection process. Of the 175 populations ex- amined in the experiment, the MathCAD version of the Romberg algorithm failed

Analysis of L-band Multi-Channel Sea Clutter

DTIC Science & Technology

2010-08-01

Some researchers found that the use of a hybrid algorithm of PS and GA could accelerate the convergence for array beamforming designs (Yeo and Lu...to be shown is array failure correction using the PS algorithm . Assume element 5 of a 32 half-wavelength spacing linear array is in failure. The goal... algorithm . The blue one is the 20 dB Chebyshev pattern and the template in red is the goal pattern to achieve. Two corrected beam patterns are

Optically Transparent Wood from a Nanoporous Cellulosic Template: Combining Functional and Structural Performance.

PubMed

Li, Yuanyuan; Fu, Qiliang; Yu, Shun; Yan, Min; Berglund, Lars

2016-04-11

Optically transparent wood (TW) with transmittance as high as 85% and haze of 71% was obtained using a delignified nanoporous wood template. The template was prepared by removing the light-absorbing lignin component, creating nanoporosity in the wood cell wall. Transparent wood was prepared by successful impregnation of lumen and the nanoscale cellulose fiber network in the cell wall with refractive-index-matched prepolymerized methyl methacrylate (MMA). During the process, the hierarchical wood structure was preserved. Optical properties of TW are tunable by changing the cellulose volume fraction. The synergy between wood and PMMA was observed for mechanical properties. Lightweight and strong transparent wood is a potential candidate for lightweight low-cost, light-transmitting buildings and transparent solar cell windows.

Real Time Intelligent Target Detection and Analysis with Machine Vision

NASA Technical Reports Server (NTRS)

Howard, Ayanna; Padgett, Curtis; Brown, Kenneth

2000-01-01

We present an algorithm for detecting a specified set of targets for an Automatic Target Recognition (ATR) application. ATR involves processing images for detecting, classifying, and tracking targets embedded in a background scene. We address the problem of discriminating between targets and nontarget objects in a scene by evaluating 40x40 image blocks belonging to an image. Each image block is first projected onto a set of templates specifically designed to separate images of targets embedded in a typical background scene from those background images without targets. These filters are found using directed principal component analysis which maximally separates the two groups. The projected images are then clustered into one of n classes based on a minimum distance to a set of n cluster prototypes. These cluster prototypes have previously been identified using a modified clustering algorithm based on prior sensed data. Each projected image pattern is then fed into the associated cluster's trained neural network for classification. A detailed description of our algorithm will be given in this paper. We outline our methodology for designing the templates, describe our modified clustering algorithm, and provide details on the neural network classifiers. Evaluation of the overall algorithm demonstrates that our detection rates approach 96% with a false positive rate of less than 0.03%.

Optimized atom position and coefficient coding for matching pursuit-based image compression.

PubMed

Shoa, Alireza; Shirani, Shahram

2009-12-01

In this paper, we propose a new encoding algorithm for matching pursuit image coding. We show that coding performance is improved when correlations between atom positions and atom coefficients are both used in encoding. We find the optimum tradeoff between efficient atom position coding and efficient atom coefficient coding and optimize the encoder parameters. Our proposed algorithm outperforms the existing coding algorithms designed for matching pursuit image coding. Additionally, we show that our algorithm results in better rate distortion performance than JPEG 2000 at low bit rates.

Data-analysis driven comparison of analytic and numerical coalescing binary waveforms: Nonspinning case

DOE Office of Scientific and Technical Information (OSTI.GOV)

Pan Yi; Buonanno, Alessandra; McWilliams, Sean T.

2008-01-15

We compare waveforms obtained by numerically evolving nonspinning binary black holes to post-Newtonian (PN) template families currently used in the search for gravitational waves by ground-based detectors. We find that the time-domain 3.5PN template family, which includes the inspiral phase, has fitting factors (FFs) {>=}0.96 for binary systems with total mass M=10-20M{sub {center_dot}}. The time-domain 3.5PN effective-one-body template family, which includes the inspiral, merger, and ring-down phases, gives satisfactory signal-matching performance with FFs {>=}0.96 for binary systems with total mass M=10-120M{sub {center_dot}}. If we introduce a cutoff frequency properly adjusted to the final black-hole ring-down frequency, we find that themore » frequency-domain stationary-phase-approximated template family at 3.5PN order has FFs {>=}0.96 for binary systems with total mass M=10-20M{sub {center_dot}}. However, to obtain high matching performances for larger binary masses, we need to either extend this family to unphysical regions of the parameter space or introduce a 4PN order coefficient in the frequency-domain gravitational wave (GW) phase. Finally, we find that the phenomenological Buonanno-Chen-Vallisneri family has FFs {>=}0.97 with total mass M=10-120M{sub {center_dot}}. The main analyses use the noise-spectral density of LIGO, but several tests are extended to VIRGO and advanced LIGO noise-spectral densities.« less

Image velocimetry for clouds with relaxation labeling based on deformation consistency

NASA Astrophysics Data System (ADS)

Horinouchi, Takeshi; Murakami, Shin-ya; Kouyama, Toru; Ogohara, Kazunori; Yamazaki, Atsushi; Yamada, Manabu; Watanabe, Shigeto

2017-08-01

Correlation-based cloud tracking has been extensively used to measure atmospheric winds, but still difficulty remains. In this study, aiming at developing a cloud tracking system for Akatsuki, an artificial satellite orbiting Venus, a formulation is developed for improving the relaxation labeling technique to select appropriate peaks of cross-correlation surfaces which tend to have multiple peaks. The formulation makes an explicit use of consistency inherent in the type of cross-correlation method where template sub-images are slid without deformation; if the resultant motion vectors indicate a too-large deformation, it is contradictory to the assumption of the method. The deformation consistency is exploited further to develop two post processes; one clusters the motion vectors into groups within each of which the consistency is perfect, and the other extends the groups using the original candidate lists. These processes are useful to eliminate erroneous vectors, distinguish motion vectors at different altitudes, and detect phase velocities of waves in fluids such as atmospheric gravity waves. As a basis of the relaxation labeling and the post processes as well as uncertainty estimation, the necessity to find isolated (well-separated) peaks of cross-correlation surfaces is argued, and an algorithm to realize it is presented. All the methods are implemented, and their effectiveness is demonstrated with initial images obtained by the ultraviolet imager onboard Akatsuki. Since the deformation consistency regards the logical consistency inherent in template matching methods, it should have broad application beyond cloud tracking.

Computational design of d-peptide inhibitors of hepatitis delta antigen dimerization

NASA Astrophysics Data System (ADS)

Elkin, Carl D.; Zuccola, Harmon J.; Hogle, James M.; Joseph-McCarthy, Diane

2000-11-01

Hepatitis delta virus (HDV) encodes a single polypeptide called hepatitis delta antigen (DAg). Dimerization of DAg is required for viral replication. The structure of the dimerization region, residues 12 to 60, consists of an anti-parallel coiled coil [Zuccola et al., Structure, 6 (1998) 821]. Multiple Copy Simultaneous Searches (MCSS) of the hydrophobic core region formed by the bend in the helix of one monomer of this structure were carried out for many diverse functional groups. Six critical interaction sites were identified. The Protein Data Bank was searched for backbone templates to use in the subsequent design process by matching to these sites. A 14 residue helix expected to bind to the d-isomer of the target structure was selected as the template. Over 200 000 mutant sequences of this peptide were generated based on the MCSS results. A secondary structure prediction algorithm was used to screen all sequences, and in general only those that were predicted to be highly helical were retained. Approximately 100 of these 14-mers were model built as d-peptides and docked with the l-isomer of the target monomer. Based on calculated interaction energies, predicted helicity, and intrahelical salt bridge patterns, a small number of peptides were selected as the most promising candidates. The ligand design approach presented here is the computational analogue of mirror image phage display. The results have been used to characterize the interactions responsible for formation of this model anti-parallel coiled coil and to suggest potential ligands to disrupt it.

A template-based approach for parallel hexahedral two-refinement

DOE PAGES

Owen, Steven J.; Shih, Ryan M.; Ernst, Corey D.

2016-10-17

Here, we provide a template-based approach for generating locally refined all-hex meshes. We focus specifically on refinement of initially structured grids utilizing a 2-refinement approach where uniformly refined hexes are subdivided into eight child elements. The refinement algorithm consists of identifying marked nodes that are used as the basis for a set of four simple refinement templates. The target application for 2-refinement is a parallel grid-based all-hex meshing tool for high performance computing in a distributed environment. The result is a parallel consistent locally refined mesh requiring minimal communication and where minimum mesh quality is greater than scaled Jacobian 0.3more » prior to smoothing.« less

A template-based approach for parallel hexahedral two-refinement

DOE Office of Scientific and Technical Information (OSTI.GOV)

Owen, Steven J.; Shih, Ryan M.; Ernst, Corey D.

Here, we provide a template-based approach for generating locally refined all-hex meshes. We focus specifically on refinement of initially structured grids utilizing a 2-refinement approach where uniformly refined hexes are subdivided into eight child elements. The refinement algorithm consists of identifying marked nodes that are used as the basis for a set of four simple refinement templates. The target application for 2-refinement is a parallel grid-based all-hex meshing tool for high performance computing in a distributed environment. The result is a parallel consistent locally refined mesh requiring minimal communication and where minimum mesh quality is greater than scaled Jacobian 0.3more » prior to smoothing.« less

Automatic identification of resting state networks: an extended version of multiple template-matching

NASA Astrophysics Data System (ADS)

Guaje, Javier; Molina, Juan; Rudas, Jorge; Demertzi, Athena; Heine, Lizette; Tshibanda, Luaba; Soddu, Andrea; Laureys, Steven; Gómez, Francisco

2015-12-01

Functional magnetic resonance imaging in resting state (fMRI-RS) constitutes an informative protocol to investigate several pathological and pharmacological conditions. A common approach to study this data source is through the analysis of changes in the so called resting state networks (RSNs). These networks correspond to well-defined functional entities that have been associated to different low and high brain order functions. RSNs may be characterized by using Independent Component Analysis (ICA). ICA provides a decomposition of the fMRI-RS signal into sources of brain activity, but it lacks of information about the nature of the signal, i.e., if the source is artifactual or not. Recently, a multiple template-matching (MTM) approach was proposed to automatically recognize RSNs in a set of Independent Components (ICs). This method provides valuable information to assess subjects at individual level. Nevertheless, it lacks of a mechanism to quantify how much certainty there is about the existence/absence of each network. This information may be important for the assessment of patients with severely damaged brains, in which RSNs may be greatly affected as a result of the pathological condition. In this work we propose a set of changes to the original MTM that improves the RSNs recognition task and also extends the functionality of the method. The key points of this improvement is a standardization strategy and a modification of method's constraints that adds flexibility to the approach. Additionally, we also introduce an analysis to the trustworthiness measurement of each RSN obtained by using template-matching approach. This analysis consists of a thresholding strategy applied over the computed Goodness-of-Fit (GOF) between the set of templates and the ICs. The proposed method was validated on 2 two independent studies (Baltimore, 23 healthy subjects and Liege, 27 healthy subjects) with different configurations of MTM. Results suggest that the method will provide complementary information for characterization of RSNs at individual level.

75 FR 66404 - Self-Regulatory Organizations; C2 Options Exchange, Incorporated; Notice of Filing and Immediate...

Federal Register 2010, 2011, 2012, 2013, 2014

2010-10-28

... Change The Exchange proposes to modify the wording of Rule 6.12 relating to the C2 matching algorithm... matching algorithm and subsequently overlay certain priorities over the selected base algorithm. There are currently two base algorithms: price-time (often referred to as first in, first out or FIFO) in which...

Evaluation of Existing Image Matching Methods for Deriving Glacier Surface Displacements Globally from Optical Satellite Imagery

NASA Astrophysics Data System (ADS)

Heid, T.; Kääb, A.

2011-12-01

Automatic matching of images from two different times is a method that is often used to derive glacier surface velocity. Nearly global repeat coverage of the Earth's surface by optical satellite sensors now opens the possibility for global-scale mapping and monitoring of glacier flow with a number of applications in, for example, glacier physics, glacier-related climate change and impact assessment, and glacier hazard management. The purpose of this study is to compare and evaluate different existing image matching methods for glacier flow determination over large scales. The study compares six different matching methods: normalized cross-correlation (NCC), the phase correlation algorithm used in the COSI-Corr software, and four other Fourier methods with different normalizations. We compare the methods over five regions of the world with different representative glacier characteristics: Karakoram, the European Alps, Alaska, Pine Island (Antarctica) and southwest Greenland. Landsat images are chosen for matching because they expand back to 1972, they cover large areas, and at the same time their spatial resolution is as good as 15 m for images after 1999 (ETM+ pan). Cross-correlation on orientation images (CCF-O) outperforms the three similar Fourier methods, both in areas with high and low visual contrast. NCC experiences problems in areas with low visual contrast, areas with thin clouds or changing snow conditions between the images. CCF-O has problems on narrow outlet glaciers where small window sizes (about 16 pixels by 16 pixels or smaller) are needed, and it also obtains fewer correct matches than COSI-Corr in areas with low visual contrast. COSI-Corr has problems on narrow outlet glaciers and it obtains fewer correct matches compared to CCF-O when thin clouds cover the surface, or if one of the images contains snow dunes. In total, we consider CCF-O and COSI-Corr to be the two most robust matching methods for global-scale mapping and monitoring of glacier velocities. If combining CCF-O with locally adaptive template sizes and by filtering the matching results automatically by comparing the displacement matrix to its low pass filtered version, the matching process can be automated to a large degree. This allows the derivation of glacier velocities with minimal (but not without!) user interaction and hence also opens up the possibility of global-scale mapping and monitoring of glacier flow.

AN FDTD ALGORITHM WITH PERFECTLY MATCHED LAYERS FOR CONDUCTIVE MEDIA. (R825225)

EPA Science Inventory

We extend Berenger's perfectly matched layers (PML) to conductive media. A finite-difference-time-domain (FDTD) algorithm with PML as an absorbing boundary condition is developed for solutions of Maxwell's equations in inhomogeneous, conductive media. For a perfectly matched laye...

A comparison of semiglobal and local dense matching algorithms for surface reconstruction

NASA Astrophysics Data System (ADS)

Dall'Asta, E.; Roncella, R.

