Science.gov

Sample records for 3d object detection

  1. Lifting Object Detection Datasets into 3D.

    PubMed

    Carreira, Joao; Vicente, Sara; Agapito, Lourdes; Batista, Jorge

    2016-07-01

    While data has certainly taken the center stage in computer vision in recent years, it can still be difficult to obtain in certain scenarios. In particular, acquiring ground truth 3D shapes of objects pictured in 2D images remains a challenging feat and this has hampered progress in recognition-based object reconstruction from a single image. Here we propose to bypass previous solutions such as 3D scanning or manual design, that scale poorly, and instead populate object category detection datasets semi-automatically with dense, per-object 3D reconstructions, bootstrapped from:(i) class labels, (ii) ground truth figure-ground segmentations and (iii) a small set of keypoint annotations. Our proposed algorithm first estimates camera viewpoint using rigid structure-from-motion and then reconstructs object shapes by optimizing over visual hull proposals guided by loose within-class shape similarity assumptions. The visual hull sampling process attempts to intersect an object's projection cone with the cones of minimal subsets of other similar objects among those pictured from certain vantage points. We show that our method is able to produce convincing per-object 3D reconstructions and to accurately estimate cameras viewpoints on one of the most challenging existing object-category detection datasets, PASCAL VOC. We hope that our results will re-stimulate interest on joint object recognition and 3D reconstruction from a single image. PMID:27295458

  2. Viewpoint-independent 3D object segmentation for randomly stacked objects using optical object detection

    NASA Astrophysics Data System (ADS)

    Chen, Liang-Chia; Nguyen, Thanh-Hung; Lin, Shyh-Tsong

    2015-10-01

    This work proposes a novel approach to segmenting randomly stacked objects in unstructured 3D point clouds, which are acquired by a random-speckle 3D imaging system for the purpose of automated object detection and reconstruction. An innovative algorithm is proposed; it is based on a novel concept of 3D watershed segmentation and the strategies for resolving over-segmentation and under-segmentation problems. Acquired 3D point clouds are first transformed into a corresponding orthogonally projected depth map along the optical imaging axis of the 3D sensor. A 3D watershed algorithm based on the process of distance transformation is then performed to detect the boundary, called the edge dam, between stacked objects and thereby to segment point clouds individually belonging to two stacked objects. Most importantly, an object-matching algorithm is developed to solve the over- and under-segmentation problems that may arise during the watershed segmentation. The feasibility and effectiveness of the method are confirmed experimentally. The results reveal that the proposed method is a fast and effective scheme for the detection and reconstruction of a 3D object in a random stack of such objects. In the experiments, the precision of the segmentation exceeds 95% and the recall exceeds 80%.

  3. 3D object detection from roadside data using laser scanners

    NASA Astrophysics Data System (ADS)

    Tang, Jimmy; Zakhor, Avideh

    2011-03-01

    The detection of objects on a given road path by vehicles equipped with range measurement devices is important to many civilian and military applications such as obstacle avoidance in autonomous navigation systems. In this thesis, we develop a method to detect objects of a specific size lying on a road using an acquisition vehicle equipped with forward looking Light Detection And Range (LiDAR) sensors and inertial navigation system. We use GPS data to accurately place the LiDAR points in a world map, extract point cloud clusters protruding from the road, and detect objects of interest using weighted random forest trees. We show that our proposed method is effective in identifying objects for several road datasets collected with various object locations and vehicle speeds.

  4. Improving object detection in 2D images using a 3D world model

    NASA Astrophysics Data System (ADS)

    Viggh, Herbert E. M.; Cho, Peter L.; Armstrong-Crews, Nicholas; Nam, Myra; Shah, Danelle C.; Brown, Geoffrey E.

    2014-05-01

    A mobile robot operating in a netcentric environment can utilize offboard resources on the network to improve its local perception. One such offboard resource is a world model built and maintained by other sensor systems. In this paper we present results from research into improving the performance of Deformable Parts Model object detection algorithms by using an offboard 3D world model. Experiments were run for detecting both people and cars in 2D photographs taken in an urban environment. After generating candidate object detections, a 3D world model built from airborne Light Detection and Ranging (LIDAR) and aerial photographs was used to filter out false alarm using several types of geometric reasoning. Comparison of the baseline detection performance to the performance after false alarm filtering showed a significant decrease in false alarms for a given probability of detection.

  5. Identification and Detection of Simple 3D Objects with Severely Blurred Vision

    PubMed Central

    Kallie, Christopher S.; Legge, Gordon E.; Yu, Deyue

    2012-01-01

    Purpose. Detecting and recognizing three-dimensional (3D) objects is an important component of the visual accessibility of public spaces for people with impaired vision. The present study investigated the impact of environmental factors and object properties on the recognition of objects by subjects who viewed physical objects with severely reduced acuity. Methods. The experiment was conducted in an indoor testing space. We examined detection and identification of simple convex objects by normally sighted subjects wearing diffusing goggles that reduced effective acuity to 20/900. We used psychophysical methods to examine the effect on performance of important environmental variables: viewing distance (from 10–24 feet, or 3.05–7.32 m) and illumination (overhead fluorescent and artificial window), and object variables: shape (boxes and cylinders), size (heights from 2–6 feet, or 0.61–1.83 m), and color (gray and white). Results. Object identification was significantly affected by distance, color, height, and shape, as well as interactions between illumination, color, and shape. A stepwise regression analysis showed that 64% of the variability in identification could be explained by object contrast values (58%) and object visual angle (6%). Conclusions. When acuity is severely limited, illumination, distance, color, height, and shape influence the identification and detection of simple 3D objects. These effects can be explained in large part by the impact of these variables on object contrast and visual angle. Basic design principles for improving object visibility are discussed. PMID:23111613

  6. Applying Mean-Shift - Clustering for 3D object detection in remote sensing data

    NASA Astrophysics Data System (ADS)

    Simon, Jürgen-Lorenz; Diederich, Malte; Troemel, Silke

    2013-04-01

    The timely warning and forecasting of high-impact weather events is crucial for life, safety and economy. Therefore, the development and improvement of methods for detection and nowcasting / short-term forecasting of these events is an ongoing research question. A new 3D object detection and tracking algorithm is presented. Within the project "object-based analysis and seamless predictin (OASE)" we address a better understanding and forecasting of convective events based on the synergetic use of remotely sensed data and new methods for detection, nowcasting, validation and assimilation. In order to gain advanced insight into the lifecycle of convective cells, we perform an object-detection on a new high-resolution 3D radar- and satellite based composite and plan to track the detected objects over time, providing us with a model of the lifecycle. The insights in the lifecycle will be used in order to improve prediction of convective events in the nowcasting time scale, as well as a new type of data to be assimilated into numerical weather models, thus seamlessly bridging the gap between nowcasting and NWP.. The object identification (or clustering) is performed using a technique borrowed from computer vision, called mean-shift clustering. Mean-Shift clustering works without many of the parameterizations or rigid threshold schemes employed by many existing schemes (e. g. KONRAD, TITAN, Trace-3D), which limit the tracking to fully matured, convective cells of significant size and/or strength. Mean-Shift performs without such limiting definitions, providing a wider scope for studying larger classes of phenomena and providing a vehicle for research into the object definition itself. Since the mean-shift clustering technique could be applied on many types of remote-sensing and model data for object detection, it is of general interest to the remote sensing and modeling community. The focus of the presentation is the introduction of this technique and the results of its

  7. The time course of configural change detection for novel 3-D objects.

    PubMed

    Favelle, Simone; Palmisano, Stephen

    2010-05-01

    The present study investigated the time course of visual information processing that is responsible for successful object change detection involving the configuration and shape of 3-D novel object parts. Using a one-shot change detection task, we manipulated stimulus and interstimulus mask durations (40-500 msec). Experiments 1A and 1B showed no change detection advantage for configuration at very short (40-msec) stimulus durations, but the configural advantage did emerge with durations between 80 and 160 msec. In Experiment 2, we showed that, at shorter stimulus durations, the number of parts changing was the best predictor of change detection performance. Finally, in Experiment 3, with a stimulus duration of 160 msec, configuration change detection was found to be highly accurate for each of the mask durations tested, suggesting a fast processing speed for this kind of change information. However, switch and shape change detection reached peak levels of accuracy only when mask durations were increased to 160 and 320 msec, respectively. We conclude that, with very short stimulus exposures, successful object change detection depends primarily on quantitative measures of change. However, with longer stimulus exposures, the qualitative nature of the change becomes progressively more important, resulting in the well-known configural advantage for change detection.

  8. Knowledge guided object detection and identification in 3D point clouds

    NASA Astrophysics Data System (ADS)

    Karmacharya, A.; Boochs, F.; Tietz, B.

    2015-05-01

    Modern instruments like laser scanner and 3D cameras or image based techniques like structure from motion produce huge point clouds as base for further object analysis. This has considerably changed the way of data compilation away from selective manually guided processes towards automatic and computer supported strategies. However it's still a long way to achieve the quality and robustness of manual processes as data sets are mostly very complex. Looking at existing strategies 3D data processing for object detections and reconstruction rely heavily on either data driven or model driven approaches. These approaches come with their limitation on depending highly on the nature of data and inability to handle any deviation. Furthermore, the lack of capabilities to integrate other data or information in between the processing steps further exposes their limitations. This restricts the approaches to be executed with strict predefined strategy and does not allow deviations when and if new unexpected situations arise. We propose a solution that induces intelligence in the processing activities through the usage of semantics. The solution binds the objects along with other related knowledge domains to the numerical processing to facilitate the detection of geometries and then uses experts' inference rules to annotate them. The solution was tested within the prototypical application of the research project "Wissensbasierte Detektion von Objekten in Punktwolken für Anwendungen im Ingenieurbereich (WiDOP)". The flexibility of the solution is demonstrated through two entirely different USE Case scenarios: Deutsche Bahn (German Railway System) for the outdoor scenarios and Fraport (Frankfort Airport) for the indoor scenarios. Apart from the difference in their environments, they provide different conditions, which the solution needs to consider. While locations of the objects in Fraport were previously known, that of DB were not known at the beginning.

  9. 220GHz wideband 3D imaging radar for concealed object detection technology development and phenomenology studies

    NASA Astrophysics Data System (ADS)

    Robertson, Duncan A.; Macfarlane, David G.; Bryllert, Tomas

    2016-05-01

    We present a 220 GHz 3D imaging `Pathfinder' radar developed within the EU FP7 project CONSORTIS (Concealed Object Stand-Off Real-Time Imaging for Security) which has been built to address two objectives: (i) to de-risk the radar hardware development and (ii) to enable the collection of phenomenology data with ~1 cm3 volumetric resolution. The radar combines a DDS-based chirp generator and self-mixing multiplier technology to achieve a 30 GHz bandwidth chirp with such high linearity that the raw point response is close to ideal and only requires minor nonlinearity compensation. The single transceiver is focused with a 30 cm lens mounted on a gimbal to acquire 3D volumetric images of static test targets and materials.

  10. Detection of hidden objects using a real-time 3-D millimeter-wave imaging system

    NASA Astrophysics Data System (ADS)

    Rozban, Daniel; Aharon, Avihai; Levanon, Assaf; Abramovich, Amir; Yitzhaky, Yitzhak; Kopeika, N. S.

    2014-10-01

    Millimeter (mm)and sub-mm wavelengths or terahertz (THz) band have several properties that motivate their use in imaging for security applications such as recognition of hidden objects, dangerous materials, aerosols, imaging through walls as in hostage situations, and also in bad weather conditions. There is no known ionization hazard for biological tissue, and atmospheric degradation of THz radiation is relatively low for practical imaging distances. We recently developed a new technology for the detection of THz radiation. This technology is based on very inexpensive plasma neon indicator lamps, also known as Glow Discharge Detector (GDD), that can be used as very sensitive THz radiation detectors. Using them, we designed and constructed a Focal Plane Array (FPA) and obtained recognizable2-dimensional THz images of both dielectric and metallic objects. Using THz wave it is shown here that even concealed weapons made of dielectric material can be detected. An example is an image of a knife concealed inside a leather bag and also under heavy clothing. Three-dimensional imaging using radar methods can enhance those images since it can allow the isolation of the concealed objects from the body and environmental clutter such as nearby furniture or other people. The GDDs enable direct heterodyning between the electric field of the target signal and the reference signal eliminating the requirement for expensive mixers, sources, and Low Noise Amplifiers (LNAs).We expanded the ability of the FPA so that we are able to obtain recognizable 2-dimensional THz images in real time. We show here that the THz detection of objects in three dimensions, using FMCW principles is also applicable in real time. This imaging system is also shown here to be capable of imaging objects from distances allowing standoff detection of suspicious objects and humans from large distances.

  11. A supervised method for object-based 3D building change detection on aerial stereo images

    NASA Astrophysics Data System (ADS)

    Qin, R.; Gruen, A.

    2014-08-01

    There is a great demand for studying the changes of buildings over time. The current trend for building change detection combines the orthophoto and DSM (Digital Surface Models). The pixel-based change detection methods are very sensitive to the quality of the images and DSMs, while the object-based methods are more robust towards these problems. In this paper, we propose a supervised method for building change detection. After a segment-based SVM (Support Vector Machine) classification with features extracted from the orthophoto and DSM, we focus on the detection of the building changes of different periods by measuring their height and texture differences, as well as their shapes. A decision tree analysis is used to assess the probability of change for each building segment and the traffic lighting system is used to indicate the status "change", "non-change" and "uncertain change" for building segments. The proposed method is applied to scanned aerial photos of the city of Zurich in 2002 and 2007, and the results have demonstrated that our method is able to achieve high detection accuracy.

  12. 3D object retrieval using salient views

    PubMed Central

    Shapiro, Linda G.

    2013-01-01

    This paper presents a method for selecting salient 2D views to describe 3D objects for the purpose of retrieval. The views are obtained by first identifying salient points via a learning approach that uses shape characteristics of the 3D points (Atmosukarto and Shapiro in International workshop on structural, syntactic, and statistical pattern recognition, 2008; Atmosukarto and Shapiro in ACM multimedia information retrieval, 2008). The salient views are selected by choosing views with multiple salient points on the silhouette of the object. Silhouette-based similarity measures from Chen et al. (Comput Graph Forum 22(3):223–232, 2003) are then used to calculate the similarity between two 3D objects. Retrieval experiments were performed on three datasets: the Heads dataset, the SHREC2008 dataset, and the Princeton dataset. Experimental results show that the retrieval results using the salient views are comparable to the existing light field descriptor method (Chen et al. in Comput Graph Forum 22(3):223–232, 2003), and our method achieves a 15-fold speedup in the feature extraction computation time. PMID:23833704

  13. 3D laser imaging for concealed object identification

    NASA Astrophysics Data System (ADS)

    Berechet, Ion; Berginc, Gérard; Berechet, Stefan

    2014-09-01

    This paper deals with new optical non-conventional 3D laser imaging. Optical non-conventional imaging explores the advantages of laser imaging to form a three-dimensional image of the scene. 3D laser imaging can be used for threedimensional medical imaging, topography, surveillance, robotic vision because of ability to detect and recognize objects. In this paper, we present a 3D laser imaging for concealed object identification. The objective of this new 3D laser imaging is to provide the user a complete 3D reconstruction of the concealed object from available 2D data limited in number and with low representativeness. The 2D laser data used in this paper come from simulations that are based on the calculation of the laser interactions with the different interfaces of the scene of interest and from experimental results. We show the global 3D reconstruction procedures capable to separate objects from foliage and reconstruct a threedimensional image of the considered object. In this paper, we present examples of reconstruction and completion of three-dimensional images and we analyse the different parameters of the identification process such as resolution, the scenario of camouflage, noise impact and lacunarity degree.

  14. Automatic 3D video format detection

    NASA Astrophysics Data System (ADS)

    Zhang, Tao; Wang, Zhe; Zhai, Jiefu; Doyen, Didier

    2011-03-01

    Many 3D formats exist and will probably co-exist for a long time even if 3D standards are today under definition. The support for multiple 3D formats will be important for bringing 3D into home. In this paper, we propose a novel and effective method to detect whether a video is a 3D video or not, and to further identify the exact 3D format. First, we present how to detect those 3D formats that encode a pair of stereo images into a single image. The proposed method detects features and establishes correspondences between features in the left and right view images, and applies the statistics from the distribution of the positional differences between corresponding features to detect the existence of a 3D format and to identify the format. Second, we present how to detect the frame sequential 3D format. In the frame sequential 3D format, the feature points are oscillating from frame to frame. Similarly, the proposed method tracks feature points over consecutive frames, computes the positional differences between features, and makes a detection decision based on whether the features are oscillating. Experiments show the effectiveness of our method.

  15. Computational integral-imaging reconstruction-based 3-D volumetric target object recognition by using a 3-D reference object.

    PubMed

    Kim, Seung-Cheol; Park, Seok-Chan; Kim, Eun-Soo

    2009-12-01

    In this paper, we propose a novel computational integral-imaging reconstruction (CIIR)-based three-dimensional (3-D) image correlator system for the recognition of 3-D volumetric objects by employing a 3-D reference object. That is, a number of plane object images (POIs) computationally reconstructed from the 3-D reference object are used for the 3-D volumetric target recognition. In other words, simultaneous 3-D image correlations between two sets of target and reference POIs, which are depth-dependently reconstructed by using the CIIR method, are performed for effective recognition of 3-D volumetric objects in the proposed system. Successful experiments with this CIIR-based 3-D image correlator confirmed the feasibility of the proposed method.