2014-06-01

Encouraged by the growing interest in automatic 3D image-based reconstruction, the development and improvement of robust stereo matching techniques is one of the most investigated research topic of the last years in photogrammetry and computer vision. The paper is focused on the comparison of some stereo matching algorithms (local and global) which are very popular both in photogrammetry and computer vision. In particular, the Semi-Global Matching (SGM), which realizes a pixel-wise matching and relies on the application of consistency constraints during the matching cost aggregation, will be discussed. The results of some tests performed on real and simulated stereo image datasets, evaluating in particular the accuracy of the obtained digital surface models, will be presented. Several algorithms and different implementation are considered in the comparison, using freeware software codes like MICMAC and OpenCV, commercial software (e.g. Agisoft PhotoScan) and proprietary codes implementing Least Square e Semi-Global Matching algorithms. The comparisons will also consider the completeness and the level of detail within fine structures, and the reliability and repeatability of the obtainable data.

An enhanced multi-view vertical line locus matching algorithm of object space ground primitives based on positioning consistency for aerial and space images

NASA Astrophysics Data System (ADS)

Zhang, Ka; Sheng, Yehua; Wang, Meizhen; Fu, Suxia

2018-05-01

The traditional multi-view vertical line locus (TMVLL) matching method is an object-space-based method that is commonly used to directly acquire spatial 3D coordinates of ground objects in photogrammetry. However, the TMVLL method can only obtain one elevation and lacks an accurate means of validating the matching results. In this paper, we propose an enhanced multi-view vertical line locus (EMVLL) matching algorithm based on positioning consistency for aerial or space images. The algorithm involves three components: confirming candidate pixels of the ground primitive in the base image, multi-view image matching based on the object space constraints for all candidate pixels, and validating the consistency of the object space coordinates with the multi-view matching result. The proposed algorithm was tested using actual aerial images and space images. Experimental results show that the EMVLL method successfully solves the problems associated with the TMVLL method, and has greater reliability, accuracy and computing efficiency.

A Novel Real-Time Reference Key Frame Scan Matching Method

PubMed Central

Mohamed, Haytham; Moussa, Adel; Elhabiby, Mohamed; El-Sheimy, Naser; Sesay, Abu

2017-01-01

Unmanned aerial vehicles represent an effective technology for indoor search and rescue operations. Typically, most indoor missions’ environments would be unknown, unstructured, and/or dynamic. Navigation of UAVs in such environments is addressed by simultaneous localization and mapping approach using either local or global approaches. Both approaches suffer from accumulated errors and high processing time due to the iterative nature of the scan matching method. Moreover, point-to-point scan matching is prone to outlier association processes. This paper proposes a low-cost novel method for 2D real-time scan matching based on a reference key frame (RKF). RKF is a hybrid scan matching technique comprised of feature-to-feature and point-to-point approaches. This algorithm aims at mitigating errors accumulation using the key frame technique, which is inspired from video streaming broadcast process. The algorithm depends on the iterative closest point algorithm during the lack of linear features which is typically exhibited in unstructured environments. The algorithm switches back to the RKF once linear features are detected. To validate and evaluate the algorithm, the mapping performance and time consumption are compared with various algorithms in static and dynamic environments. The performance of the algorithm exhibits promising navigational, mapping results and very short computational time, that indicates the potential use of the new algorithm with real-time systems. PMID:28481285

A human auditory tuning curves matched wavelet function.

PubMed

Abolhassani, Mohammad D; Salimpour, Yousef

2008-01-01

This paper proposes a new quantitative approach to the problem of matching a wavelet function to a human auditory tuning curves. The auditory filter shapes were derived from the psychophysical measurements in normal-hearing listeners using the variant of the notched-noise method for brief signals in forward and simultaneous masking. These filters were used as templates for the designing a wavelet function that has the maximum matching to a tuning curve. The scaling function was calculated from the matched wavelet function and by using these functions, low pass and high pass filters were derived for the implementation of a filter bank. Therefore, new wavelet families were derived.

An improved feature extraction algorithm based on KAZE for multi-spectral image

NASA Astrophysics Data System (ADS)

Yang, Jianping; Li, Jun

2018-02-01

Multi-spectral image contains abundant spectral information, which is widely used in all fields like resource exploration, meteorological observation and modern military. Image preprocessing, such as image feature extraction and matching, is indispensable while dealing with multi-spectral remote sensing image. Although the feature matching algorithm based on linear scale such as SIFT and SURF performs strong on robustness, the local accuracy cannot be guaranteed. Therefore, this paper proposes an improved KAZE algorithm, which is based on nonlinear scale, to raise the number of feature and to enhance the matching rate by using the adjusted-cosine vector. The experiment result shows that the number of feature and the matching rate of the improved KAZE are remarkably than the original KAZE algorithm.

Understanding the General Packing Rearrangements Required for Successful Template Based Modeling of Protein Structure from a CASP Experiment

PubMed Central

Day, Ryan; Joo, Hyun; Chavan, Archana; Lennox, Kristin P.; Chen, Ann; Dahl, David B.; Vannucci, Marina; Tsai, Jerry W.

2012-01-01

As an alternative to the common template based protein structure prediction methods based on main-chain position, a novel side-chain centric approach has been developed. Together with a Bayesian loop modeling procedure and a combination scoring function, the Stone Soup algorithm was applied to the CASP9 set of template based modeling targets. Although the method did not generate as large of perturbations to the template structures as necessary, the analysis of the results gives unique insights into the differences in packing between the target structures and their templates. Considerable variation in packing is found between target and template structures even when the structures are close, and this variation is found due to 2 and 3 body packing interactions. Outside the inherent restrictions in packing representation of the PDB, the first steps in correctly defining those regions of variable packing have been mapped primarily to local interactions, as the packing at the secondary and tertiary structure are largely conserved. Of the scoring functions used, a loop scoring function based on water structure exhibited some promise for discrimination. These results present a clear structural path for further development of a side-chain centered approach to template based modeling. PMID:23266765

Understanding the general packing rearrangements required for successful template based modeling of protein structure from a CASP experiment.

PubMed

Day, Ryan; Joo, Hyun; Chavan, Archana C; Lennox, Kristin P; Chen, Y Ann; Dahl, David B; Vannucci, Marina; Tsai, Jerry W

2013-02-01

As an alternative to the common template based protein structure prediction methods based on main-chain position, a novel side-chain centric approach has been developed. Together with a Bayesian loop modeling procedure and a combination scoring function, the Stone Soup algorithm was applied to the CASP9 set of template based modeling targets. Although the method did not generate as large of perturbations to the template structures as necessary, the analysis of the results gives unique insights into the differences in packing between the target structures and their templates. Considerable variation in packing is found between target and template structures even when the structures are close, and this variation is found due to 2 and 3 body packing interactions. Outside the inherent restrictions in packing representation of the PDB, the first steps in correctly defining those regions of variable packing have been mapped primarily to local interactions, as the packing at the secondary and tertiary structure are largely conserved. Of the scoring functions used, a loop scoring function based on water structure exhibited some promise for discrimination. These results present a clear structural path for further development of a side-chain centered approach to template based modeling. Copyright © 2012 Elsevier Ltd. All rights reserved.

Knowledge-based image processing for on-off type DNA microarray

NASA Astrophysics Data System (ADS)

Kim, Jong D.; Kim, Seo K.; Cho, Jeong S.; Kim, Jongwon

2002-06-01

This paper addresses the image processing technique for discriminating whether the probes are hybrized with target DNA in the Human Papilloma Virus (HPV) DNA Chip designed for genotyping HPV. In addition to the probes, the HPV DNA chip has markers that always react with the sample DNA. The positions of probe-dots in the final scanned image are fixed relative to the marker-dot locations with a small variation according to the accuracy of the dotter and the scanner. The probes are duplicated 4 times for the diagnostic stability. The prior knowledges such as the maker relative distance and the duplication information of probes is integrated into the template matching technique with the normalized correlation measure. Results show that the employment of both of the prior knowledges is to simply average the template matching measures over the positions of the markers and probes. The eventual proposed scheme yields stable marker locating and probe classification.

Breast MR segmentation and lesion detection with cellular neural networks and 3D template matching.

PubMed

Ertaş, Gökhan; Gülçür, H Ozcan; Osman, Onur; Uçan, Osman N; Tunaci, Mehtap; Dursun, Memduh

2008-01-01

A novel fully automated system is introduced to facilitate lesion detection in dynamic contrast-enhanced, magnetic resonance mammography (DCE-MRM). The system extracts breast regions from pre-contrast images using a cellular neural network, generates normalized maximum intensity-time ratio (nMITR) maps and performs 3D template matching with three layers of 12x12 cells to detect lesions. A breast is considered to be properly segmented when relative overlap >0.85 and misclassification rate <0.10. Sensitivity, false-positive rate per slice and per lesion are used to assess detection performance. The system was tested with a dataset of 2064 breast MR images (344slicesx6 acquisitions over time) from 19 women containing 39 marked lesions. Ninety-seven percent of the breasts were segmented properly and all the lesions were detected correctly (detection sensitivity=100%), however, there were some false-positive detections (31%/lesion, 10%/slice).

Database extraction strategies for low-template evidence.

PubMed

Bleka, Øyvind; Dørum, Guro; Haned, Hinda; Gill, Peter

2014-03-01

Often in forensic cases, the profile of at least one of the contributors to a DNA evidence sample is unknown and a database search is needed to discover possible perpetrators. In this article we consider two types of search strategies to extract suspects from a database using methods based on probability arguments. The performance of the proposed match scores is demonstrated by carrying out a study of each match score relative to the level of allele drop-out in the crime sample, simulating low-template DNA. The efficiency was measured by random man simulation and we compared the performance using the SGM Plus kit and the ESX 17 kit for the Norwegian population, demonstrating that the latter has greatly enhanced power to discover perpetrators of crime in large national DNA databases. The code for the database extraction strategies will be prepared for release in the R-package forensim. Copyright © 2013 Elsevier Ireland Ltd. All rights reserved.

Fingerprint separation: an application of ICA

NASA Astrophysics Data System (ADS)

Singh, Meenakshi; Singh, Deepak Kumar; Kalra, Prem Kumar

2008-04-01

Among all existing biometric techniques, fingerprint-based identification is the oldest method, which has been successfully used in numerous applications. Fingerprint-based identification is the most recognized tool in biometrics because of its reliability and accuracy. Fingerprint identification is done by matching questioned and known friction skin ridge impressions from fingers, palms, and toes to determine if the impressions are from the same finger (or palm, toe, etc.). There are many fingerprint matching algorithms which automate and facilitate the job of fingerprint matching, but for any of these algorithms matching can be difficult if the fingerprints are overlapped or mixed. In this paper, we have proposed a new algorithm for separating overlapped or mixed fingerprints so that the performance of the matching algorithms will improve when they are fed with these inputs. Independent Component Analysis (ICA) has been used as a tool to separate the overlapped or mixed fingerprints.

Acoustic transient classification with a template correlation processor.

PubMed

Edwards, R T

1999-10-01

I present an architecture for acoustic pattern classification using trinary-trinary template correlation. In spite of its computational simplicity, the algorithm and architecture represent a method which greatly reduces bandwidth of the input, storage requirements of the classifier memory, and power consumption of the system without compromising classification accuracy. The linear system should be amenable to training using recently-developed methods such as Independent Component Analysis (ICA), and we predict that behavior will be qualitatively similar to that of structures in the auditory cortex.

Quasi-Epipolar Resampling of High Resolution Satellite Stereo Imagery for Semi Global Matching

NASA Astrophysics Data System (ADS)

Tatar, N.; Saadatseresht, M.; Arefi, H.; Hadavand, A.

2015-12-01

Semi-global matching is a well-known stereo matching algorithm in photogrammetric and computer vision society. Epipolar images are supposed as input of this algorithm. Epipolar geometry of linear array scanners is not a straight line as in case of frame camera. Traditional epipolar resampling algorithms demands for rational polynomial coefficients (RPCs), physical sensor model or ground control points. In this paper we propose a new solution for epipolar resampling method which works without the need for these information. In proposed method, automatic feature extraction algorithms are employed to generate corresponding features for registering stereo pairs. Also original images are divided into small tiles. In this way by omitting the need for extra information, the speed of matching algorithm increased and the need for high temporal memory decreased. Our experiments on GeoEye-1 stereo pair captured over Qom city in Iran demonstrates that the epipolar images are generated with sub-pixel accuracy.

Foot-mounted inertial measurement unit for activity classification.

PubMed

Ghobadi, Mostafa; Esfahani, Ehsan T

2014-01-01

This paper proposes a classification technique for daily base activity recognition for human monitoring during physical therapy in home. The proposed method estimates the foot motion using single inertial measurement unit, then segments the motion into steps classify them by template-matching as walking, stairs up or stairs down steps. The results show a high accuracy of activity recognition. Unlike previous works which are limited to activity recognition, the proposed approach is more qualitative by providing similarity index of any activity to its desired template which can be used to assess subjects improvement.

iTemplate: A template-based eye movement data analysis approach.

PubMed

Xiao, Naiqi G; Lee, Kang

2018-02-08

Current eye movement data analysis methods rely on defining areas of interest (AOIs). Due to the fact that AOIs are created and modified manually, variances in their size, shape, and location are unavoidable. These variances affect not only the consistency of the AOI definitions, but also the validity of the eye movement analyses based on the AOIs. To reduce the variances in AOI creation and modification and achieve a procedure to process eye movement data with high precision and efficiency, we propose a template-based eye movement data analysis method. Using a linear transformation algorithm, this method registers the eye movement data from each individual stimulus to a template. Thus, users only need to create one set of AOIs for the template in order to analyze eye movement data, rather than creating a unique set of AOIs for all individual stimuli. This change greatly reduces the error caused by the variance from manually created AOIs and boosts the efficiency of the data analysis. Furthermore, this method can help researchers prepare eye movement data for some advanced analysis approaches, such as iMap. We have developed software (iTemplate) with a graphic user interface to make this analysis method available to researchers.

A Rotor Tip Vortex Tracing Algorithm for Image Post-Processing

NASA Technical Reports Server (NTRS)

Overmeyer, Austin D.

2015-01-01

A neurite tracing algorithm, originally developed for medical image processing, was used to trace the location of the rotor tip vortex in density gradient flow visualization images. The tracing algorithm was applied to several representative test images to form case studies. The accuracy of the tracing algorithm was compared to two current methods including a manual point and click method and a cross-correlation template method. It is shown that the neurite tracing algorithm can reduce the post-processing time to trace the vortex by a factor of 10 to 15 without compromising the accuracy of the tip vortex location compared to other methods presented in literature.