  16. 3D PDF - a means of public access to geological 3D - objects, using the example of GTA3D

    NASA Astrophysics Data System (ADS)

    Slaby, Mark-Fabian; Reimann, Rüdiger

    2013-04-01

    In geology, 3D modeling has become very important. In the past, two-dimensional data such as isolines, drilling profiles, or cross-sections based on those, were used to illustrate the subsurface geology, whereas now, we can create complex digital 3D models. These models are produced with special software, such as GOCAD ®. The models can be viewed, only through the software used to create them, or through viewers available for free. The platform-independent PDF (Portable Document Format), enforced by Adobe, has found a wide distribution. This format has constantly evolved over time. Meanwhile, it is possible to display CAD data in an Adobe 3D PDF file with the free Adobe Reader (version 7). In a 3D PDF, a 3D model is freely rotatable and can be assembled from a plurality of objects, which can thus be viewed from all directions on their own. In addition, it is possible to create moveable cross-sections (profiles), and to assign transparency to the objects. Based on industry-standard CAD software, 3D PDFs can be generated from a large number of formats, or even be exported directly from this software. In geoinformatics, different approaches to creating 3D PDFs exist. The intent of the Authority for Mining, Energy and Geology to allow free access to the models of the Geotectonic Atlas (GTA3D), could not be realized with standard software solutions. A specially designed code converts the 3D objects to VRML (Virtual Reality Modeling Language). VRML is one of the few formats that allow using image files (maps) as textures, and to represent colors and shapes correctly. The files were merged in Acrobat X Pro, and a 3D PDF was generated subsequently. A topographic map, a display of geographic directions and horizontal and vertical scales help to facilitate the use.

  17. Acquiring 3-D Spatial Data Of A Real Object

    NASA Astrophysics Data System (ADS)

    Wu, C. K.; Wang, D. Q.; Bajcsy, R. K...

    1983-10-01

    A method of acquiring spatial data of a real object via a stereometric system is presented. Three-dimensional (3-D) data of an object are acquired by: (1) camera calibration; (2) stereo matching; (3) multiple stereo views covering the whole object; (4) geometrical computations to determine the 3-D coordinates for each sample point of the object. The analysis and the experimental results indicate the method implemented is capable of measuring the spatial data of a real object with satisfactory accuracy.

  18. Design of 3d Topological Data Structure for 3d Cadastre Objects

    NASA Astrophysics Data System (ADS)

    Zulkifli, N. A.; Rahman, A. Abdul; Hassan, M. I.

    2016-09-01

    This paper describes the design of 3D modelling and topological data structure for cadastre objects based on Land Administration Domain Model (LADM) specifications. Tetrahedral Network (TEN) is selected as a 3D topological data structure for this project. Data modelling is based on the LADM standard and it is used five classes (i.e. point, boundary face string, boundary face, tetrahedron and spatial unit). This research aims to enhance the current cadastral system by incorporating 3D topology model based on LADM standard.

  19. 3D model-based still image object categorization

    NASA Astrophysics Data System (ADS)

    Petre, Raluca-Diana; Zaharia, Titus

    2011-09-01

    This paper proposes a novel recognition scheme algorithm for semantic labeling of 2D object present in still images. The principle consists of matching unknown 2D objects with categorized 3D models in order to infer the semantics of the 3D object to the image. We tested our new recognition framework by using the MPEG-7 and Princeton 3D model databases in order to label unknown images randomly selected from the web. Results obtained show promising performances, with recognition rate up to 84%, which opens interesting perspectives in terms of semantic metadata extraction from still images/videos.

  20. Phase Sensitive Cueing for 3D Objects in Overhead Images

    SciTech Connect

    Paglieroni, D

    2005-02-04

    Locating specific 3D objects in overhead images is an important problem in many remote sensing applications. 3D objects may contain either one connected component or multiple disconnected components. Solutions must accommodate images acquired with diverse sensors at various times of the day, in various seasons of the year, or under various weather conditions. Moreover, the physical manifestation of a 3D object with fixed physical dimensions in an overhead image is highly dependent on object physical dimensions, object position/orientation, image spatial resolution, and imaging geometry (e.g., obliqueness). This paper describes a two-stage computer-assisted approach for locating 3D objects in overhead images. In the matching stage, the computer matches models of 3D objects to overhead images. The strongest degree of match over all object orientations is computed at each pixel. Unambiguous local maxima in the degree of match as a function of pixel location are then found. In the cueing stage, the computer sorts image thumbnails in descending order of figure-of-merit and presents them to human analysts for visual inspection and interpretation. The figure-of-merit associated with an image thumbnail is computed from the degrees of match to a 3D object model associated with unambiguous local maxima that lie within the thumbnail. This form of computer assistance is invaluable when most of the relevant thumbnails are highly ranked, and the amount of inspection time needed is much less for the highly ranked thumbnails than for images as a whole.

  1. An Evaluative Review of Simulated Dynamic Smart 3d Objects

    NASA Astrophysics Data System (ADS)

    Romeijn, H.; Sheth, F.; Pettit, C. J.

    2012-07-01

    Three-dimensional (3D) modelling of plants can be an asset for creating agricultural based visualisation products. The continuum of 3D plants models ranges from static to dynamic objects, also known as smart 3D objects. There is an increasing requirement for smarter simulated 3D objects that are attributed mathematically and/or from biological inputs. A systematic approach to plant simulation offers significant advantages to applications in agricultural research, particularly in simulating plant behaviour and the influences of external environmental factors. This approach of 3D plant object visualisation is primarily evident from the visualisation of plants using photographed billboarded images, to more advanced procedural models that come closer to simulating realistic virtual plants. However, few programs model physical reactions of plants to external factors and even fewer are able to grow plants based on mathematical and/or biological parameters. In this paper, we undertake an evaluation of plant-based object simulation programs currently available, with a focus upon the components and techniques involved in producing these objects. Through an analytical review process we consider the strengths and weaknesses of several program packages, the features and use of these programs and the possible opportunities in deploying these for creating smart 3D plant-based objects to support agricultural research and natural resource management. In creating smart 3D objects the model needs to be informed by both plant physiology and phenology. Expert knowledge will frame the parameters and procedures that will attribute the object and allow the simulation of dynamic virtual plants. Ultimately, biologically smart 3D virtual plants that react to changes within an environment could be an effective medium to visually represent landscapes and communicate land management scenarios and practices to planners and decision-makers.

  2. 3D object hiding using three-dimensional ptychography

    NASA Astrophysics Data System (ADS)

    Zhang, Jun; Wang, Zhibo; Li, Tuo; Pan, An; Wang, Yali; Shi, Yishi

    2016-09-01

    We present a novel technique for 3D object hiding by applying three-dimensional ptychography. Compared with 3D information hiding based on holography, the proposed ptychography-based hiding technique is easier to implement, because the reference beam and high-precision interferometric optical setup are not required. The acquisition of the 3D object and the ptychographic encoding process are performed optically. Owing to the introduction of probe keys, the security of the ptychography-based hiding system is significantly enhanced. A series of experiments and simulations demonstrate the feasibility and imperceptibility of the proposed method.

  3. 3D dimeron as a stable topological object

    NASA Astrophysics Data System (ADS)

    Yang, Shijie; Liu, Yongkai

    2015-03-01

    Searching for novel topological objects is always an intriguing task for scientists in various fields. We study a new three-dimensional (3D) topological structure called 3D dimeron in the trapped two-component Bose-Einstein condensates. The 3D dimeron differs to the conventional 3D skyrmion for the condensates hosting two interlocked vortex-rings. We demonstrate that the vortex-rings are connected by a singular string and the complexity constitutes a vortex-molecule. The stability is investigated through numerically evolving the Gross-Pitaevskii equations, giving a coherent Rabi coupling between the two components. Alternatively, we find that the stable 3D dimeron can be naturally generated from a vortex-free Gaussian wave packet via incorporating a synthetic non-Abelian gauge potential into the condensates. This work is supported by the NSF of China under Grant No. 11374036 and the National 973 program under Grant No. 2012CB821403.

  4. Large distance 3D imaging of hidden objects

    NASA Astrophysics Data System (ADS)

    Rozban, Daniel; Aharon Akram, Avihai; Kopeika, N. S.; Abramovich, A.; Levanon, Assaf

    2014-06-01

    Imaging systems in millimeter waves are required for applications in medicine, communications, homeland security, and space technology. This is because there is no known ionization hazard for biological tissue, and atmospheric attenuation in this range of the spectrum is low compared to that of infrared and optical rays. The lack of an inexpensive room temperature detector makes it difficult to give a suitable real time implement for the above applications. A 3D MMW imaging system based on chirp radar was studied previously using a scanning imaging system of a single detector. The system presented here proposes to employ a chirp radar method with Glow Discharge Detector (GDD) Focal Plane Array (FPA of plasma based detectors) using heterodyne detection. The intensity at each pixel in the GDD FPA yields the usual 2D image. The value of the I-F frequency yields the range information at each pixel. This will enable 3D MMW imaging. In this work we experimentally demonstrate the feasibility of implementing an imaging system based on radar principles and FPA of inexpensive detectors. This imaging system is shown to be capable of imaging objects from distances of at least 10 meters.