A scale-invariant keypoint detector in log-polar space

NASA Astrophysics Data System (ADS)

Tao, Tao; Zhang, Yun

2017-02-01

The scale-invariant feature transform (SIFT) algorithm is devised to detect keypoints via the difference of Gaussian (DoG) images. However, the DoG data lacks the high-frequency information, which can lead to a performance drop of the algorithm. To address this issue, this paper proposes a novel log-polar feature detector (LPFD) to detect scale-invariant blubs (keypoints) in log-polar space, which, in contrast, can retain all the image information. The algorithm consists of three components, viz. keypoint detection, descriptor extraction and descriptor matching. Besides, the algorithm is evaluated in detecting keypoints from the INRIA dataset by comparing with the SIFT algorithm and one of its fast versions, the speed up robust features (SURF) algorithm in terms of three performance measures, viz. correspondences, repeatability, correct matches and matching score.

Visual working memory simultaneously guides facilitation and inhibition during visual search.

PubMed

Dube, Blaire; Basciano, April; Emrich, Stephen M; Al-Aidroos, Naseem

2016-07-01

During visual search, visual working memory (VWM) supports the guidance of attention in two ways: It stores the identity of the search target, facilitating the selection of matching stimuli in the search array, and it maintains a record of the distractors processed during search so that they can be inhibited. In two experiments, we investigated whether the full contents of VWM can be used to support both of these abilities simultaneously. In Experiment 1, participants completed a preview search task in which (a) a subset of search distractors appeared before the remainder of the search items, affording participants the opportunity to inhibit them, and (b) the search target varied from trial to trial, requiring the search target template to be maintained in VWM. We observed the established signature of VWM-based inhibition-reduced ability to ignore previewed distractors when the number of distractors exceeds VWM's capacity-suggesting that VWM can serve this role while also representing the target template. In Experiment 2, we replicated Experiment 1, but added to the search displays a singleton distractor that sometimes matched the color (a task-irrelevant feature) of the search target, to evaluate capture. We again observed the signature of VWM-based preview inhibition along with attentional capture by (and, thus, facilitation of) singletons matching the target template. These findings indicate that more than one VWM representation can bias attention at a time, and that these representations can separately affect selection through either facilitation or inhibition, placing constraints on existing models of the VWM-based guidance of attention.

A 3D terrain reconstruction method of stereo vision based quadruped robot navigation system

NASA Astrophysics Data System (ADS)

Ge, Zhuo; Zhu, Ying; Liang, Guanhao

2017-01-01

To provide 3D environment information for the quadruped robot autonomous navigation system during walking through rough terrain, based on the stereo vision, a novel 3D terrain reconstruction method is presented. In order to solve the problem that images collected by stereo sensors have large regions with similar grayscale and the problem that image matching is poor at real-time performance, watershed algorithm and fuzzy c-means clustering algorithm are combined for contour extraction. Aiming at the problem of error matching, duel constraint with region matching and pixel matching is established for matching optimization. Using the stereo matching edge pixel pairs, the 3D coordinate algorithm is estimated according to the binocular stereo vision imaging model. Experimental results show that the proposed method can yield high stereo matching ratio and reconstruct 3D scene quickly and efficiently.

Application of Approximate Pattern Matching in Two Dimensional Spaces to Grid Layout for Biochemical Network Maps

PubMed Central

Inoue, Kentaro; Shimozono, Shinichi; Yoshida, Hideaki; Kurata, Hiroyuki

2012-01-01

Background For visualizing large-scale biochemical network maps, it is important to calculate the coordinates of molecular nodes quickly and to enhance the understanding or traceability of them. The grid layout is effective in drawing compact, orderly, balanced network maps with node label spaces, but existing grid layout algorithms often require a high computational cost because they have to consider complicated positional constraints through the entire optimization process. Results We propose a hybrid grid layout algorithm that consists of a non-grid, fast layout (preprocessor) algorithm and an approximate pattern matching algorithm that distributes the resultant preprocessed nodes on square grid points. To demonstrate the feasibility of the hybrid layout algorithm, it is characterized in terms of the calculation time, numbers of edge-edge and node-edge crossings, relative edge lengths, and F-measures. The proposed algorithm achieves outstanding performances compared with other existing grid layouts. Conclusions Use of an approximate pattern matching algorithm quickly redistributes the laid-out nodes by fast, non-grid algorithms on the square grid points, while preserving the topological relationships among the nodes. The proposed algorithm is a novel use of the pattern matching, thereby providing a breakthrough for grid layout. This application program can be freely downloaded from http://www.cadlive.jp/hybridlayout/hybridlayout.html. PMID:22679486

Application of approximate pattern matching in two dimensional spaces to grid layout for biochemical network maps.

PubMed

Inoue, Kentaro; Shimozono, Shinichi; Yoshida, Hideaki; Kurata, Hiroyuki

2012-01-01

For visualizing large-scale biochemical network maps, it is important to calculate the coordinates of molecular nodes quickly and to enhance the understanding or traceability of them. The grid layout is effective in drawing compact, orderly, balanced network maps with node label spaces, but existing grid layout algorithms often require a high computational cost because they have to consider complicated positional constraints through the entire optimization process. We propose a hybrid grid layout algorithm that consists of a non-grid, fast layout (preprocessor) algorithm and an approximate pattern matching algorithm that distributes the resultant preprocessed nodes on square grid points. To demonstrate the feasibility of the hybrid layout algorithm, it is characterized in terms of the calculation time, numbers of edge-edge and node-edge crossings, relative edge lengths, and F-measures. The proposed algorithm achieves outstanding performances compared with other existing grid layouts. Use of an approximate pattern matching algorithm quickly redistributes the laid-out nodes by fast, non-grid algorithms on the square grid points, while preserving the topological relationships among the nodes. The proposed algorithm is a novel use of the pattern matching, thereby providing a breakthrough for grid layout. This application program can be freely downloaded from http://www.cadlive.jp/hybridlayout/hybridlayout.html.

A Software Architecture for Adaptive Modular Sensing Systems

PubMed Central

Lyle, Andrew C.; Naish, Michael D.

2010-01-01

By combining a number of simple transducer modules, an arbitrarily complex sensing system may be produced to accommodate a wide range of applications. This work outlines a novel software architecture and knowledge representation scheme that has been developed to support this type of flexible and reconfigurable modular sensing system. Template algorithms are used to embed intelligence within each module. As modules are added or removed, the composite sensor is able to automatically determine its overall geometry and assume an appropriate collective identity. A virtual machine-based middleware layer runs on top of a real-time operating system with a pre-emptive kernel, enabling platform-independent template algorithms to be written once and run on any module, irrespective of its underlying hardware architecture. Applications that may benefit from easily reconfigurable modular sensing systems include flexible inspection, mobile robotics, surveillance, and space exploration. PMID:22163614

A software architecture for adaptive modular sensing systems.

PubMed

Lyle, Andrew C; Naish, Michael D

2010-01-01

By combining a number of simple transducer modules, an arbitrarily complex sensing system may be produced to accommodate a wide range of applications. This work outlines a novel software architecture and knowledge representation scheme that has been developed to support this type of flexible and reconfigurable modular sensing system. Template algorithms are used to embed intelligence within each module. As modules are added or removed, the composite sensor is able to automatically determine its overall geometry and assume an appropriate collective identity. A virtual machine-based middleware layer runs on top of a real-time operating system with a pre-emptive kernel, enabling platform-independent template algorithms to be written once and run on any module, irrespective of its underlying hardware architecture. Applications that may benefit from easily reconfigurable modular sensing systems include flexible inspection, mobile robotics, surveillance, and space exploration.

Robust spike sorting of retinal ganglion cells tuned to spot stimuli.

PubMed

Ghahari, Alireza; Badea, Tudor C

2016-08-01

We propose an automatic spike sorting approach for the data recorded from a microelectrode array during visual stimulation of wild type retinas with tiled spot stimuli. The approach first detects individual spikes per electrode by their signature local minima. With the mixture probability distribution of the local minima estimated afterwards, it applies a minimum-squared-error clustering algorithm to sort the spikes into different clusters. A template waveform for each cluster per electrode is defined, and a number of reliability tests are performed on it and its corresponding spikes. Finally, a divisive hierarchical clustering algorithm is used to deal with the correlated templates per cluster type across all the electrodes. According to the measures of performance of the spike sorting approach, it is robust even in the cases of recordings with low signal-to-noise ratio.

75 FR 36147 - Self-Regulatory Organizations; Chicago Board Options Exchange, Incorporated; Order Approving...

Federal Register 2010, 2011, 2012, 2013, 2014

2010-06-24

..., as Modified by Amendment No. 1 Thereto, Related to the Hybrid Matching Algorithms June 17, 2010. On... Hybrid System. Each rule currently provides allocation algorithms the Exchange can utilize when executing incoming electronic orders, including the Ultimate Matching Algorithm (``UMA''), and price-time and pro...

Unconstrained and contactless hand geometry biometrics.

PubMed

de-Santos-Sierra, Alberto; Sánchez-Ávila, Carmen; Del Pozo, Gonzalo Bailador; Guerra-Casanova, Javier

2011-01-01

This paper presents a hand biometric system for contact-less, platform-free scenarios, proposing innovative methods in feature extraction, template creation and template matching. The evaluation of the proposed method considers both the use of three contact-less publicly available hand databases, and the comparison of the performance to two competitive pattern recognition techniques existing in literature: namely support vector machines (SVM) and k-nearest neighbour (k-NN). Results highlight the fact that the proposed method outcomes existing approaches in literature in terms of computational cost, accuracy in human identification, number of extracted features and number of samples for template creation. The proposed method is a suitable solution for human identification in contact-less scenarios based on hand biometrics, providing a feasible solution to devices with limited hardware requirements like mobile devices.

Unconstrained and Contactless Hand Geometry Biometrics

PubMed Central

de-Santos-Sierra, Alberto; Sánchez-Ávila, Carmen; del Pozo, Gonzalo Bailador; Guerra-Casanova, Javier

2011-01-01

This paper presents a hand biometric system for contact-less, platform-free scenarios, proposing innovative methods in feature extraction, template creation and template matching. The evaluation of the proposed method considers both the use of three contact-less publicly available hand databases, and the comparison of the performance to two competitive pattern recognition techniques existing in literature: namely Support Vector Machines (SVM) and k-Nearest Neighbour (k-NN). Results highlight the fact that the proposed method outcomes existing approaches in literature in terms of computational cost, accuracy in human identification, number of extracted features and number of samples for template creation. The proposed method is a suitable solution for human identification in contact-less scenarios based on hand biometrics, providing a feasible solution to devices with limited hardware requirements like mobile devices. PMID:22346634

De novo design of molecular architectures by evolutionary assembly of drug-derived building blocks.

PubMed

Schneider, G; Lee, M L; Stahl, M; Schneider, P

2000-07-01

An evolutionary algorithm was developed for fragment-based de novo design of molecules (TOPAS, TOPology-Assigning System). This stochastic method aims at generating a novel molecular structure mimicking a template structure. A set of approximately 25,000 fragment structures serves as the building block supply, which were obtained by a straightforward fragmentation procedure applied to 36,000 known drugs. Eleven reaction schemes were implemented for both fragmentation and building block assembly. This combination of drug-derived building blocks and a restricted set of reaction schemes proved to be a key for the automatic development of novel, synthetically tractable structures. In a cyclic optimization process, molecular architectures were generated from a parent structure by virtual synthesis, and the best structure of a generation was selected as the parent for the subsequent TOPAS cycle. Similarity measures were used to define 'fitness', based on 2D-structural similarity or topological pharmacophore distance between the template molecule and the variants. The concept of varying library 'diversity' during a design process was consequently implemented by using adaptive variant distributions. The efficiency of the design algorithm was demonstrated for the de novo construction of potential thrombin inhibitors mimicking peptide and non-peptide template structures.

Integrity Determination for Image Rendering Vision Navigation

DTIC Science & Technology

2016-03-01

identifying an object within a scene, tracking a SIFT feature between frames or matching images and/or features for stereo vision applications. This... object level, either in 2-D or 3-D, versus individual features. There is a breadth of information, largely from the machine vision community...matching or image rendering image correspondence approach is based upon using either 2-D or 3-D object models or templates to perform object detection or

An Improved Image Matching Method Based on Surf Algorithm

NASA Astrophysics Data System (ADS)

Chen, S. J.; Zheng, S. Z.; Xu, Z. G.; Guo, C. C.; Ma, X. L.

2018-04-01

Many state-of-the-art image matching methods, based on the feature matching, have been widely studied in the remote sensing field. These methods of feature matching which get highly operating efficiency, have a disadvantage of low accuracy and robustness. This paper proposes an improved image matching method which based on the SURF algorithm. The proposed method introduces color invariant transformation, information entropy theory and a series of constraint conditions to increase feature points detection and matching accuracy. First, the model of color invariant transformation is introduced for two matching images aiming at obtaining more color information during the matching process and information entropy theory is used to obtain the most information of two matching images. Then SURF algorithm is applied to detect and describe points from the images. Finally, constraint conditions which including Delaunay triangulation construction, similarity function and projective invariant are employed to eliminate the mismatches so as to improve matching precision. The proposed method has been validated on the remote sensing images and the result benefits from its high precision and robustness.

An Integrated Ransac and Graph Based Mismatch Elimination Approach for Wide-Baseline Image Matching

NASA Astrophysics Data System (ADS)

Hasheminasab, M.; Ebadi, H.; Sedaghat, A.

2015-12-01

In this paper we propose an integrated approach in order to increase the precision of feature point matching. Many different algorithms have been developed as to optimizing the short-baseline image matching while because of illumination differences and viewpoints changes, wide-baseline image matching is so difficult to handle. Fortunately, the recent developments in the automatic extraction of local invariant features make wide-baseline image matching possible. The matching algorithms which are based on local feature similarity principle, using feature descriptor as to establish correspondence between feature point sets. To date, the most remarkable descriptor is the scale-invariant feature transform (SIFT) descriptor , which is invariant to image rotation and scale, and it remains robust across a substantial range of affine distortion, presence of noise, and changes in illumination. The epipolar constraint based on RANSAC (random sample consensus) method is a conventional model for mismatch elimination, particularly in computer vision. Because only the distance from the epipolar line is considered, there are a few false matches in the selected matching results based on epipolar geometry and RANSAC. Aguilariu et al. proposed Graph Transformation Matching (GTM) algorithm to remove outliers which has some difficulties when the mismatched points surrounded by the same local neighbor structure. In this study to overcome these limitations, which mentioned above, a new three step matching scheme is presented where the SIFT algorithm is used to obtain initial corresponding point sets. In the second step, in order to reduce the outliers, RANSAC algorithm is applied. Finally, to remove the remained mismatches, based on the adjacent K-NN graph, the GTM is implemented. Four different close range image datasets with changes in viewpoint are utilized to evaluate the performance of the proposed method and the experimental results indicate its robustness and capability.

Automatic script identification from images using cluster-based templates

DOE Office of Scientific and Technical Information (OSTI.GOV)

Hochberg, J.; Kerns, L.; Kelly, P.

We have developed a technique for automatically identifying the script used to generate a document that is stored electronically in bit image form. Our approach differs from previous work in that the distinctions among scripts are discovered by an automatic learning procedure, without any handson analysis. We first develop a set of representative symbols (templates) for each script in our database (Cyrillic, Roman, etc.). We do this by identifying all textual symbols in a set of training documents, scaling each symbol to a fixed size, clustering similar symbols, pruning minor clusters, and finding each cluster`s centroid. To identify a newmore » document`s script, we identify and scale a subset of symbols from the document and compare them to the templates for each script. We choose the script whose templates provide the best match. Our current system distinguishes among the Armenian, Burmese, Chinese, Cyrillic, Ethiopic, Greek, Hebrew, Japanese, Korean, Roman, and Thai scripts with over 90% accuracy.« less

SU-F-T-20: Novel Catheter Lumen Recognition Algorithm for Rapid Digitization

DOE Office of Scientific and Technical Information (OSTI.GOV)

Dise, J; McDonald, D; Ashenafi, M

Purpose: Manual catheter recognition remains a time-consuming aspect of high-dose-rate brachytherapy (HDR) treatment planning. In this work, a novel catheter lumen recognition algorithm was created for accurate and rapid digitization. Methods: MatLab v8.5 was used to create the catheter recognition algorithm. Initially, the algorithm searches the patient CT dataset using an intensity based k-means filter designed to locate catheters. Once the catheters have been located, seed points are manually selected to initialize digitization of each catheter. From each seed point, the algorithm searches locally in order to automatically digitize the remaining catheter. This digitization is accomplished by finding pixels withmore » similar image curvature and divergence parameters compared to the seed pixel. Newly digitized pixels are treated as new seed positions, and hessian image analysis is used to direct the algorithm toward neighboring catheter pixels, and to make the algorithm insensitive to adjacent catheters that are unresolvable on CT, air pockets, and high Z artifacts. The algorithm was tested using 11 HDR treatment plans, including the Syed template, tandem and ovoid applicator, and multi-catheter lung brachytherapy. Digitization error was calculated by comparing manually determined catheter positions to those determined by the algorithm. Results: he digitization error was 0.23 mm ± 0.14 mm axially and 0.62 mm ± 0.13 mm longitudinally at the tip. The time of digitization, following initial seed placement was less than 1 second per catheter. The maximum total time required to digitize all tested applicators was 4 minutes (Syed template with 15 needles). Conclusion: This algorithm successfully digitizes HDR catheters for a variety of applicators with or without CT markers. The minimal axial error demonstrates the accuracy of the algorithm, and its insensitivity to image artifacts and challenging catheter positioning. Future work to automatically place initial seed positions would improve the algorithm speed.« less

Effects of Channel Modification on Detection and Dating of Fault Scarps

NASA Astrophysics Data System (ADS)

Sare, R.; Hilley, G. E.

2016-12-01

Template matching of scarp-like features could potentially generate morphologic age estimates for individual scarps over entire regions, but data noise and scarp modification limits detection of fault scarps by this method. Template functions based on diffusion in the cross-scarp direction may fail to accurately date scarps near channel boundaries. Where channels reduce scarp amplitudes, or where cross-scarp noise is significant, signal-to-noise ratios decrease and the scarp may be poorly resolved. In this contribution, we explore the bias in morphologic age of a complex scarp produced by systematic changes in fault scarp curvature. For example, fault scarps may be modified by encroaching channel banks and mass failure, lateral diffusion of material into a channel, or undercutting parallel to the base of a scarp. We quantify such biases on morphologic age estimates using a block offset model subject to two-dimensional linear diffusion. We carry out a synthetic study of the effects of two-dimensional transport on morphologic age calculated using a profile model, and compare these results to a well- studied and constrained site along the San Andreas Fault at Wallace Creek, CA. This study serves as a first step towards defining regions of high confidence in template matching results based on scarp length, channel geometry, and near-scarp topography.

A roadmap of clustering algorithms: finding a match for a biomedical application.

PubMed

Andreopoulos, Bill; An, Aijun; Wang, Xiaogang; Schroeder, Michael

2009-05-01

Clustering is ubiquitously applied in bioinformatics with hierarchical clustering and k-means partitioning being the most popular methods. Numerous improvements of these two clustering methods have been introduced, as well as completely different approaches such as grid-based, density-based and model-based clustering. For improved bioinformatics analysis of data, it is important to match clusterings to the requirements of a biomedical application. In this article, we present a set of desirable clustering features that are used as evaluation criteria for clustering algorithms. We review 40 different clustering algorithms of all approaches and datatypes. We compare algorithms on the basis of desirable clustering features, and outline algorithms' benefits and drawbacks as a basis for matching them to biomedical applications.

High performance embedded system for real-time pattern matching

NASA Astrophysics Data System (ADS)

Sotiropoulou, C.-L.; Luciano, P.; Gkaitatzis, S.; Citraro, S.; Giannetti, P.; Dell'Orso, M.

2017-02-01

In this paper we present an innovative and high performance embedded system for real-time pattern matching. This system is based on the evolution of hardware and algorithms developed for the field of High Energy Physics and more specifically for the execution of extremely fast pattern matching for tracking of particles produced by proton-proton collisions in hadron collider experiments. A miniaturized version of this complex system is being developed for pattern matching in generic image processing applications. The system works as a contour identifier able to extract the salient features of an image. It is based on the principles of cognitive image processing, which means that it executes fast pattern matching and data reduction mimicking the operation of the human brain. The pattern matching can be executed by a custom designed Associative Memory chip. The reference patterns are chosen by a complex training algorithm implemented on an FPGA device. Post processing algorithms (e.g. pixel clustering) are also implemented on the FPGA. The pattern matching can be executed on a 2D or 3D space, on black and white or grayscale images, depending on the application and thus increasing exponentially the processing requirements of the system. We present the firmware implementation of the training and pattern matching algorithm, performance and results on a latest generation Xilinx Kintex Ultrascale FPGA device.

Functional annotation by sequence-weighted structure alignments: statistical analysis and case studies from the Protein 3000 structural genomics project in Japan.

PubMed

Standley, Daron M; Toh, Hiroyuki; Nakamura, Haruki

2008-09-01

A method to functionally annotate structural genomics targets, based on a novel structural alignment scoring function, is proposed. In the proposed score, position-specific scoring matrices are used to weight structurally aligned residue pairs to highlight evolutionarily conserved motifs. The functional form of the score is first optimized for discriminating domains belonging to the same Pfam family from domains belonging to different families but the same CATH or SCOP superfamily. In the optimization stage, we consider four standard weighting functions as well as our own, the "maximum substitution probability," and combinations of these functions. The optimized score achieves an area of 0.87 under the receiver-operating characteristic curve with respect to identifying Pfam families within a sequence-unique benchmark set of domain pairs. Confidence measures are then derived from the benchmark distribution of true-positive scores. The alignment method is next applied to the task of functionally annotating 230 query proteins released to the public as part of the Protein 3000 structural genomics project in Japan. Of these queries, 78 were found to align to templates with the same Pfam family as the query or had sequence identities > or = 30%. Another 49 queries were found to match more distantly related templates. Within this group, the template predicted by our method to be the closest functional relative was often not the most structurally similar. Several nontrivial cases are discussed in detail. Finally, 103 queries matched templates at the fold level, but not the family or superfamily level, and remain functionally uncharacterized. 2008 Wiley-Liss, Inc.

Hybrid markerless tracking of complex articulated motion in golf swings.

PubMed

Fung, Sim Kwoh; Sundaraj, Kenneth; Ahamed, Nizam Uddin; Kiang, Lam Chee; Nadarajah, Sivadev; Sahayadhas, Arun; Ali, Md Asraf; Islam, Md Anamul; Palaniappan, Rajkumar

2014-04-01

Sports video tracking is a research topic that has attained increasing attention due to its high commercial potential. A number of sports, including tennis, soccer, gymnastics, running, golf, badminton and cricket have been utilised to display the novel ideas in sports motion tracking. The main challenge associated with this research concerns the extraction of a highly complex articulated motion from a video scene. Our research focuses on the development of a markerless human motion tracking system that tracks the major body parts of an athlete straight from a sports broadcast video. We proposed a hybrid tracking method, which consists of a combination of three algorithms (pyramidal Lucas-Kanade optical flow (LK), normalised correlation-based template matching and background subtraction), to track the golfer's head, body, hands, shoulders, knees and feet during a full swing. We then match, track and map the results onto a 2D articulated human stick model to represent the pose of the golfer over time. Our work was tested using two video broadcasts of a golfer, and we obtained satisfactory results. The current outcomes of this research can play an important role in enhancing the performance of a golfer, provide vital information to sports medicine practitioners by providing technically sound guidance on movements and should assist to diminish the risk of golfing injuries. Copyright © 2013 Elsevier Ltd. All rights reserved.

Underwater terrain-aided navigation system based on combination matching algorithm.

PubMed

Li, Peijuan; Sheng, Guoliang; Zhang, Xiaofei; Wu, Jingqiu; Xu, Baochun; Liu, Xing; Zhang, Yao

2018-07-01

Considering that the terrain-aided navigation (TAN) system based on iterated closest contour point (ICCP) algorithm diverges easily when the indicative track of strapdown inertial navigation system (SINS) is large, Kalman filter is adopted in the traditional ICCP algorithm, difference between matching result and SINS output is used as the measurement of Kalman filter, then the cumulative error of the SINS is corrected in time by filter feedback correction, and the indicative track used in ICCP is improved. The mathematic model of the autonomous underwater vehicle (AUV) integrated into the navigation system and the observation model of TAN is built. Proper matching point number is designated by comparing the simulation results of matching time and matching precision. Simulation experiments are carried out according to the ICCP algorithm and the mathematic model. It can be concluded from the simulation experiments that the navigation accuracy and stability are improved with the proposed combinational algorithm in case that proper matching point number is engaged. It will be shown that the integrated navigation system is effective in prohibiting the divergence of the indicative track and can meet the requirements of underwater, long-term and high precision of the navigation system for autonomous underwater vehicles. Copyright © 2017. Published by Elsevier Ltd.

Stereo-Based Region-Growing using String Matching

NASA Technical Reports Server (NTRS)

Mandelbaum, Robert; Mintz, Max

1995-01-01

We present a novel stereo algorithm based on a coarse texture segmentation preprocessing phase. Matching is performed using a string comparison. Matching sub-strings correspond to matching sequences of textures. Inter-scanline clustering of matching sub-strings yields regions of matching texture. The shape of these regions yield information concerning object's height, width and azimuthal position relative to the camera pair. Hence, rather than the standard dense depth map, the output of this algorithm is a segmentation of objects in the scene. Such a format is useful for the integration of stereo with other sensor modalities on a mobile robotic platform. It is also useful for localization; the height and width of a detected object may be used for landmark recognition, while depth and relative azimuthal location determine pose. The algorithm does not rely on the monotonicity of order of image primitives. Occlusions, exposures, and foreshortening effects are not problematic. The algorithm can deal with certain types of transparencies. It is computationally efficient, and very amenable to parallel implementation. Further, the epipolar constraints may be relaxed to some small but significant degree. A version of the algorithm has been implemented and tested on various types of images. It performs best on random dot stereograms, on images with easily filtered backgrounds (as in synthetic images), and on real scenes with uncontrived backgrounds.

A portable MPI-based parallel vector template library

NASA Technical Reports Server (NTRS)

Sheffler, Thomas J.

1995-01-01

This paper discusses the design and implementation of a polymorphic collection library for distributed address-space parallel computers. The library provides a data-parallel programming model for C++ by providing three main components: a single generic collection class, generic algorithms over collections, and generic algebraic combining functions. Collection elements are the fourth component of a program written using the library and may be either of the built-in types of C or of user-defined types. Many ideas are borrowed from the Standard Template Library (STL) of C++, although a restricted programming model is proposed because of the distributed address-space memory model assumed. Whereas the STL provides standard collections and implementations of algorithms for uniprocessors, this paper advocates standardizing interfaces that may be customized for different parallel computers. Just as the STL attempts to increase programmer productivity through code reuse, a similar standard for parallel computers could provide programmers with a standard set of algorithms portable across many different architectures. The efficacy of this approach is verified by examining performance data collected from an initial implementation of the library running on an IBM SP-2 and an Intel Paragon.

A Portable MPI-Based Parallel Vector Template Library

NASA Technical Reports Server (NTRS)

Sheffler, Thomas J.

1995-01-01

This paper discusses the design and implementation of a polymorphic collection library for distributed address-space parallel computers. The library provides a data-parallel programming model for C + + by providing three main components: a single generic collection class, generic algorithms over collections, and generic algebraic combining functions. Collection elements are the fourth component of a program written using the library and may be either of the built-in types of c or of user-defined types. Many ideas are borrowed from the Standard Template Library (STL) of C++, although a restricted programming model is proposed because of the distributed address-space memory model assumed. Whereas the STL provides standard collections and implementations of algorithms for uniprocessors, this paper advocates standardizing interfaces that may be customized for different parallel computers. Just as the STL attempts to increase programmer productivity through code reuse, a similar standard for parallel computers could provide programmers with a standard set of algorithms portable across many different architectures. The efficacy of this approach is verified by examining performance data collected from an initial implementation of the library running on an IBM SP-2 and an Intel Paragon.

Performance evaluation of non-targeted peak-based cross-sample analysis for comprehensive two-dimensional gas chromatography-mass spectrometry data and application to processed hazelnut profiling.