  5. Embedding objects during 3D printing to add new functionalities.

    PubMed

    Yuen, Po Ki

    2016-07-01

    A novel method for integrating and embedding objects to add new functionalities during 3D printing based on fused deposition modeling (FDM) (also known as fused filament fabrication or molten polymer deposition) is presented. Unlike typical 3D printing, FDM-based 3D printing could allow objects to be integrated and embedded during 3D printing and the FDM-based 3D printed devices do not typically require any post-processing and finishing. Thus, various fluidic devices with integrated glass cover slips or polystyrene films with and without an embedded porous membrane, and optical devices with embedded Corning(®) Fibrance™ Light-Diffusing Fiber were 3D printed to demonstrate the versatility of the FDM-based 3D printing and embedding method. Fluid perfusion flow experiments with a blue colored food dye solution were used to visually confirm fluid flow and/or fluid perfusion through the embedded porous membrane in the 3D printed fluidic devices. Similar to typical 3D printed devices, FDM-based 3D printed devices are translucent at best unless post-polishing is performed and optical transparency is highly desirable in any fluidic devices; integrated glass cover slips or polystyrene films would provide a perfect optical transparent window for observation and visualization. In addition, they also provide a compatible flat smooth surface for biological or biomolecular applications. The 3D printed fluidic devices with an embedded porous membrane are applicable to biological or chemical applications such as continuous perfusion cell culture or biocatalytic synthesis but without the need for any post-device assembly and finishing. The 3D printed devices with embedded Corning(®) Fibrance™ Light-Diffusing Fiber would have applications in display, illumination, or optical applications. Furthermore, the FDM-based 3D printing and embedding method could also be utilized to print casting molds with an integrated glass bottom for polydimethylsiloxane (PDMS) device replication

  6. Embedding objects during 3D printing to add new functionalities.

    PubMed

    Yuen, Po Ki

    2016-07-01

    A novel method for integrating and embedding objects to add new functionalities during 3D printing based on fused deposition modeling (FDM) (also known as fused filament fabrication or molten polymer deposition) is presented. Unlike typical 3D printing, FDM-based 3D printing could allow objects to be integrated and embedded during 3D printing and the FDM-based 3D printed devices do not typically require any post-processing and finishing. Thus, various fluidic devices with integrated glass cover slips or polystyrene films with and without an embedded porous membrane, and optical devices with embedded Corning(®) Fibrance™ Light-Diffusing Fiber were 3D printed to demonstrate the versatility of the FDM-based 3D printing and embedding method. Fluid perfusion flow experiments with a blue colored food dye solution were used to visually confirm fluid flow and/or fluid perfusion through the embedded porous membrane in the 3D printed fluidic devices. Similar to typical 3D printed devices, FDM-based 3D printed devices are translucent at best unless post-polishing is performed and optical transparency is highly desirable in any fluidic devices; integrated glass cover slips or polystyrene films would provide a perfect optical transparent window for observation and visualization. In addition, they also provide a compatible flat smooth surface for biological or biomolecular applications. The 3D printed fluidic devices with an embedded porous membrane are applicable to biological or chemical applications such as continuous perfusion cell culture or biocatalytic synthesis but without the need for any post-device assembly and finishing. The 3D printed devices with embedded Corning(®) Fibrance™ Light-Diffusing Fiber would have applications in display, illumination, or optical applications. Furthermore, the FDM-based 3D printing and embedding method could also be utilized to print casting molds with an integrated glass bottom for polydimethylsiloxane (PDMS) device replication

  7. Sketch-driven mental 3D object retrieval

    NASA Astrophysics Data System (ADS)

    Napoléon, Thibault; Sahbi, Hichem

    2010-02-01

    3D object recognition and retrieval recently gained a big interest because of the limitation of the "2D-to-2D" approaches. The latter suffer from several drawbacks such as the lack of information (due for instance to occlusion), pose sensitivity, illumination changes, etc. Our main motivation is to gather both discrimination and easy interaction by allowing simple (but multiple) 2D specifications of queries and their retrieval into 3D gallery sets. We introduce a novel "2D sketch-to-3D model" retrieval framework with the following contributions: (i) first a novel generative approach for aligning and normalizing the pose of 3D gallery objects and extracting their 2D canonical views is introduced. (ii) Afterwards, robust and compact contour signatures are extracted using the set of 2D canonical views. We also introduce a pruning approach to speedup the whole search process in a coarseto- fine way. (iii) Finally, object ranking is performed using our variant of elastic dynamic programming which considers only a subset of possible matches thereby providing a considerable gain in performance for the same amount of errors. Our experiments are reported/compared through the Princeton Shape Benchmark; clearly showing the good performance of our framework w.r.t. the other approaches. An iPhone demo of this method is available and allows us to achieve "2D sketch to 3D object" querying and interaction.

  8. Recognition of 3-D Scene with Partially Occluded Objects

    NASA Astrophysics Data System (ADS)

    Lu, Siwei; Wong, Andrew K. C...

    1987-03-01

    This paper presents a robot vision system which is capable of recognizing objects in a 3-D scene and interpreting their spatial relation even though some objects in the scene may be partially occluded by other objects. An algorithm is developed to transform the geometric information from the range data into an attributed hypergraph representation (AHR). A hypergraph monomorphism algorithm is then used to compare the AHR of objects in the scene with a set of complete AHR's of prototypes. The capability of identifying connected components and interpreting various types of edges in the 3-D scene enables us to distinguish objects which are partially blocking each other in the scene. Using structural information stored in the primitive area graph, a heuristic hypergraph monomorphism algorithm provides an effective way for recognizing, locating, and interpreting partially occluded objects in the range image.

  9. A 3-D measurement system using object-oriented FORTH

    SciTech Connect

    Butterfield, K.B.

    1989-01-01

    Discussed is a system for storing 3-D measurements of points that relates the coordinate system of the measurement device to the global coordinate system. The program described here used object-oriented FORTH to store the measured points as sons of the measuring device location. Conversion of local coordinates to absolute coordinates is performed by passing messages to the point objects. Modifications to the object-oriented FORTH system are also described. 1 ref.

  10. Algorithms for Haptic Rendering of 3D Objects

    NASA Technical Reports Server (NTRS)

    Basdogan, Cagatay; Ho, Chih-Hao; Srinavasan, Mandayam

    2003-01-01

    Algorithms have been developed to provide haptic rendering of three-dimensional (3D) objects in virtual (that is, computationally simulated) environments. The goal of haptic rendering is to generate tactual displays of the shapes, hardnesses, surface textures, and frictional properties of 3D objects in real time. Haptic rendering is a major element of the emerging field of computer haptics, which invites comparison with computer graphics. We have already seen various applications of computer haptics in the areas of medicine (surgical simulation, telemedicine, haptic user interfaces for blind people, and rehabilitation of patients with neurological disorders), entertainment (3D painting, character animation, morphing, and sculpting), mechanical design (path planning and assembly sequencing), and scientific visualization (geophysical data analysis and molecular manipulation).

  11. Objective breast symmetry evaluation using 3-D surface imaging.

    PubMed

    Eder, Maximilian; Waldenfels, Fee V; Swobodnik, Alexandra; Klöppel, Markus; Pape, Ann-Kathrin; Schuster, Tibor; Raith, Stefan; Kitzler, Elena; Papadopulos, Nikolaos A; Machens, Hans-Günther; Kovacs, Laszlo

    2012-04-01

    This study develops an objective breast symmetry evaluation using 3-D surface imaging (Konica-Minolta V910(®) scanner) by superimposing the mirrored left breast over the right and objectively determining the mean 3-D contour difference between the 2 breast surfaces. 3 observers analyzed the evaluation protocol precision using 2 dummy models (n = 60), 10 test subjects (n = 300), clinically tested it on 30 patients (n = 900) and compared it to established 2-D measurements on 23 breast reconstructive patients using the BCCT.core software (n = 690). Mean 3-D evaluation precision, expressed as the coefficient of variation (VC), was 3.54 ± 0.18 for all human subjects without significant intra- and inter-observer differences (p > 0.05). The 3-D breast symmetry evaluation is observer independent, significantly more precise (p < 0.001) than the BCCT.core software (VC = 6.92 ± 0.88) and may play a part in an objective surgical outcome analysis after incorporation into clinical practice.

  12. 3-D Object Recognition from Point Cloud Data

    NASA Astrophysics Data System (ADS)

    Smith, W.; Walker, A. S.; Zhang, B.

    2011-09-01

    The market for real-time 3-D mapping includes not only traditional geospatial applications but also navigation of unmanned autonomous vehicles (UAVs). Massively parallel processes such as graphics processing unit (GPU) computing make real-time 3-D object recognition and mapping achievable. Geospatial technologies such as digital photogrammetry and GIS offer advanced capabilities to produce 2-D and 3-D static maps using UAV data. The goal is to develop real-time UAV navigation through increased automation. It is challenging for a computer to identify a 3-D object such as a car, a tree or a house, yet automatic 3-D object recognition is essential to increasing the productivity of geospatial data such as 3-D city site models. In the past three decades, researchers have used radiometric properties to identify objects in digital imagery with limited success, because these properties vary considerably from image to image. Consequently, our team has developed software that recognizes certain types of 3-D objects within 3-D point clouds. Although our software is developed for modeling, simulation and visualization, it has the potential to be valuable in robotics and UAV applications. The locations and shapes of 3-D objects such as buildings and trees are easily recognizable by a human from a brief glance at a representation of a point cloud such as terrain-shaded relief. The algorithms to extract these objects have been developed and require only the point cloud and minimal human inputs such as a set of limits on building size and a request to turn on a squaring option. The algorithms use both digital surface model (DSM) and digital elevation model (DEM), so software has also been developed to derive the latter from the former. The process continues through the following steps: identify and group 3-D object points into regions; separate buildings and houses from trees; trace region boundaries; regularize and simplify boundary polygons; construct complex roofs. Several case

  13. Automatic detection of artifacts in converted S3D video

    NASA Astrophysics Data System (ADS)

    Bokov, Alexander; Vatolin, Dmitriy; Zachesov, Anton; Belous, Alexander; Erofeev, Mikhail

    2014-03-01

    In this paper we present algorithms for automatically detecting issues specific to converted S3D content. When a depth-image-based rendering approach produces a stereoscopic image, the quality of the result depends on both the depth maps and the warping algorithms. The most common problem with converted S3D video is edge-sharpness mismatch. This artifact may appear owing to depth-map blurriness at semitransparent edges: after warping, the object boundary becomes sharper in one view and blurrier in the other, yielding binocular rivalry. To detect this problem we estimate the disparity map, extract boundaries with noticeable differences, and analyze edge-sharpness correspondence between views. We pay additional attention to cases involving a complex background and large occlusions. Another problem is detection of scenes that lack depth volume: we present algorithms for detecting at scenes and scenes with at foreground objects. To identify these problems we analyze the features of the RGB image as well as uniform areas in the depth map. Testing of our algorithms involved examining 10 Blu-ray 3D releases with converted S3D content, including Clash of the Titans, The Avengers, and The Chronicles of Narnia: The Voyage of the Dawn Treader. The algorithms we present enable improved automatic quality assessment during the production stage.

  14. 3-D object recognition using 2-D views.

    PubMed

    Li, Wenjing; Bebis, George; Bourbakis, Nikolaos G

    2008-11-01

    We consider the problem of recognizing 3-D objects from 2-D images using geometric models and assuming different viewing angles and positions. Our goal is to recognize and localize instances of specific objects (i.e., model-based) in a scene. This is in contrast to category-based object recognition methods where the goal is to search for instances of objects that belong to a certain visual category (e.g., faces or cars). The key contribution of our work is improving 3-D object recognition by integrating Algebraic Functions of Views (AFoVs), a powerful framework for predicting the geometric appearance of an object due to viewpoint changes, with indexing and learning. During training, we compute the space of views that groups of object features can produce under the assumption of 3-D linear transformations, by combining a small number of reference views that contain the object features using AFoVs. Unrealistic views (e.g., due to the assumption of 3-D linear transformations) are eliminated by imposing a pair of rigidity constraints based on knowledge of the transformation between the reference views of the object. To represent the space of views that an object can produce compactly while allowing efficient hypothesis generation during recognition, we propose combining indexing with learning in two stages. In the first stage, we sample the space of views of an object sparsely and represent information about the samples using indexing. In the second stage, we build probabilistic models of shape appearance by sampling the space of views of the object densely and learning the manifold formed by the samples. Learning employs the Expectation-Maximization (EM) algorithm and takes place in a "universal," lower-dimensional, space computed through Random Projection (RP). During recognition, we extract groups of point features from the scene and we use indexing to retrieve the most feasible model groups that might have produced them (i.e., hypothesis generation). The likelihood

  15. Exploring local regularities for 3D object recognition

    NASA Astrophysics Data System (ADS)

    Tian, Huaiwen; Qin, Shengfeng

    2016-09-01

    In order to find better simplicity measurements for 3D object recognition, a new set of local regularities is developed and tested in a stepwise 3D reconstruction method, including localized minimizing standard deviation of angles(L-MSDA), localized minimizing standard deviation of segment magnitudes(L-MSDSM), localized minimum standard deviation of areas of child faces (L-MSDAF), localized minimum sum of segment magnitudes of common edges (L-MSSM), and localized minimum sum of areas of child face (L-MSAF). Based on their effectiveness measurements in terms of form and size distortions, it is found that when two local regularities: L-MSDA and L-MSDSM are combined together, they can produce better performance. In addition, the best weightings for them to work together are identified as 10% for L-MSDSM and 90% for L-MSDA. The test results show that the combined usage of L-MSDA and L-MSDSM with identified weightings has a potential to be applied in other optimization based 3D recognition methods to improve their efficacy and robustness.

  16. Divided attention limits perception of 3-D object shapes.

    PubMed

    Scharff, Alec; Palmer, John; Moore, Cathleen M

    2013-01-01

    Can one perceive multiple object shapes at once? We tested two benchmark models of object shape perception under divided attention: an unlimited-capacity and a fixed-capacity model. Under unlimited-capacity models, shapes are analyzed independently and in parallel. Under fixed-capacity models, shapes are processed at a fixed rate (as in a serial model). To distinguish these models, we compared conditions in which observers were presented with simultaneous or sequential presentations of a fixed number of objects (The extended simultaneous-sequential method: Scharff, Palmer, & Moore, 2011a, 2011b). We used novel physical objects as stimuli, minimizing the role of semantic categorization in the task. Observers searched for a specific object among similar objects. We ensured that non-shape stimulus properties such as color and texture could not be used to complete the task. Unpredictable viewing angles were used to preclude image-matching strategies. The results rejected unlimited-capacity models for object shape perception and were consistent with the predictions of a fixed-capacity model. In contrast, a task that required observers to recognize 2-D shapes with predictable viewing angles yielded an unlimited capacity result. Further experiments ruled out alternative explanations for the capacity limit, leading us to conclude that there is a fixed-capacity limit on the ability to perceive 3-D object shapes.

  17. Phase Sensitive Cueing for 3D Objects in Overhead Images

    SciTech Connect

    Paglieroni, D W; Eppler, W G; Poland, D N

    2005-02-18

    A 3D solid model-aided object cueing method that matches phase angles of directional derivative vectors at image pixels to phase angles of vectors normal to projected model edges is described. It is intended for finding specific types of objects at arbitrary position and orientation in overhead images, independent of spatial resolution, obliqueness, acquisition conditions, and type of imaging sensor. It is shown that the phase similarity measure can be efficiently evaluated over all combinations of model position and orientation using the FFT. The highest degree of similarity over all model orientations is captured in a match surface of similarity values vs. model position. Unambiguous peaks in this surface are sorted in descending order of similarity value, and the small image thumbnails that contain them are presented to human analysts for inspection in sorted order.

  18. An object oriented fully 3D tomography visual toolkit.

    PubMed

    Agostinelli, S; Paoli, G

    2001-04-01

    In this paper we present a modern object oriented component object model (COMM) C + + toolkit dedicated to fully 3D cone-beam tomography. The toolkit allows the display and visual manipulation of analytical phantoms, projection sets and volumetric data through a standard Windows graphical user interface. Data input/output is performed using proprietary file formats but import/export of industry standard file formats, including raw binary, Windows bitmap and AVI, ACR/NEMA DICOMM 3 and NCSA HDF is available. At the time of writing built-in implemented data manipulators include a basic phantom ray-tracer and a Matrox Genesis frame grabbing facility. A COMM plug-in interface is provided for user-defined custom backprojector algorithms: a simple Feldkamp ActiveX control, including source code, is provided as an example; our fast Feldkamp plug-in is also available.