PubMed

Kiefl, Johannes; Cordero, Chiara; Nicolotti, Luca; Schieberle, Peter; Reichenbach, Stephen E; Bicchi, Carlo

2012-06-22

The continuous interest in non-targeted profiling induced the development of tools for automated cross-sample analysis. Such tools were found to be selective or not comprehensive thus delivering a biased view on the qualitative/quantitative peak distribution across 2D sample chromatograms. Therefore, the performance of non-targeted approaches needs to be critically evaluated. This study focused on the development of a validation procedure for non-targeted, peak-based, GC×GC-MS data profiling. The procedure introduced performance parameters such as specificity, precision, accuracy, and uncertainty for a profiling method known as Comprehensive Template Matching. The performance was assessed by applying a three-week validation protocol based on CITAC/EURACHEM guidelines. Optimized ¹D and ²D retention times search windows, MS match factor threshold, detection threshold, and template threshold were evolved from two training sets by a semi-automated learning process. The effectiveness of proposed settings to consistently match 2D peak patterns was established by evaluating the rate of mismatched peaks and was expressed in terms of results accuracy. The study utilized 23 different 2D peak patterns providing the chemical fingerprints of raw and roasted hazelnuts (Corylus avellana L.) from different geographical origins, of diverse varieties and different roasting degrees. The validation results show that non-targeted peak-based profiling can be reliable with error rates lower than 10% independent of the degree of analytical variance. The optimized Comprehensive Template Matching procedure was employed to study hazelnut roasting profiles and in particular to find marker compounds strongly dependent on the thermal treatment, and to establish the correlation of potential marker compounds to geographical origin and variety/cultivar and finally to reveal the characteristic release of aroma active compounds. Copyright © 2012 Elsevier B.V. All rights reserved.

Monoplane 3D-2D registration of cerebral angiograms based on multi-objective stratified optimization

NASA Astrophysics Data System (ADS)

Aksoy, T.; Špiclin, Ž.; Pernuš, F.; Unal, G.

2017-12-01

Registration of 3D pre-interventional to 2D intra-interventional medical images has an increasingly important role in surgical planning, navigation and treatment, because it enables the physician to co-locate depth information given by pre-interventional 3D images with the live information in intra-interventional 2D images such as x-ray. Most tasks during image-guided interventions are carried out under a monoplane x-ray, which is a highly ill-posed problem for state-of-the-art 3D to 2D registration methods. To address the problem of rigid 3D-2D monoplane registration we propose a novel multi-objective stratified parameter optimization, wherein a small set of high-magnitude intensity gradients are matched between the 3D and 2D images. The stratified parameter optimization matches rotation templates to depth templates, first sampled from projected 3D gradients and second from the 2D image gradients, so as to recover 3D rigid-body rotations and out-of-plane translation. The objective for matching was the gradient magnitude correlation coefficient, which is invariant to in-plane translation. The in-plane translations are then found by locating the maximum of the gradient phase correlation between the best matching pair of rotation and depth templates. On twenty pairs of 3D and 2D images of ten patients undergoing cerebral endovascular image-guided intervention the 3D to monoplane 2D registration experiments were setup with a rather high range of initial mean target registration error from 0 to 100 mm. The proposed method effectively reduced the registration error to below 2 mm, which was further refined by a fast iterative method and resulted in a high final registration accuracy (0.40 mm) and high success rate (> 96%). Taking into account a fast execution time below 10 s, the observed performance of the proposed method shows a high potential for application into clinical image-guidance systems.

Self-calibration of a noisy multiple-sensor system with genetic algorithms

NASA Astrophysics Data System (ADS)

Brooks, Richard R.; Iyengar, S. Sitharama; Chen, Jianhua

1996-01-01

This paper explores an image processing application of optimization techniques which entails interpreting noisy sensor data. The application is a generalization of image correlation; we attempt to find the optimal gruence which matches two overlapping gray-scale images corrupted with noise. Both taboo search and genetic algorithms are used to find the parameters which match the two images. A genetic algorithm approach using an elitist reproduction scheme is found to provide significantly superior results. The presentation includes a graphic presentation of the paths taken by tabu search and genetic algorithms when trying to find the best possible match between two corrupted images.

Joint Seismic-Geodetic Algorithm for Finite-Fault Detection and Slip Inversion in the West Coast ShakeAlert System

NASA Astrophysics Data System (ADS)

Smith, D. E.; Felizardo, C.; Minson, S. E.; Boese, M.; Langbein, J. O.; Murray, J. R.

2016-12-01

Finite-fault source algorithms can greatly benefit earthquake early warning (EEW) systems. Estimates of finite-fault parameters provide spatial information, which can significantly improve real-time shaking calculations and help with disaster response. In this project, we have focused on integrating a finite-fault seismic-geodetic algorithm into the West Coast ShakeAlert framework. The seismic part is FinDer 2, a C++ version of the algorithm developed by Böse et al. (2012). It interpolates peak ground accelerations and calculates the best fault length and strike from template matching. The geodetic part is a C++ version of BEFORES, the algorithm developed by Minson et al. (2014) that uses a Bayesian methodology to search for the most probable slip distribution on a fault of unknown orientation. Ultimately, these two will be used together where FinDer generates a Bayesian prior for BEFORES via the methodology of Minson et al. (2015), and the joint solution will generate estimates of finite-fault extent, strike, dip, best slip distribution, and magnitude. We have created C++ versions of both FinDer and BEFORES using open source libraries and have developed a C++ Application Protocol Interface (API) for them both. Their APIs allow FinDer and BEFORES to contribute to the ShakeAlert system via an open source messaging system, ActiveMQ. FinDer has been receiving real-time data, detecting earthquakes, and reporting messages on the development system for several months. We are also testing FinDer extensively with Earthworm tankplayer files. BEFORES has been tested with ActiveMQ messaging in the ShakeAlert framework, and works off a FinDer trigger. We are finishing the FinDer-BEFORES connections in this framework, and testing this system via seismic-geodetic tankplayer files. This will include actual and simulated data.

A KARAOKE System Singing Evaluation Method that More Closely Matches Human Evaluation

NASA Astrophysics Data System (ADS)

Takeuchi, Hideyo; Hoguro, Masahiro; Umezaki, Taizo

KARAOKE is a popular amusement for old and young. Many KARAOKE machines have singing evaluation function. However, it is often said that the scores given by KARAOKE machines do not match human evaluation. In this paper a KARAOKE scoring method strongly correlated with human evaluation is proposed. This paper proposes a way to evaluate songs based on the distance between singing pitch and musical scale, employing a vibrato extraction method based on template matching of spectrum. The results show that correlation coefficients between scores given by the proposed system and human evaluation are -0.76∼-0.89.

Implementation of a Real-Time Stacking Algorithm in a Photogrammetric Digital Camera for Uavs

NASA Astrophysics Data System (ADS)

Audi, A.; Pierrot-Deseilligny, M.; Meynard, C.; Thom, C.

2017-08-01

In the recent years, unmanned aerial vehicles (UAVs) have become an interesting tool in aerial photography and photogrammetry activities. In this context, some applications (like cloudy sky surveys, narrow-spectral imagery and night-vision imagery) need a longexposure time where one of the main problems is the motion blur caused by the erratic camera movements during image acquisition. This paper describes an automatic real-time stacking algorithm which produces a high photogrammetric quality final composite image with an equivalent long-exposure time using several images acquired with short-exposure times. Our method is inspired by feature-based image registration technique. The algorithm is implemented on the light-weight IGN camera, which has an IMU sensor and a SoC/FPGA. To obtain the correct parameters for the resampling of images, the presented method accurately estimates the geometrical relation between the first and the Nth image, taking into account the internal parameters and the distortion of the camera. Features are detected in the first image by the FAST detector, than homologous points on other images are obtained by template matching aided by the IMU sensors. The SoC/FPGA in the camera is used to speed up time-consuming parts of the algorithm such as features detection and images resampling in order to achieve a real-time performance as we want to write only the resulting final image to save bandwidth on the storage device. The paper includes a detailed description of the implemented algorithm, resource usage summary, resulting processing time, resulting images, as well as block diagrams of the described architecture. The resulting stacked image obtained on real surveys doesn't seem visually impaired. Timing results demonstrate that our algorithm can be used in real-time since its processing time is less than the writing time of an image in the storage device. An interesting by-product of this algorithm is the 3D rotation estimated by a photogrammetric method between poses, which can be used to recalibrate in real-time the gyrometers of the IMU.

Gaia Data Release 1. Cross-match with external catalogues. Algorithm and results

NASA Astrophysics Data System (ADS)

Marrese, P. M.; Marinoni, S.; Fabrizio, M.; Giuffrida, G.

2017-11-01

Context. Although the Gaia catalogue on its own will be a very powerful tool, it is the combination of this highly accurate archive with other archives that will truly open up amazing possibilities for astronomical research. The advanced interoperation of archives is based on cross-matching, leaving the user with the feeling of working with one single data archive. The data retrieval should work not only across data archives, but also across wavelength domains. The first step for seamless data access is the computation of the cross-match between Gaia and external surveys. Aims: The matching of astronomical catalogues is a complex and challenging problem both scientifically and technologically (especially when matching large surveys like Gaia). We describe the cross-match algorithm used to pre-compute the match of Gaia Data Release 1 (DR1) with a selected list of large publicly available optical and IR surveys. Methods: The overall principles of the adopted cross-match algorithm are outlined. Details are given on the developed algorithm, including the methods used to account for position errors, proper motions, and environment; to define the neighbours; and to define the figure of merit used to select the most probable counterpart. Results: Statistics on the results are also given. The results of the cross-match are part of the official Gaia DR1 catalogue.

17 CFR Appendix A to Part 37 - Guidance on Compliance With Registration Criteria

Code of Federal Regulations, 2011 CFR

2011-04-01

... facility should include the system's trade-matching algorithm and order entry procedures. A submission involving a trade-matching algorithm that is based on order priority factors other than on a best price/earliest time basis should include a brief explanation of the alternative algorithm. (b) A board of trade's...

17 CFR Appendix A to Part 37 - Guidance on Compliance With Registration Criteria

Code of Federal Regulations, 2012 CFR

2012-04-01

... facility should include the system's trade-matching algorithm and order entry procedures. A submission involving a trade-matching algorithm that is based on order priority factors other than on a best price/earliest time basis should include a brief explanation of the alternative algorithm. (b) A board of trade's...

Block-suffix shifting: fast, simultaneous medical concept set identification in large medical record corpora.

PubMed

Liu, Ying; Lita, Lucian Vlad; Niculescu, Radu Stefan; Mitra, Prasenjit; Giles, C Lee

2008-11-06

Owing to new advances in computer hardware, large text databases have become more prevalent than ever.Automatically mining information from these databases proves to be a challenge due to slow pattern/string matching techniques. In this paper we present a new, fast multi-string pattern matching method based on the well known Aho-Chorasick algorithm. Advantages of our algorithm include:the ability to exploit the natural structure of text, the ability to perform significant character shifting, avoiding backtracking jumps that are not useful, efficiency in terms of matching time and avoiding the typical "sub-string" false positive errors.Our algorithm is applicable to many fields with free text, such as the health care domain and the scientific document field. In this paper, we apply the BSS algorithm to health care data and mine hundreds of thousands of medical concepts from a large Electronic Medical Record (EMR) corpora simultaneously and efficiently. Experimental results show the superiority of our algorithm when compared with the top of the line multi-string matching algorithms.

An Evolutionary Algorithm for Fast Intensity Based Image Matching Between Optical and SAR Satellite Imagery

NASA Astrophysics Data System (ADS)

Fischer, Peter; Schuegraf, Philipp; Merkle, Nina; Storch, Tobias

2018-04-01

This paper presents a hybrid evolutionary algorithm for fast intensity based matching between satellite imagery from SAR and very high-resolution (VHR) optical sensor systems. The precise and accurate co-registration of image time series and images of different sensors is a key task in multi-sensor image processing scenarios. The necessary preprocessing step of image matching and tie-point detection is divided into a search problem and a similarity measurement. Within this paper we evaluate the use of an evolutionary search strategy for establishing the spatial correspondence between satellite imagery of optical and radar sensors. The aim of the proposed algorithm is to decrease the computational costs during the search process by formulating the search as an optimization problem. Based upon the canonical evolutionary algorithm, the proposed algorithm is adapted for SAR/optical imagery intensity based matching. Extensions are drawn using techniques like hybridization (e.g. local search) and others to lower the number of objective function calls and refine the result. The algorithm significantely decreases the computational costs whilst finding the optimal solution in a reliable way.

Poor textural image tie point matching via graph theory

NASA Astrophysics Data System (ADS)

Yuan, Xiuxiao; Chen, Shiyu; Yuan, Wei; Cai, Yang

2017-07-01

Feature matching aims to find corresponding points to serve as tie points between images. Robust matching is still a challenging task when input images are characterized by low contrast or contain repetitive patterns, occlusions, or homogeneous textures. In this paper, a novel feature matching algorithm based on graph theory is proposed. This algorithm integrates both geometric and radiometric constraints into an edge-weighted (EW) affinity tensor. Tie points are then obtained by high-order graph matching. Four pairs of poor textural images covering forests, deserts, bare lands, and urban areas are tested. For comparison, three state-of-the-art matching techniques, namely, scale-invariant feature transform (SIFT), speeded up robust features (SURF), and features from accelerated segment test (FAST), are also used. The experimental results show that the matching recall obtained by SIFT, SURF, and FAST varies from 0 to 35% in different types of poor textures. However, through the integration of both geometry and radiometry and the EW strategy, the recall obtained by the proposed algorithm is better than 50% in all four image pairs. The better matching recall improves the number of correct matches, dispersion, and positional accuracy.

Reducing the worst case running times of a family of RNA and CFG problems, using Valiant's approach.

PubMed

Zakov, Shay; Tsur, Dekel; Ziv-Ukelson, Michal

2011-08-18

RNA secondary structure prediction is a mainstream bioinformatic domain, and is key to computational analysis of functional RNA. In more than 30 years, much research has been devoted to defining different variants of RNA structure prediction problems, and to developing techniques for improving prediction quality. Nevertheless, most of the algorithms in this field follow a similar dynamic programming approach as that presented by Nussinov and Jacobson in the late 70's, which typically yields cubic worst case running time algorithms. Recently, some algorithmic approaches were applied to improve the complexity of these algorithms, motivated by new discoveries in the RNA domain and by the need to efficiently analyze the increasing amount of accumulated genome-wide data. We study Valiant's classical algorithm for Context Free Grammar recognition in sub-cubic time, and extract features that are common to problems on which Valiant's approach can be applied. Based on this, we describe several problem templates, and formulate generic algorithms that use Valiant's technique and can be applied to all problems which abide by these templates, including many problems within the world of RNA Secondary Structures and Context Free Grammars. The algorithms presented in this paper improve the theoretical asymptotic worst case running time bounds for a large family of important problems. It is also possible that the suggested techniques could be applied to yield a practical speedup for these problems. For some of the problems (such as computing the RNA partition function and base-pair binding probabilities), the presented techniques are the only ones which are currently known for reducing the asymptotic running time bounds of the standard algorithms.