  19. Objective 3D face recognition: Evolution, approaches and challenges.

    PubMed

    Smeets, Dirk; Claes, Peter; Vandermeulen, Dirk; Clement, John Gerald

    2010-09-10

    Face recognition is a natural human ability and a widely accepted identification and authentication method. In modern legal settings, a lot of credence is placed on identifications made by eyewitnesses. Consequently these are based on human perception which is often flawed and can lead to situations where identity is disputed. Therefore, there is a clear need to secure identifications in an objective way based on anthropometric measures. Anthropometry has existed for many years and has evolved with each advent of new technology and computing power. As a result of this, face recognition methodology has shifted from a purely 2D image-based approach to the use of 3D facial shape. However, one of the main challenges still remaining is the non-rigid structure of the face, which can change permanently over varying time-scales and briefly with facial expressions. The majority of face recognition methods have been developed by scientists with a very technical background such as biometry, pattern recognition and computer vision. This article strives to bridge the gap between these communities and the forensic science end-users. A concise review of face recognition using 3D shape is given. Methods using 3D shape applied to data embodying facial expressions are tabulated for reference. From this list a categorization of different strategies to deal with expressions is presented. The underlying concepts and practical issues relating to the application of each strategy are given, without going into technical details. The discussion clearly articulates the justification to establish archival, reference databases to compare and evaluate different strategies. PMID:20395086

  20. Objective 3D face recognition: Evolution, approaches and challenges.

    PubMed

    Smeets, Dirk; Claes, Peter; Vandermeulen, Dirk; Clement, John Gerald

    2010-09-10

    Face recognition is a natural human ability and a widely accepted identification and authentication method. In modern legal settings, a lot of credence is placed on identifications made by eyewitnesses. Consequently these are based on human perception which is often flawed and can lead to situations where identity is disputed. Therefore, there is a clear need to secure identifications in an objective way based on anthropometric measures. Anthropometry has existed for many years and has evolved with each advent of new technology and computing power. As a result of this, face recognition methodology has shifted from a purely 2D image-based approach to the use of 3D facial shape. However, one of the main challenges still remaining is the non-rigid structure of the face, which can change permanently over varying time-scales and briefly with facial expressions. The majority of face recognition methods have been developed by scientists with a very technical background such as biometry, pattern recognition and computer vision. This article strives to bridge the gap between these communities and the forensic science end-users. A concise review of face recognition using 3D shape is given. Methods using 3D shape applied to data embodying facial expressions are tabulated for reference. From this list a categorization of different strategies to deal with expressions is presented. The underlying concepts and practical issues relating to the application of each strategy are given, without going into technical details. The discussion clearly articulates the justification to establish archival, reference databases to compare and evaluate different strategies.

  1. Additive manufacturing. Continuous liquid interface production of 3D objects.

    PubMed

    Tumbleston, John R; Shirvanyants, David; Ermoshkin, Nikita; Janusziewicz, Rima; Johnson, Ashley R; Kelly, David; Chen, Kai; Pinschmidt, Robert; Rolland, Jason P; Ermoshkin, Alexander; Samulski, Edward T; DeSimone, Joseph M

    2015-03-20

    Additive manufacturing processes such as 3D printing use time-consuming, stepwise layer-by-layer approaches to object fabrication. We demonstrate the continuous generation of monolithic polymeric parts up to tens of centimeters in size with feature resolution below 100 micrometers. Continuous liquid interface production is achieved with an oxygen-permeable window below the ultraviolet image projection plane, which creates a "dead zone" (persistent liquid interface) where photopolymerization is inhibited between the window and the polymerizing part. We delineate critical control parameters and show that complex solid parts can be drawn out of the resin at rates of hundreds of millimeters per hour. These print speeds allow parts to be produced in minutes instead of hours.

  2. 3-D Interpolation in Object Perception: Evidence from an Objective Performance Paradigm

    ERIC Educational Resources Information Center

    Kellman, Philip J.; Garrigan, Patrick; Shipley, Thomas F.; Yin, Carol; Machado, Liana

    2005-01-01

    Object perception requires interpolation processes that connect visible regions despite spatial gaps. Some research has suggested that interpolation may be a 3-D process, but objective performance data and evidence about the conditions leading to interpolation are needed. The authors developed an objective performance paradigm for testing 3-D…

  3. Object Segmentation and Ground Truth in 3D Embryonic Imaging.

    PubMed

    Rajasekaran, Bhavna; Uriu, Koichiro; Valentin, Guillaume; Tinevez, Jean-Yves; Oates, Andrew C

    2016-01-01

    Many questions in developmental biology depend on measuring the position and movement of individual cells within developing embryos. Yet, tools that provide this data are often challenged by high cell density and their accuracy is difficult to measure. Here, we present a three-step procedure to address this problem. Step one is a novel segmentation algorithm based on image derivatives that, in combination with selective post-processing, reliably and automatically segments cell nuclei from images of densely packed tissue. Step two is a quantitative validation using synthetic images to ascertain the efficiency of the algorithm with respect to signal-to-noise ratio and object density. Finally, we propose an original method to generate reliable and experimentally faithful ground truth datasets: Sparse-dense dual-labeled embryo chimeras are used to unambiguously measure segmentation errors within experimental data. Together, the three steps outlined here establish a robust, iterative procedure to fine-tune image analysis algorithms and microscopy settings associated with embryonic 3D image data sets. PMID:27332860

  4. Object Segmentation and Ground Truth in 3D Embryonic Imaging

    PubMed Central

    Rajasekaran, Bhavna; Uriu, Koichiro; Valentin, Guillaume; Tinevez, Jean-Yves; Oates, Andrew C.

    2016-01-01

    Many questions in developmental biology depend on measuring the position and movement of individual cells within developing embryos. Yet, tools that provide this data are often challenged by high cell density and their accuracy is difficult to measure. Here, we present a three-step procedure to address this problem. Step one is a novel segmentation algorithm based on image derivatives that, in combination with selective post-processing, reliably and automatically segments cell nuclei from images of densely packed tissue. Step two is a quantitative validation using synthetic images to ascertain the efficiency of the algorithm with respect to signal-to-noise ratio and object density. Finally, we propose an original method to generate reliable and experimentally faithful ground truth datasets: Sparse-dense dual-labeled embryo chimeras are used to unambiguously measure segmentation errors within experimental data. Together, the three steps outlined here establish a robust, iterative procedure to fine-tune image analysis algorithms and microscopy settings associated with embryonic 3D image data sets. PMID:27332860

  5. Telecentric scanner for 3D profilometry of very large objects

    NASA Astrophysics Data System (ADS)

    Thibault, Simon; Borra, Ermanno F.; Szapiel, Stan

    1997-09-01

    Triangulation systems that are based on an autosynchronized scanning principle to provide accurate and fast acquisition of 3D shapes are able to scan large fields. It is done generally by a coordinate measuring machine (CMM) carrying a small-volume 3D camera. However the acquisition speed is limited by the CMM movement and also by the image fusion time required to get the complete 3D shape. This paper describes some practical consideration for large volume 3D inspections with emphasis on telecentric scanning. We present the analytical and the optical design of a large telecentric scanner using a large reflective surface. Some results of the laboratory prototype will be presented. We also discuss applications and the viability of this new approach.

  6. Segmentation and detection of fluorescent 3D spots.

    PubMed

    Ram, Sundaresh; Rodríguez, Jeffrey J; Bosco, Giovanni

    2012-03-01

    The 3D spatial organization of genes and other genetic elements within the nucleus is important for regulating gene expression. Understanding how this spatial organization is established and maintained throughout the life of a cell is key to elucidating the many layers of gene regulation. Quantitative methods for studying nuclear organization will lead to insights into the molecular mechanisms that maintain gene organization as well as serve as diagnostic tools for pathologies caused by loss of nuclear structure. However, biologists currently lack automated and high throughput methods for quantitative and qualitative global analysis of 3D gene organization. In this study, we use confocal microscopy and fluorescence in-situ hybridization (FISH) as a cytogenetic technique to detect and localize the presence of specific DNA sequences in 3D. FISH uses probes that bind to specific targeted locations on the chromosomes, appearing as fluorescent spots in 3D images obtained using fluorescence microscopy. In this article, we propose an automated algorithm for segmentation and detection of 3D FISH spots. The algorithm is divided into two stages: spot segmentation and spot detection. Spot segmentation consists of 3D anisotropic smoothing to reduce the effect of noise, top-hat filtering, and intensity thresholding, followed by 3D region-growing. Spot detection uses a Bayesian classifier with spot features such as volume, average intensity, texture, and contrast to detect and classify the segmented spots as either true or false spots. Quantitative assessment of the proposed algorithm demonstrates improved segmentation and detection accuracy compared to other techniques.

  7. Reconstruction and 3D visualisation based on objective real 3D based documentation.

    PubMed

    Bolliger, Michael J; Buck, Ursula; Thali, Michael J; Bolliger, Stephan A

    2012-09-01

    Reconstructions based directly upon forensic evidence alone are called primary information. Historically this consists of documentation of findings by verbal protocols, photographs and other visual means. Currently modern imaging techniques such as 3D surface scanning and radiological methods (computer tomography, magnetic resonance imaging) are also applied. Secondary interpretation is based on facts and the examiner's experience. Usually such reconstructive expertises are given in written form, and are often enhanced by sketches. However, narrative interpretations can, especially in complex courses of action, be difficult to present and can be misunderstood. In this report we demonstrate the use of graphic reconstruction of secondary interpretation with supporting pictorial evidence, applying digital visualisation (using 'Poser') or scientific animation (using '3D Studio Max', 'Maya') and present methods of clearly distinguishing between factual documentation and examiners' interpretation based on three cases. The first case involved a pedestrian who was initially struck by a car on a motorway and was then run over by a second car. The second case involved a suicidal gunshot to the head with a rifle, in which the trigger was pushed with a rod. The third case dealt with a collision between two motorcycles. Pictorial reconstruction of the secondary interpretation of these cases has several advantages. The images enable an immediate overview, give rise to enhanced clarity, and compel the examiner to look at all details if he or she is to create a complete image. PMID:21979427

  8. Acquiring 3-D information about thick objects from differential interference contrast images using texture extraction

    NASA Astrophysics Data System (ADS)

    Sierra, Heidy; Brooks, Dana; Dimarzio, Charles

    2010-07-01

    The extraction of 3-D morphological information about thick objects is explored in this work. We extract this information from 3-D differential interference contrast (DIC) images by applying a texture detection method. Texture extraction methods have been successfully used in different applications to study biological samples. A 3-D texture image is obtained by applying a local entropy-based texture extraction method. The use of this method to detect regions of blastocyst mouse embryos that are used in assisted reproduction techniques such as in vitro fertilization is presented as an example. Results demonstrate the potential of using texture detection methods to improve morphological analysis of thick samples, which is relevant to many biomedical and biological studies. Fluorescence and optical quadrature microscope phase images are used for validation.

  9. Objective and subjective quality assessment of geometry compression of reconstructed 3D humans in a 3D virtual room

    NASA Astrophysics Data System (ADS)

    Mekuria, Rufael; Cesar, Pablo; Doumanis, Ioannis; Frisiello, Antonella

    2015-09-01

    Compression of 3D object based video is relevant for 3D Immersive applications. Nevertheless, the perceptual aspects of the degradation introduced by codecs for meshes and point clouds are not well understood. In this paper we evaluate the subjective and objective degradations introduced by such codecs in a state of art 3D immersive virtual room. In the 3D immersive virtual room, users are captured with multiple cameras, and their surfaces are reconstructed as photorealistic colored/textured 3D meshes or point clouds. To test the perceptual effect of compression and transmission, we render degraded versions with different frame rates in different contexts (near/far) in the scene. A quantitative subjective study with 16 users shows that negligible distortion of decoded surfaces compared to the original reconstructions can be achieved in the 3D virtual room. In addition, a qualitative task based analysis in a full prototype field trial shows increased presence, emotion, user and state recognition of the reconstructed 3D Human representation compared to animated computer avatars.

  10. Polygonal Shapes Detection in 3d Models of Complex Architectures

    NASA Astrophysics Data System (ADS)

    Benciolini, G. B.; Vitti, A.

    2015-02-01

    A sequential application of two global models defined on a variational framework is proposed for the detection of polygonal shapes in 3D models of complex architectures. As a first step, the procedure involves the use of the Mumford and Shah (1989) 1st-order variational model in dimension two (gridded height data are processed). In the Mumford-Shah model an auxiliary function detects the sharp changes, i.e., the discontinuities, of a piecewise smooth approximation of the data. The Mumford-Shah model requires the global minimization of a specific functional to simultaneously produce both the smooth approximation and its discontinuities. In the proposed procedure, the edges of the smooth approximation derived by a specific processing of the auxiliary function are then processed using the Blake and Zisserman (1987) 2nd-order variational model in dimension one (edges are processed in the plane). This second step permits to describe the edges of an object by means of piecewise almost-linear approximation of the input edges themselves and to detects sharp changes of the first-derivative of the edges so to detect corners. The Mumford-Shah variational model is used in two dimensions accepting the original data as primary input. The Blake-Zisserman variational model is used in one dimension for the refinement of the description of the edges. The selection among all the boundaries detected by the Mumford-Shah model of those that present a shape close to a polygon is performed by considering only those boundaries for which the Blake-Zisserman model identified discontinuities in their first derivative. The output of the procedure are hence shapes, coming from 3D geometric data, that can be considered as polygons. The application of the procedure is suitable for, but not limited to, the detection of objects such as foot-print of polygonal buildings, building facade boundaries or windows contours. v The procedure is applied to a height model of the building of the Engineering

  11. 3D shape shearography with integrated structured light projection for strain inspection of curved objects

    NASA Astrophysics Data System (ADS)

    Anisimov, Andrei G.; Groves, Roger M.

    2015-05-01

    Shearography (speckle pattern shearing interferometry) is a non-destructive testing technique that provides full-field surface strain characterization. Although real-life objects especially in aerospace, transport or cultural heritage are not flat (e.g. aircraft leading edges or sculptures), their inspection with shearography is of interest for both hidden defect detection and material characterization. Accurate strain measuring of a highly curved or free form surface needs to be performed by combining inline object shape measuring and processing of shearography data in 3D. Previous research has not provided a general solution. This research is devoted to the practical questions of 3D shape shearography system development for surface strain characterization of curved objects. The complete procedure of calibration and data processing of a 3D shape shearography system with integrated structured light projector is presented. This includes an estimation of the actual shear distance and a sensitivity matrix correction within the system field of view. For the experimental part a 3D shape shearography system prototype was developed. It employs three spatially-distributed shearing cameras, with Michelson interferometers acting as the shearing devices, one illumination laser source and a structured light projector. The developed system performance was evaluated with a previously reported cylinder specimen (length 400 mm, external diameter 190 mmm) loaded by internal pressure. Further steps for the 3D shape shearography prototype and the technique development are also proposed.

  12. Extension of RCC Topological Relations for 3d Complex Objects Components Extracted from 3d LIDAR Point Clouds

    NASA Astrophysics Data System (ADS)

    Xing, Xu-Feng; Abolfazl Mostafavia, Mir; Wang, Chen

    2016-06-01

    Topological relations are fundamental for qualitative description, querying and analysis of a 3D scene. Although topological relations for 2D objects have been extensively studied and implemented in GIS applications, their direct extension to 3D is very challenging and they cannot be directly applied to represent relations between components of complex 3D objects represented by 3D B-Rep models in R3. Herein we present an extended Region Connection Calculus (RCC) model to express and formalize topological relations between planar regions for creating 3D model represented by Boundary Representation model in R3. We proposed a new dimension extended 9-Intersection model to represent the basic relations among components of a complex object, including disjoint, meet and intersect. The last element in 3*3 matrix records the details of connection through the common parts of two regions and the intersecting line of two planes. Additionally, this model can deal with the case of planar regions with holes. Finally, the geometric information is transformed into a list of strings consisting of topological relations between two planar regions and detailed connection information. The experiments show that the proposed approach helps to identify topological relations of planar segments of point cloud automatically.

  13. Object-oriented urban 3D spatial data model organization method

    NASA Astrophysics Data System (ADS)

    Li, Jing-wen; Li, Wen-qing; Lv, Nan; Su, Tao

    2015-12-01

    This paper combined the 3d data model with object-oriented organization method, put forward the model of 3d data based on object-oriented method, implemented the city 3d model to quickly build logical semantic expression and model, solved the city 3d spatial information representation problem of the same location with multiple property and the same property with multiple locations, designed the space object structure of point, line, polygon, body for city of 3d spatial database, and provided a new thought and method for the city 3d GIS model and organization management.

  14. A Taxonomy of 3D Occluded Objects Recognition Techniques

    NASA Astrophysics Data System (ADS)

    Soleimanizadeh, Shiva; Mohamad, Dzulkifli; Saba, Tanzila; Al-ghamdi, Jarallah Saleh

    2016-03-01

    The overall performances of object recognition techniques under different condition (e.g., occlusion, viewpoint, and illumination) have been improved significantly in recent years. New applications and hardware are shifted towards digital photography, and digital media. This faces an increase in Internet usage requiring object recognition for certain applications; particularly occulded objects. However occlusion is still an issue unhandled, interlacing the relations between extracted feature points through image, research is going on to develop efficient techniques and easy to use algorithms that would help users to source images; this need to overcome problems and issues regarding occlusion. The aim of this research is to review recognition occluded objects algorithms and figure out their pros and cons to solve the occlusion problem features, which are extracted from occluded object to distinguish objects from other co-existing objects by determining the new techniques, which could differentiate the occluded fragment and sections inside an image.