Reducing the worst case running times of a family of RNA and CFG problems, using Valiant's approach

PubMed Central

2011-01-01

Background RNA secondary structure prediction is a mainstream bioinformatic domain, and is key to computational analysis of functional RNA. In more than 30 years, much research has been devoted to defining different variants of RNA structure prediction problems, and to developing techniques for improving prediction quality. Nevertheless, most of the algorithms in this field follow a similar dynamic programming approach as that presented by Nussinov and Jacobson in the late 70's, which typically yields cubic worst case running time algorithms. Recently, some algorithmic approaches were applied to improve the complexity of these algorithms, motivated by new discoveries in the RNA domain and by the need to efficiently analyze the increasing amount of accumulated genome-wide data. Results We study Valiant's classical algorithm for Context Free Grammar recognition in sub-cubic time, and extract features that are common to problems on which Valiant's approach can be applied. Based on this, we describe several problem templates, and formulate generic algorithms that use Valiant's technique and can be applied to all problems which abide by these templates, including many problems within the world of RNA Secondary Structures and Context Free Grammars. Conclusions The algorithms presented in this paper improve the theoretical asymptotic worst case running time bounds for a large family of important problems. It is also possible that the suggested techniques could be applied to yield a practical speedup for these problems. For some of the problems (such as computing the RNA partition function and base-pair binding probabilities), the presented techniques are the only ones which are currently known for reducing the asymptotic running time bounds of the standard algorithms. PMID:21851589

Improved pulse laser ranging algorithm based on high speed sampling

NASA Astrophysics Data System (ADS)

Gao, Xuan-yi; Qian, Rui-hai; Zhang, Yan-mei; Li, Huan; Guo, Hai-chao; He, Shi-jie; Guo, Xiao-kang

2016-10-01

Narrow pulse laser ranging achieves long-range target detection using laser pulse with low divergent beams. Pulse laser ranging is widely used in military, industrial, civil, engineering and transportation field. In this paper, an improved narrow pulse laser ranging algorithm is studied based on the high speed sampling. Firstly, theoretical simulation models have been built and analyzed including the laser emission and pulse laser ranging algorithm. An improved pulse ranging algorithm is developed. This new algorithm combines the matched filter algorithm and the constant fraction discrimination (CFD) algorithm. After the algorithm simulation, a laser ranging hardware system is set up to implement the improved algorithm. The laser ranging hardware system includes a laser diode, a laser detector and a high sample rate data logging circuit. Subsequently, using Verilog HDL language, the improved algorithm is implemented in the FPGA chip based on fusion of the matched filter algorithm and the CFD algorithm. Finally, the laser ranging experiment is carried out to test the improved algorithm ranging performance comparing to the matched filter algorithm and the CFD algorithm using the laser ranging hardware system. The test analysis result demonstrates that the laser ranging hardware system realized the high speed processing and high speed sampling data transmission. The algorithm analysis result presents that the improved algorithm achieves 0.3m distance ranging precision. The improved algorithm analysis result meets the expected effect, which is consistent with the theoretical simulation.

A new feature detection mechanism and its application in secured ECG transmission with noise masking.

PubMed

Sufi, Fahim; Khalil, Ibrahim

2009-04-01

With cardiovascular disease as the number one killer of modern era, Electrocardiogram (ECG) is collected, stored and transmitted in greater frequency than ever before. However, in reality, ECG is rarely transmitted and stored in a secured manner. Recent research shows that eavesdropper can reveal the identity and cardiovascular condition from an intercepted ECG. Therefore, ECG data must be anonymized before transmission over the network and also stored as such in medical repositories. To achieve this, first of all, this paper presents a new ECG feature detection mechanism, which was compared against existing cross correlation (CC) based template matching algorithms. Two types of CC methods were used for comparison. Compared to the CC based approaches, which had 40% and 53% misclassification rates, the proposed detection algorithm did not perform any single misclassification. Secondly, a new ECG obfuscation method was designed and implemented on 15 subjects using added noises corresponding to each of the ECG features. This obfuscated ECG can be freely distributed over the internet without the necessity of encryption, since the original features needed to identify personal information of the patient remain concealed. Only authorized personnel possessing a secret key will be able to reconstruct the original ECG from the obfuscated ECG. Distribution of the would appear as regular ECG without encryption. Therefore, traditional decryption techniques including powerful brute force attack are useless against this obfuscation.

Deployable reconnaissance from a VTOL UAS in urban environments

NASA Astrophysics Data System (ADS)

Barnett, Shane; Bird, John; Culhane, Andrew; Sharkasi, Adam; Reinholtz, Charles

2007-04-01

Reconnaissance collection in unknown or hostile environments can be a dangerous and life threatening task. To reduce this risk, the Unmanned Systems Group at Virginia Tech has produced a fully autonomous reconnaissance system able to provide live video reconnaissance from outside and inside unknown structures. This system consists of an autonomous helicopter which launches a small reconnaissance pod inside a building and an operator control unit (OCU) on a ground station. The helicopter is a modified Bergen Industrial Twin using a Rotomotion flight controller and can fly missions of up to one half hour. The mission planning OCU can control the helicopter remotely through teleoperation or fully autonomously by GPS waypoints. A forward facing camera and template matching aid in navigation by identifying the target building. Once the target structure is identified, vision algorithms will center the UAS adjacent to open windows or doorways. Tunable parameters in the vision algorithm account for varying launch distances and opening sizes. Launch of the reconnaissance pod may be initiated remotely through a human in the loop or autonomously. Compressed air propels the half pound stationary pod or the larger mobile pod into the open portals. Once inside the building, the reconnaissance pod will then transmit live video back to the helicopter. The helicopter acts as a repeater node for increased video range and simplification of communication back to the ground station.

Tracking and recognition face in videos with incremental local sparse representation model

NASA Astrophysics Data System (ADS)

Wang, Chao; Wang, Yunhong; Zhang, Zhaoxiang

2013-10-01

This paper addresses the problem of tracking and recognizing faces via incremental local sparse representation. First a robust face tracking algorithm is proposed via employing local sparse appearance and covariance pooling method. In the following face recognition stage, with the employment of a novel template update strategy, which combines incremental subspace learning, our recognition algorithm adapts the template to appearance changes and reduces the influence of occlusion and illumination variation. This leads to a robust video-based face tracking and recognition with desirable performance. In the experiments, we test the quality of face recognition in real-world noisy videos on YouTube database, which includes 47 celebrities. Our proposed method produces a high face recognition rate at 95% of all videos. The proposed face tracking and recognition algorithms are also tested on a set of noisy videos under heavy occlusion and illumination variation. The tracking results on challenging benchmark videos demonstrate that the proposed tracking algorithm performs favorably against several state-of-the-art methods. In the case of the challenging dataset in which faces undergo occlusion and illumination variation, and tracking and recognition experiments under significant pose variation on the University of California, San Diego (Honda/UCSD) database, our proposed method also consistently demonstrates a high recognition rate.

Automated segmentation of ventricles from serial brain MRI for the quantification of volumetric changes associated with communicating hydrocephalus in patients with brain tumor

NASA Astrophysics Data System (ADS)

Pura, John A.; Hamilton, Allison M.; Vargish, Geoffrey A.; Butman, John A.; Linguraru, Marius George

2011-03-01

Accurate ventricle volume estimates could improve the understanding and diagnosis of postoperative communicating hydrocephalus. For this category of patients, associated changes in ventricle volume can be difficult to identify, particularly over short time intervals. We present an automated segmentation algorithm that evaluates ventricle size from serial brain MRI examination. The technique combines serial T1- weighted images to increase SNR and segments the means image to generate a ventricle template. After pre-processing, the segmentation is initiated by a fuzzy c-means clustering algorithm to find the seeds used in a combination of fast marching methods and geodesic active contours. Finally, the ventricle template is propagated onto the serial data via non-linear registration. Serial volume estimates were obtained in an automated robust and accurate manner from difficult data.

Research on rolling element bearing fault diagnosis based on genetic algorithm matching pursuit

NASA Astrophysics Data System (ADS)

Rong, R. W.; Ming, T. F.

2017-12-01

In order to solve the problem of slow computation speed, matching pursuit algorithm is applied to rolling bearing fault diagnosis, and the improvement are conducted from two aspects that are the construction of dictionary and the way to search for atoms. To be specific, Gabor function which can reflect time-frequency localization characteristic well is used to construct the dictionary, and the genetic algorithm to improve the searching speed. A time-frequency analysis method based on genetic algorithm matching pursuit (GAMP) algorithm is proposed. The way to set property parameters for the improvement of the decomposition results is studied. Simulation and experimental results illustrate that the weak fault feature of rolling bearing can be extracted effectively by this proposed method, at the same time, the computation speed increases obviously.

US-VISIT Identity Matching Algorithm Evaluation Program: ADIS Algorithm Evaluation Project Plan Update

DOE Office of Scientific and Technical Information (OSTI.GOV)

Grant, C W; Lenderman, J S; Gansemer, J D

This document is an update to the 'ADIS Algorithm Evaluation Project Plan' specified in the Statement of Work for the US-VISIT Identity Matching Algorithm Evaluation Program, as deliverable II.D.1. The original plan was delivered in August 2010. This document modifies the plan to reflect modified deliverables reflecting delays in obtaining a database refresh. This document describes the revised schedule of the program deliverables. The detailed description of the processes used, the statistical analysis processes and the results of the statistical analysis will be described fully in the program deliverables. The US-VISIT Identity Matching Algorithm Evaluation Program is work performed bymore » Lawrence Livermore National Laboratory (LLNL) under IAA HSHQVT-07-X-00002 P00004 from the Department of Homeland Security (DHS).« less

Integrating image quality in 2nu-SVM biometric match score fusion.

PubMed

Vatsa, Mayank; Singh, Richa; Noore, Afzel

2007-10-01

This paper proposes an intelligent 2nu-support vector machine based match score fusion algorithm to improve the performance of face and iris recognition by integrating the quality of images. The proposed algorithm applies redundant discrete wavelet transform to evaluate the underlying linear and non-linear features present in the image. A composite quality score is computed to determine the extent of smoothness, sharpness, noise, and other pertinent features present in each subband of the image. The match score and the corresponding quality score of an image are fused using 2nu-support vector machine to improve the verification performance. The proposed algorithm is experimentally validated using the FERET face database and the CASIA iris database. The verification performance and statistical evaluation show that the proposed algorithm outperforms existing fusion algorithms.

Template-guided vs. non-guided drilling in site preparation of dental implants.

PubMed

Scherer, Uta; Stoetzer, Marcus; Ruecker, Martin; Gellrich, Nils-Claudius; von See, Constantin

2015-07-01

Clinical success of oral implants is related to primary stability and osseointegration. These parameters are associated with delicate surgical techniques. We herein studied whether template-guided drilling has a significant influence on drillholes diameter and accuracy in an in vitro model. Fresh cadaveric porcine mandibles were used for drilling experiments of four experimental groups. Each group consisted of three operators, comparing guide templates for drilling with free-handed procedure. Operators without surgical knowledge were grouped together, contrasting highly experienced oral surgeons in other groups. A total of 180 drilling actions were performed, and diameters were recorded at multiple depth levels, with a precision measuring instrument. Template-guided drilling procedure improved accuracy on a very significant level in comparison with free-handed drilling operation (p ≤ 0.001). Inaccuracy of free-handed drilling became more significant in relation to measurement depth. High homogenic uniformity of template-guided drillholes was significantly stronger than unguided drilling operations by highly experienced oral surgeons (p ≤ 0.001). Template-guided drilling procedure leads to significantly enhanced accuracy. Significant results compared to free-handed drilling actions were achieved, irrespective of the clinical experience level of the operator. Template-guided drilling procedures lead to a more predictable clinical diameter. It shows that any set of instruments has to be carefully chosen to match the specific implant system. The current in vitro study is implicating an improvement of implant bed preparation but needs to be confirmed in clinical studies.

Periodic Two-Dimensional GaAs and InGaAs Quantum Rings Grown on GaAs (001) by Droplet Epitaxy.

PubMed

Tung, Kar Hoo Patrick; Huang, Jian; Danner, Aaron

2016-06-01

Growth of ordered GaAs and InGaAs quantum rings (QRs) in a patterned SiO2 nanohole template by molecular beam epitaxy (MBE) using droplet epitaxy (DE) process is demonstrated. DE is an MBE growth technique used to fabricate quantum nanostructures of high crystal quality by supplying group III and group V elements in separate phases. In this work, ordered QRs grown on an ordered nanohole template are compared to self-assembled QRs grown with the same DE technique without the nanohole template. This study allows us to understand and compare the surface kinetics of Ga and InGa droplets when a template is present. It is found that template-grown GaAs QRs form clustered rings which can be attributed to low mobility of Ga droplets resulting in multiple nucleation sites for QR formation when As is supplied. However, the case of template-grown InGaAs QRs only one ring is formed per nanohole; no clustering is observed. The outer QR diameter is a close match to the nanohole template diameter. This can be attributed to more mobile InGa droplets, which coalesce from an Ostwald ripening to form a single large droplet before As is supplied. Thus, well-patterned InGaAs QRs are demonstrated and the kinetics of their growth are better understood which could potentially lead to improvements in the future devices that require the unique properties of patterned QRs.

Templated biomimetic multifunctional coatings

NASA Astrophysics Data System (ADS)

Sun, Chih-Hung; Gonzalez, Adriel; Linn, Nicholas C.; Jiang, Peng; Jiang, Bin

2008-02-01

We report a bioinspired templating technique for fabricating multifunctional optical coatings that mimic both unique functionalities of antireflective moth eyes and superhydrophobic cicada wings. Subwavelength-structured fluoropolymer nipple arrays are created by a soft-lithography-like process. The utilization of fluoropolymers simultaneously enhances the antireflective performance and the hydrophobicity of the replicated films. The specular reflectivity matches the optical simulation using a thin-film multilayer model. The dependence of the size and the crystalline ordering of the replicated nipples on the resulting antireflective properties have also been investigated by experiment and modeling. These biomimetic materials may find important technological application in self-cleaning antireflection coatings.

Perception for rugged terrain

NASA Technical Reports Server (NTRS)

Kweon, In SO; Hebert, Martial; Kanade, Takeo

1989-01-01

A three-dimensional perception system for building a geometrical description of rugged terrain environments from range image data is presented with reference to the exploration of the rugged terrain of Mars. An intermediate representation consisting of an elevation map that includes an explicit representation of uncertainty and labeling of the occluded regions is proposed. The locus method used to convert range image to an elevation map is introduced, along with an uncertainty model based on this algorithm. Both the elevation map and the locus method are the basis of a terrain matching algorithm which does not assume any correspondences between range images. The two-stage algorithm consists of a feature-based matching algorithm to compute an initial transform and an iconic terrain matching algorithm to merge multiple range images into a uniform representation. Terrain modeling results on real range images of rugged terrain are presented. The algorithms considered are a fundamental part of the perception system for the Ambler, a legged locomotor.

Vocal learning beyond imitation: mechanisms of adaptive vocal development in songbirds and human infants

PubMed Central

Tchernichovski, Ofer; Marcus, Gary

2014-01-01

Studies of vocal learning in songbirds typically focus on the acquisition of sensory templates for song imitation and on the consequent process of matching song production to templates. However, functional vocal development also requires the capacity to adaptively diverge from sensory templates, and to flexibly assemble vocal units. Examples of adaptive divergence include the corrective imitation of abnormal songs, and the decreased tendency to copy overabundant syllables. Such frequency-dependent effects might mirror tradeoffs between the assimilation of group identity (culture) while establishing individual and flexibly expressive songs. Intriguingly, although the requirements for vocal plasticity vary across songbirds, and more so between birdsong and language, the capacity to flexibly assemble vocal sounds develops in a similar, stepwise manner across species. Therefore, universal features of vocal learning go well beyond the capacity to imitate. PMID:25005823

a Band Selection Method for High Precision Registration of Hyperspectral Image

NASA Astrophysics Data System (ADS)

Yang, H.; Li, X.

2018-04-01

During the registration of hyperspectral images and high spatial resolution images, too much bands in a hyperspectral image make it difficult to select bands with good registration performance. Terrible bands are possible to reduce matching speed and accuracy. To solve this problem, an algorithm based on Cram'er-Rao lower bound theory is proposed to select good matching bands in this paper. The algorithm applies the Cram'er-Rao lower bound theory to the study of registration accuracy, and selects good matching bands by CRLB parameters. Experiments show that the algorithm in this paper can choose good matching bands and provide better data for the registration of hyperspectral image and high spatial resolution image.

Magnitude and Peak Amplitude Relationship for Microseismicity Induced by a Hydraulic Fracture Experiment

NASA Astrophysics Data System (ADS)

Smith, T.; Arce, A. C.; Ji, C.

2016-12-01

Waveform cross-correlation technique is widely used to improve the detection of small magnitude events induced by hydraulic fracturing. However, when events are detected, assigning a reliable magnitude is a challenging task, especially considering their small signal amplitude and high background noise during injections. In this study, we adopt the Match & Locate algorithm (M&L, Zhang and Wen, 2015) to analyze seven hours of continuous seismic observations from a hydraulic fracturing experiment in Central California. The site of the stimulated region is only 300-400m away from a 16-receiver vertical-borehole array which spans 230 m. The sampling rate is 4000 Hz. Both the injection sites and borehole array are more than 1.7 km below the surface. This dataset has previously been studied by an industry group, producing a catalog of 1134 events with moment magnitudes (Mw) ranging from -3.1 to -0.9. In this study, we select 202 events from this catalog with high signal to noise ratios to use as templates. Our M&L analysis produces a new catalog that contains 2119 events, which is 10 times more detections than the number of templates and about two times the original catalog. Using these two catalogs, we investigate the relationship of moment magnitude difference (ΔMW) and local magnitude difference (ΔML) between the detected event and corresponding template event. ΔML is computed using the peak amplitude ratio between the detected and template event for each channel. Our analysis yields an empirical relationship of ΔMW=0.64-0.65ΔML with an R2 of 0.99. The coefficient of 2/3 suggests that the information of the event's corner frequency is entirely lost (Hanks and Boore, 1984). The cause might not be unique, which implies that Earth's attenuation at this depth range (>1.7 km) is significant; or the 4000 Hz sampling rate is not sufficient. This relationship is crucial to estimate the b-value of the microseismicity induced by hydraulic fracture experiments. The analysis using the M&L catalog with the relation ΔMW = 2/3*ΔML , results in a normal b-value of 1.1, whereas a smaller b value of 0.88 is be obtained if ΔMW = ΔML.

Quantifying Normal Craniofacial Form and Baseline Craniofacial Asymmetry in the Pediatric Population.

PubMed

Cho, Min-Jeong; Hallac, Rami R; Ramesh, Jananie; Seaward, James R; Hermann, Nuno V; Darvann, Tron A; Lipira, Angelo; Kane, Alex A

2018-03-01

Restoring craniofacial symmetry is an important objective in the treatment of many craniofacial conditions. Normal form has been measured using anthropometry, cephalometry, and photography, yet all of these modalities have drawbacks. In this study, the authors define normal pediatric craniofacial form and craniofacial asymmetry using stereophotogrammetric images, which capture a densely sampled set of points on the form. After institutional review board approval, normal, healthy children (n = 533) with no known craniofacial abnormalities were recruited at well-child visits to undergo full head stereophotogrammetric imaging. The children's ages ranged from 0 to 18 years. A symmetric three-dimensional template was registered and scaled to each individual scan using 25 manually placed landmarks. The template was deformed to each subject's three-dimensional scan using a thin-plate spline algorithm and closest point matching. Age-based normal facial models were derived. Mean facial asymmetry and statistical characteristics of the population were calculated. The mean head asymmetry across all pediatric subjects was 1.5 ± 0.5 mm (range, 0.46 to 4.78 mm), and the mean facial asymmetry was 1.2 ± 0.6 mm (range, 0.4 to 5.4 mm). There were no significant differences in the mean head or facial asymmetry with age, sex, or race. Understanding the "normal" form and baseline distribution of asymmetry is an important anthropomorphic foundation. The authors present a method to quantify normal craniofacial form and baseline asymmetry in a large pediatric sample. The authors found that the normal pediatric craniofacial form is asymmetric, and does not change in magnitude with age, sex, or race.

The Elementary Operations of Human Vision Are Not Reducible to Template-Matching

PubMed Central

Neri, Peter

2015-01-01

It is generally acknowledged that biological vision presents nonlinear characteristics, yet linear filtering accounts of visual processing are ubiquitous. The template-matching operation implemented by the linear-nonlinear cascade (linear filter followed by static nonlinearity) is the most widely adopted computational tool in systems neuroscience. This simple model achieves remarkable explanatory power while retaining analytical tractability, potentially extending its reach to a wide range of systems and levels in sensory processing. The extent of its applicability to human behaviour, however, remains unclear. Because sensory stimuli possess multiple attributes (e.g. position, orientation, size), the issue of applicability may be asked by considering each attribute one at a time in relation to a family of linear-nonlinear models, or by considering all attributes collectively in relation to a specified implementation of the linear-nonlinear cascade. We demonstrate that human visual processing can operate under conditions that are indistinguishable from linear-nonlinear transduction with respect to substantially different stimulus attributes of a uniquely specified target signal with associated behavioural task. However, no specific implementation of a linear-nonlinear cascade is able to account for the entire collection of results across attributes; a satisfactory account at this level requires the introduction of a small gain-control circuit, resulting in a model that no longer belongs to the linear-nonlinear family. Our results inform and constrain efforts at obtaining and interpreting comprehensive characterizations of the human sensory process by demonstrating its inescapably nonlinear nature, even under conditions that have been painstakingly fine-tuned to facilitate template-matching behaviour and to produce results that, at some level of inspection, do conform to linear filtering predictions. They also suggest that compliance with linear transduction may be the targeted outcome of carefully crafted nonlinear circuits, rather than default behaviour exhibited by basic components. PMID:26556758

Source mechanism of small long-period events at Mount St. Helens in July 2005 using template matching, phase-weighted stacking, and full-waveform inversion

USGS Publications Warehouse

Matoza, Robin S.; Chouet, Bernard A.; Dawson, Phillip B.; Shearer, Peter M.; Haney, Matthew M.; Waite, Gregory P.; Moran, Seth C.; Mikesell, T. Dylan

2015-01-01

Long-period (LP, 0.5-5 Hz) seismicity, observed at volcanoes worldwide, is a recognized signature of unrest and eruption. Cyclic LP “drumbeating” was the characteristic seismicity accompanying the sustained dome-building phase of the 2004–2008 eruption of Mount St. Helens (MSH), WA. However, together with the LP drumbeating was a near-continuous, randomly occurring series of tiny LP seismic events (LP “subevents”), which may hold important additional information on the mechanism of seismogenesis at restless volcanoes. We employ template matching, phase-weighted stacking, and full-waveform inversion to image the source mechanism of one multiplet of these LP subevents at MSH in July 2005. The signal-to-noise ratios of the individual events are too low to produce reliable waveform-inversion results, but the events are repetitive and can be stacked. We apply network-based template matching to 8 days of continuous velocity waveform data from 29 June to 7 July 2005 using a master event to detect 822 network triggers. We stack waveforms for 359 high-quality triggers at each station and component, using a combination of linear and phase-weighted stacking to produce clean stacks for use in waveform inversion. The derived source mechanism pointsto the volumetric oscillation (~10 m3) of a subhorizontal crack located at shallow depth (~30 m) in an area to the south of Crater Glacier in the southern portion of the breached MSH crater. A possible excitation mechanism is the sudden condensation of metastable steam from a shallow pressurized hydrothermal system as it encounters cool meteoric water in the outer parts of the edifice, perhaps supplied from snow melt.

Systematic detection of seismic events at Mount St. Helens with an ultra-dense array

NASA Astrophysics Data System (ADS)

Meng, X.; Hartog, J. R.; Schmandt, B.; Hotovec-Ellis, A. J.; Hansen, S. M.; Vidale, J. E.; Vanderplas, J.

2016-12-01

During the summer of 2014, an ultra-dense array of 900 geophones was deployed around the crater of Mount St. Helens and continuously operated for 15 days. This dataset provides us an unprecedented opportunity to systematically detect seismic events around an active volcano and study their underlying mechanisms. We use a waveform-based matched filter technique to detect seismic events from this dataset. Due to the large volume of continuous data ( 1 TB), we performed the detection on the GPU cluster Stampede (https://www.tacc.utexas.edu/systems/stampede). We build a suite of template events from three catalogs: 1) the standard Pacific Northwest Seismic Network (PNSN) catalog (45 events); 2) the catalog from Hansen&Schmandt (2015) obtained with a reverse-time imaging method (212 events); and 3) the catalog identified with a matched filter technique using the PNSN permanent stations (190 events). By searching for template matches in the ultra-dense array, we find 2237 events. We then calibrate precise relative magnitudes for template and detected events, using a principal component fit to measure waveform amplitude ratios. The magnitude of completeness and b-value of the detected catalog is -0.5 and 1.1, respectively. Our detected catalog shows several intensive swarms, which are likely driven by fluid pressure transients in conduits or slip transients on faults underneath the volcano. We are currently relocating the detected catalog with HypoDD and measuring the seismic velocity changes at Mount St. Helens using the coda wave interferometry of detected repeating earthquakes. The accurate temporal-spatial migration pattern of seismicity and seismic property changes should shed light on the physical processes beneath Mount St. Helens.

A semi-automatic computer-aided method for surgical template design

NASA Astrophysics Data System (ADS)

Chen, Xiaojun; Xu, Lu; Yang, Yue; Egger, Jan

2016-02-01

This paper presents a generalized integrated framework of semi-automatic surgical template design. Several algorithms were implemented including the mesh segmentation, offset surface generation, collision detection, ruled surface generation, etc., and a special software named TemDesigner was developed. With a simple user interface, a customized template can be semi- automatically designed according to the preoperative plan. Firstly, mesh segmentation with signed scalar of vertex is utilized to partition the inner surface from the input surface mesh based on the indicated point loop. Then, the offset surface of the inner surface is obtained through contouring the distance field of the inner surface, and segmented to generate the outer surface. Ruled surface is employed to connect inner and outer surfaces. Finally, drilling tubes are generated according to the preoperative plan through collision detection and merging. It has been applied to the template design for various kinds of surgeries, including oral implantology, cervical pedicle screw insertion, iliosacral screw insertion and osteotomy, demonstrating the efficiency, functionality and generality of our method.

A semi-automatic computer-aided method for surgical template design

PubMed Central

Chen, Xiaojun; Xu, Lu; Yang, Yue; Egger, Jan

2016-01-01

This paper presents a generalized integrated framework of semi-automatic surgical template design. Several algorithms were implemented including the mesh segmentation, offset surface generation, collision detection, ruled surface generation, etc., and a special software named TemDesigner was developed. With a simple user interface, a customized template can be semi- automatically designed according to the preoperative plan. Firstly, mesh segmentation with signed scalar of vertex is utilized to partition the inner surface from the input surface mesh based on the indicated point loop. Then, the offset surface of the inner surface is obtained through contouring the distance field of the inner surface, and segmented to generate the outer surface. Ruled surface is employed to connect inner and outer surfaces. Finally, drilling tubes are generated according to the preoperative plan through collision detection and merging. It has been applied to the template design for various kinds of surgeries, including oral implantology, cervical pedicle screw insertion, iliosacral screw insertion and osteotomy, demonstrating the efficiency, functionality and generality of our method. PMID:26843434

A semi-automatic computer-aided method for surgical template design.

PubMed

Chen, Xiaojun; Xu, Lu; Yang, Yue; Egger, Jan

2016-02-04

This paper presents a generalized integrated framework of semi-automatic surgical template design. Several algorithms were implemented including the mesh segmentation, offset surface generation, collision detection, ruled surface generation, etc., and a special software named TemDesigner was developed. With a simple user interface, a customized template can be semi- automatically designed according to the preoperative plan. Firstly, mesh segmentation with signed scalar of vertex is utilized to partition the inner surface from the input surface mesh based on the indicated point loop. Then, the offset surface of the inner surface is obtained through contouring the distance field of the inner surface, and segmented to generate the outer surface. Ruled surface is employed to connect inner and outer surfaces. Finally, drilling tubes are generated according to the preoperative plan through collision detection and merging. It has been applied to the template design for various kinds of surgeries, including oral implantology, cervical pedicle screw insertion, iliosacral screw insertion and osteotomy, demonstrating the efficiency, functionality and generality of our method.

Template-based protein structure modeling using the RaptorX web server.

PubMed

Källberg, Morten; Wang, Haipeng; Wang, Sheng; Peng, Jian; Wang, Zhiyong; Lu, Hui; Xu, Jinbo

2012-07-19

A key challenge of modern biology is to uncover the functional role of the protein entities that compose cellular proteomes. To this end, the availability of reliable three-dimensional atomic models of proteins is often crucial. This protocol presents a community-wide web-based method using RaptorX (http://raptorx.uchicago.edu/) for protein secondary structure prediction, template-based tertiary structure modeling, alignment quality assessment and sophisticated probabilistic alignment sampling. RaptorX distinguishes itself from other servers by the quality of the alignment between a target sequence and one or multiple distantly related template proteins (especially those with sparse sequence profiles) and by a novel nonlinear scoring function and a probabilistic-consistency algorithm. Consequently, RaptorX delivers high-quality structural models for many targets with only remote templates. At present, it takes RaptorX ~35 min to finish processing a sequence of 200 amino acids. Since its official release in August 2011, RaptorX has processed ~6,000 sequences submitted by ~1,600 users from around the world.

Template-based protein structure modeling using the RaptorX web server

PubMed Central

Källberg, Morten; Wang, Haipeng; Wang, Sheng; Peng, Jian; Wang, Zhiyong; Lu, Hui; Xu, Jinbo

2016-01-01

A key challenge of modern biology is to uncover the functional role of the protein entities that compose cellular proteomes. To this end, the availability of reliable three-dimensional atomic models of proteins is often crucial. This protocol presents a community-wide web-based method using RaptorX (http://raptorx.uchicago.edu/) for protein secondary structure prediction, template-based tertiary structure modeling, alignment quality assessment and sophisticated probabilistic alignment sampling. RaptorX distinguishes itself from other servers by the quality of the alignment between a target sequence and one or multiple distantly related template proteins (especially those with sparse sequence profiles) and by a novel nonlinear scoring function and a probabilistic-consistency algorithm. Consequently, RaptorX delivers high-quality structural models for many targets with only remote templates. At present, it takes RaptorX ~35 min to finish processing a sequence of 200 amino acids. Since its official release in August 2011, RaptorX has processed ~6,000 sequences submitted by ~1,600 users from around the world. PMID:22814390

Tight Bounds for Minimax Grid Matching, with Applications to the Average Case Analysis of Algorithms.

DTIC Science & Technology

1986-05-01

AD-ft?l 552 TIGHT BOUNDS FOR NININAX GRID MATCHING WITH i APPLICATIONS TO THE AVERAGE C.. (U) MASSACHUSETTS INST OF TECH CAMBRIDGE LAS FOR COMPUTER...MASSACHUSETTS LABORATORYFORNSTITUTE OF COMPUTER SCIENCE TECHNOLOGY MIT/LCS/TM-298 TIGHT BOUNDS FOR MINIMAX GRID MATCHING, WITH APPLICATIONS TO THE AVERAGE...PERIOD COVERED Tight bounds for minimax grid matching, Interim research with applications to the average case May 1986 analysis of algorithms. 6

Searching social networks for subgraph patterns

NASA Astrophysics Data System (ADS)

Ogaard, Kirk; Kase, Sue; Roy, Heather; Nagi, Rakesh; Sambhoos, Kedar; Sudit, Moises

2013-06-01

Software tools for Social Network Analysis (SNA) are being developed which support various types of analysis of social networks extracted from social media websites (e.g., Twitter). Once extracted and stored in a database such social networks are amenable to analysis by SNA software. This data analysis often involves searching for occurrences of various subgraph patterns (i.e., graphical representations of entities and relationships). The authors have developed the Graph Matching Toolkit (GMT) which provides an intuitive Graphical User Interface (GUI) for a heuristic graph matching algorithm called the Truncated Search Tree (TruST) algorithm. GMT is a visual interface for graph matching algorithms processing large social networks. GMT enables an analyst to draw a subgraph pattern by using a mouse to select categories and labels for nodes and links from drop-down menus. GMT then executes the TruST algorithm to find the top five occurrences of the subgraph pattern within the social network stored in the database. GMT was tested using a simulated counter-insurgency dataset consisting of cellular phone communications within a populated area of operations in Iraq. The results indicated GMT (when executing the TruST graph matching algorithm) is a time-efficient approach to searching large social networks. GMT's visual interface to a graph matching algorithm enables intelligence analysts to quickly analyze and summarize the large amounts of data necessary to produce actionable intelligence.

INS/GPS/LiDAR Integrated Navigation System for Urban and Indoor Environments Using Hybrid Scan Matching Algorithm

PubMed Central

Gao, Yanbin; Liu, Shifei; Atia, Mohamed M.; Noureldin, Aboelmagd

2015-01-01

This paper takes advantage of the complementary characteristics of Global Positioning System (GPS) and Light Detection and Ranging (LiDAR) to provide periodic corrections to Inertial Navigation System (INS) alternatively in different environmental conditions. In open sky, where GPS signals are available and LiDAR measurements are sparse, GPS is integrated with INS. Meanwhile, in confined outdoor environments and indoors, where GPS is unreliable or unavailable and LiDAR measurements are rich, LiDAR replaces GPS to integrate with INS. This paper also proposes an innovative hybrid scan matching algorithm that combines the feature-based scan matching method and Iterative Closest Point (ICP) based scan matching method. The algorithm can work and transit between two modes depending on the number of matched line features over two scans, thus achieving efficiency and robustness concurrently. Two integration schemes of INS and LiDAR with hybrid scan matching algorithm are implemented and compared. Real experiments are performed on an Unmanned Ground Vehicle (UGV) for both outdoor and indoor environments. Experimental results show that the multi-sensor integrated system can remain sub-meter navigation accuracy during the whole trajectory. PMID:26389906

INS/GPS/LiDAR Integrated Navigation System for Urban and Indoor Environments Using Hybrid Scan Matching Algorithm.

PubMed

Gao, Yanbin; Liu, Shifei; Atia, Mohamed M; Noureldin, Aboelmagd

2015-09-15

This paper takes advantage of the complementary characteristics of Global Positioning System (GPS) and Light Detection and Ranging (LiDAR) to provide periodic corrections to Inertial Navigation System (INS) alternatively in different environmental conditions. In open sky, where GPS signals are available and LiDAR measurements are sparse, GPS is integrated with INS. Meanwhile, in confined outdoor environments and indoors, where GPS is unreliable or unavailable and LiDAR measurements are rich, LiDAR replaces GPS to integrate with INS. This paper also proposes an innovative hybrid scan matching algorithm that combines the feature-based scan matching method and Iterative Closest Point (ICP) based scan matching method. The algorithm can work and transit between two modes depending on the number of matched line features over two scans, thus achieving efficiency and robustness concurrently. Two integration schemes of INS and LiDAR with hybrid scan matching algorithm are implemented and compared. Real experiments are performed on an Unmanned Ground Vehicle (UGV) for both outdoor and indoor environments. Experimental results show that the multi-sensor integrated system can remain sub-meter navigation accuracy during the whole trajectory.

Feasibility study of patient-specific surgical templates for the fixation of pedicle screws.

PubMed

Salako, F; Aubin, C-E; Fortin, C; Labelle, H

2002-01-01

Surgery for scoliosis, as well as other posterior spinal surgeries, frequently uses pedicle screws to fix an instrumentation on the spine. Misplacement of a screw can lead to intra- and post-operative complications. The objective of this study is to design patient-specific surgical templates to guide the drilling operation. From the CT-scan of a vertebra, the optimal drilling direction and limit angles are computed from an inverse projection of the pedicle limits. The first template design uses a surface-to-surface registration method and was constructed in a CAD system by subtracting the vertebra from a rectangular prism and a cylinder with the optimal orientation. This template and the vertebra were built using rapid prototyping. The second design uses a point-to-surface registration method and has 6 adjustable screws to adjust the orientation and length of the drilling support device. A mechanism was designed to hold it in place on the spinal process. A virtual prototype was build with CATIA software. During the operation, the surgeon places either template on patient's vertebra until a perfect match is obtained before drilling. The second design seems better than the first one because it can be reused on different vertebra and is less sensible to registration errors. The next step is to build the second design and make experimental and simulations tests to evaluate the benefits of this template during a scoliosis operation.

3-Dimensional printing guide template assisted percutaneous vertebroplasty: Technical note.

PubMed

Li, Jian; Lin, JiSheng; Yang, Yong; Xu, JunChuan; Fei, Qi

2018-06-01

Percutaneous vertebroplasty (PVP) is currently considered as an effective treatment for pain caused by acute osteoporotic vertebral compression fracture. Recently, puncture-related complications are increasingly reported. It's important to find a precise technique to reduce the puncture-related complications. We report a case and discussed the novel surgical technique with step-by-step operating procedures, to introduce the precise PVP assisted by a 3-dimensional printing guide template. Based on the preoperative CT scan and infrared scan data, a well-designed individual guide template could be established in a 3-dimensional reconstruction software and printed out by a 3-dimensional printer. In real operation, by matching the guide template to patient's back skin, cement needles' insertion orientation and depth were easily established. Only 14 times C-arm fluoroscopy with HDF mode (total exposure dose was 4.5 mSv) were required during the procedure. The operation took only 17 min. Cement distribution in the vertebral body was very good without any puncture-related complications. Pain was significantly relieved after surgery. In conclusion, the novel precise 3-dimensional printing guide template system may allow (1) comprehensive visualization of the fractured vertebral body and the individual surgical planning, (2) the perfect fitting between skin and guide template to ensure the puncture stability and accuracy, and (3) increased puncture precision and decreased puncture-related complications, surgical time and radiation exposure. Copyright © 2018 Elsevier Ltd. All rights reserved.

Matching CCD images to a stellar catalog using locality-sensitive hashing

NASA Astrophysics Data System (ADS)

Liu, Bo; Yu, Jia-Zong; Peng, Qing-Yu

2018-02-01

The usage of a subset of observed stars in a CCD image to find their corresponding matched stars in a stellar catalog is an important issue in astronomical research. Subgraph isomorphic-based algorithms are the most widely used methods in star catalog matching. When more subgraph features are provided, the CCD images are recognized better. However, when the navigation feature database is large, the method requires more time to match the observing model. To solve this problem, this study investigates further and improves subgraph isomorphic matching algorithms. We present an algorithm based on a locality-sensitive hashing technique, which allocates quadrilateral models in the navigation feature database into different hash buckets and reduces the search range to the bucket in which the observed quadrilateral model is located. Experimental results indicate the effectivity of our method.

Novel techniques for data decomposition and load balancing for parallel processing of vision systems: Implementation and evaluation using a motion estimation system

NASA Technical Reports Server (NTRS)

Choudhary, Alok Nidhi; Leung, Mun K.; Huang, Thomas S.; Patel, Janak H.

1989-01-01

Computer vision systems employ a sequence of vision algorithms in which the output of an algorithm is the input of the next algorithm in the sequence. Algorithms that constitute such systems exhibit vastly different computational characteristics, and therefore, require different data decomposition techniques and efficient load balancing techniques for parallel implementation. However, since the input data for a task is produced as the output data of the previous task, this information can be exploited to perform knowledge based data decomposition and load balancing. Presented here are algorithms for a motion estimation system. The motion estimation is based on the point correspondence between the involved images which are a sequence of stereo image pairs. Researchers propose algorithms to obtain point correspondences by matching feature points among stereo image pairs at any two consecutive time instants. Furthermore, the proposed algorithms employ non-iterative procedures, which results in saving considerable amounts of computation time. The system consists of the following steps: (1) extraction of features; (2) stereo match of images in one time instant; (3) time match of images from consecutive time instants; (4) stereo match to compute final unambiguous points; and (5) computation of motion parameters.

Mechanistic design data from ODOT instrumented pavement sites : phase II report.

DOT National Transportation Integrated Search

2017-03-01

This investigation examined data obtained from three previously-instrumented pavement test sites in Oregon. Data processing algorithms and templates were developed for each test site that facilitated full processing of all the data to build databases...

Mechanistic design data from ODOT instrumented pavement sites : phase 1 report.

DOT National Transportation Integrated Search

2017-03-01

This investigation examined data obtained from three previously-instrumented pavement test sites in Oregon. Data processing algorithms and templates were developed for each test site that facilitated full processing of all the data to build databases...

A Palmprint Recognition Algorithm Using Phase-Only Correlation

NASA Astrophysics Data System (ADS)

Ito, Koichi; Aoki, Takafumi; Nakajima, Hiroshi; Kobayashi, Koji; Higuchi, Tatsuo

This paper presents a palmprint recognition algorithm using Phase-Only Correlation (POC). The use of phase components in 2D (two-dimensional) discrete Fourier transforms of palmprint images makes it possible to achieve highly robust image registration and matching. In the proposed algorithm, POC is used to align scaling, rotation and translation between two palmprint images, and evaluate similarity between them. Experimental evaluation using a palmprint image database clearly demonstrates efficient matching performance of the proposed algorithm.

Template-based de novo design for type II kinase inhibitors and its extented application to acetylcholinesterase inhibitors.

PubMed

Su, Bo-Han; Huang, Yi-Syuan; Chang, Chia-Yun; Tu, Yi-Shu; Tseng, Yufeng J

2013-10-31

There is a compelling need to discover type II inhibitors targeting the unique DFG-out inactive kinase conformation since they are likely to possess greater potency and selectivity relative to traditional type I inhibitors. Using a known inhibitor, such as a currently available and approved drug or inhibitor, as a template to design new drugs via computational de novo design is helpful when working with known ligand-receptor interactions. This study proposes a new template-based de novo design protocol to discover new inhibitors that preserve and also optimize the binding interactions of the type II kinase template. First, sorafenib (Nexavar) and nilotinib (Tasigna), two type II inhibitors with different ligand-receptor interactions, were selected as the template compounds. The five-step protocol can reassemble each drug from a large fragment library. Our procedure demonstrates that the selected template compounds can be successfully reassembled while the key ligand-receptor interactions are preserved. Furthermore, to demonstrate that the algorithm is able to construct more potent compounds, we considered kinase inhibitors and other protein dataset, acetylcholinesterase (AChE) inhibitors. The de novo optimization was initiated using a template compound possessing a less than optimal activity from a series of aminoisoquinoline and TAK-285 inhibiting type II kinases, and E2020 derivatives inhibiting AChE respectively. Three compounds with greater potency than the template compound were discovered that were also included in the original congeneric series. This template-based lead optimization protocol with the fragment library can help to design compounds with preferred binding interactions of known inhibitors automatically and further optimize the compounds in the binding pockets.

78 FR 26818 - Self-Regulatory Organizations; New York Stock Exchange LLC; Notice of Filing and Immediate...

Federal Register 2010, 2011, 2012, 2013, 2014

2013-05-08

... modifiers available to algorithms used by Floor brokers to route interest to the Exchange's matching engine...-Quotes entered into the matching engine by an algorithm on behalf of a Floor broker. STP modifiers would... algorithms removes impediments to and perfects the mechanism of a free and open market because there is a...