  15. Visual Object Recognition with 3D-Aware Features in KITTI Urban Scenes

    PubMed Central

    Yebes, J. Javier; Bergasa, Luis M.; García-Garrido, Miguel Ángel

    2015-01-01

    Driver assistance systems and autonomous robotics rely on the deployment of several sensors for environment perception. Compared to LiDAR systems, the inexpensive vision sensors can capture the 3D scene as perceived by a driver in terms of appearance and depth cues. Indeed, providing 3D image understanding capabilities to vehicles is an essential target in order to infer scene semantics in urban environments. One of the challenges that arises from the navigation task in naturalistic urban scenarios is the detection of road participants (e.g., cyclists, pedestrians and vehicles). In this regard, this paper tackles the detection and orientation estimation of cars, pedestrians and cyclists, employing the challenging and naturalistic KITTI images. This work proposes 3D-aware features computed from stereo color images in order to capture the appearance and depth peculiarities of the objects in road scenes. The successful part-based object detector, known as DPM, is extended to learn richer models from the 2.5D data (color and disparity), while also carrying out a detailed analysis of the training pipeline. A large set of experiments evaluate the proposals, and the best performing approach is ranked on the KITTI website. Indeed, this is the first work that reports results with stereo data for the KITTI object challenge, achieving increased detection ratios for the classes car and cyclist compared to a baseline DPM. PMID:25903553

  16. Visual Object Recognition with 3D-Aware Features in KITTI Urban Scenes.

    PubMed

    Yebes, J Javier; Bergasa, Luis M; García-Garrido, Miguel Ángel

    2015-01-01

    Driver assistance systems and autonomous robotics rely on the deployment of several sensors for environment perception. Compared to LiDAR systems, the inexpensive vision sensors can capture the 3D scene as perceived by a driver in terms of appearance and depth cues. Indeed, providing 3D image understanding capabilities to vehicles is an essential target in order to infer scene semantics in urban environments. One of the challenges that arises from the navigation task in naturalistic urban scenarios is the detection of road participants (e.g., cyclists, pedestrians and vehicles). In this regard, this paper tackles the detection and orientation estimation of cars, pedestrians and cyclists, employing the challenging and naturalistic KITTI images. This work proposes 3D-aware features computed from stereo color images in order to capture the appearance and depth peculiarities of the objects in road scenes. The successful part-based object detector, known as DPM, is extended to learn richer models from the 2.5D data (color and disparity), while also carrying out a detailed analysis of the training pipeline. A large set of experiments evaluate the proposals, and the best performing approach is ranked on the KITTI website. Indeed, this is the first work that reports results with stereo data for the KITTI object challenge, achieving increased detection ratios for the classes car and cyclist compared to a baseline DPM. PMID:25903553

  17. Visual Object Recognition with 3D-Aware Features in KITTI Urban Scenes.

    PubMed

    Yebes, J Javier; Bergasa, Luis M; García-Garrido, Miguel Ángel

    2015-04-20

    Driver assistance systems and autonomous robotics rely on the deployment of several sensors for environment perception. Compared to LiDAR systems, the inexpensive vision sensors can capture the 3D scene as perceived by a driver in terms of appearance and depth cues. Indeed, providing 3D image understanding capabilities to vehicles is an essential target in order to infer scene semantics in urban environments. One of the challenges that arises from the navigation task in naturalistic urban scenarios is the detection of road participants (e.g., cyclists, pedestrians and vehicles). In this regard, this paper tackles the detection and orientation estimation of cars, pedestrians and cyclists, employing the challenging and naturalistic KITTI images. This work proposes 3D-aware features computed from stereo color images in order to capture the appearance and depth peculiarities of the objects in road scenes. The successful part-based object detector, known as DPM, is extended to learn richer models from the 2.5D data (color and disparity), while also carrying out a detailed analysis of the training pipeline. A large set of experiments evaluate the proposals, and the best performing approach is ranked on the KITTI website. Indeed, this is the first work that reports results with stereo data for the KITTI object challenge, achieving increased detection ratios for the classes car and cyclist compared to a baseline DPM.

  18. Frio, Yegua objectives of E. Texas 3D seismic

    SciTech Connect

    1996-07-01

    Houston companies plan to explore deeper formations along the Sabine River on the Texas and Louisiana Gulf Coast. PetroGuard Co. Inc. and Jebco Seismic Inc., Houston, jointly secured a seismic and leasing option from Hankamer family et al. on about 120 sq miles in Newton County, Tex., and Calcasieu Parish, La. PetroGuard, which specializes in oilfield rehabilitation, has production experience in the area. Historic production in the area spans three major geologic trends: Oligocene Frio/Hackberry, downdip and mid-dip Eocene Yegua, and Eocene Wilcox. In the southern part of the area, to be explored first, the trends lie at 9,000--10,000 ft, 10,000--12,000 ft, and 14,000--15,000 ft, respectively. Output Exploration Co., an affiliate of Input/Output Inc., Houston, acquired from PetroGuard and Jebco all exploratory drilling rights in the option area. Output will conduct 3D seismic operations over nearly half the acreage this summer. Data acquisition started late this spring. Output plans to use a combination of a traditional land recording system and I/O`s new RSR 24 bit radio telemetry system because the area spans environments from dry land to swamp.

  19. 3D surface configuration modulates 2D symmetry detection.

    PubMed

    Chen, Chien-Chung; Sio, Lok-Teng

    2015-02-01

    We investigated whether three-dimensional (3D) information in a scene can affect symmetry detection. The stimuli were random dot patterns with 15% dot density. We measured the coherence threshold, or the proportion of dots that were the mirror reflection of the other dots in the other half of the image about a central vertical axis, at 75% accuracy with a 2AFC paradigm under various 3D configurations produced by the disparity between the left and right eye images. The results showed that symmetry detection was difficult when the corresponding dots across the symmetry axis were on different frontoparallel or inclined planes. However, this effect was not due to a difference in distance, as the observers could detect symmetry on a slanted surface, where the depth of the two sides of the symmetric axis was different. The threshold was reduced for a hinge configuration where the join of two slanted surfaces coincided with the axis of symmetry. Our result suggests that the detection of two-dimensional (2D) symmetry patterns is subject to the 3D configuration of the scene; and that coplanarity across the symmetry axis and consistency between the 2D pattern and 3D structure are important factors for symmetry detection.

  20. Recognition of 3D objects for autonomous mobile robot's navigation in automated shipbuilding

    NASA Astrophysics Data System (ADS)

    Lee, Hyunki; Cho, Hyungsuck

    2007-10-01

    Nowadays many parts of shipbuilding process are automated, but the painting process is not, because of the difficulty of automated on-line painting quality measurement, harsh painting environment and the difficulty of robot navigation. However, the painting automation is necessary, because it can provide consistent performance of painting film thickness. Furthermore, autonomous mobile robots are strongly required for flexible painting work. However, the main problem of autonomous mobile robot's navigation is that there are many obstacles which are not expressed in the CAD data. To overcome this problem, obstacle detection and recognition are necessary to avoid obstacles and painting work effectively. Until now many object recognition algorithms have been studied, especially 2D object recognition methods using intensity image have been widely studied. However, in our case environmental illumination does not exist, so these methods cannot be used. To overcome this, to use 3D range data must be used, but the problem of using 3D range data is high computational cost and long estimation time of recognition due to huge data base. In this paper, we propose a 3D object recognition algorithm based on PCA (Principle Component Analysis) and NN (Neural Network). In the algorithm, the novelty is that the measured 3D range data is transformed into intensity information, and then adopts the PCA and NN algorithm for transformed intensity information to reduce the processing time and make the data easy to handle which are disadvantages of previous researches of 3D object recognition. A set of experimental results are shown to verify the effectiveness of the proposed algorithm.

  1. Intuitive terrain reconstruction using height observation-based ground segmentation and 3D object boundary estimation.

    PubMed

    Song, Wei; Cho, Kyungeun; Um, Kyhyun; Won, Chee Sun; Sim, Sungdae

    2012-01-01

    Mobile robot operators must make rapid decisions based on information about the robot's surrounding environment. This means that terrain modeling and photorealistic visualization are required for the remote operation of mobile robots. We have produced a voxel map and textured mesh from the 2D and 3D datasets collected by a robot's array of sensors, but some upper parts of objects are beyond the sensors' measurements and these parts are missing in the terrain reconstruction result. This result is an incomplete terrain model. To solve this problem, we present a new ground segmentation method to detect non-ground data in the reconstructed voxel map. Our method uses height histograms to estimate the ground height range, and a Gibbs-Markov random field model to refine the segmentation results. To reconstruct a complete terrain model of the 3D environment, we develop a 3D boundary estimation method for non-ground objects. We apply a boundary detection technique to the 2D image, before estimating and refining the actual height values of the non-ground vertices in the reconstructed textured mesh. Our proposed methods were tested in an outdoor environment in which trees and buildings were not completely sensed. Our results show that the time required for ground segmentation is faster than that for data sensing, which is necessary for a real-time approach. In addition, those parts of objects that were not sensed are accurately recovered to retrieve their real-world appearances. PMID:23235454

  2. Intuitive Terrain Reconstruction Using Height Observation-Based Ground Segmentation and 3D Object Boundary Estimation

    PubMed Central

    Song, Wei; Cho, Kyungeun; Um, Kyhyun; Won, Chee Sun; Sim, Sungdae

    2012-01-01

    Mobile robot operators must make rapid decisions based on information about the robot’s surrounding environment. This means that terrain modeling and photorealistic visualization are required for the remote operation of mobile robots. We have produced a voxel map and textured mesh from the 2D and 3D datasets collected by a robot’s array of sensors, but some upper parts of objects are beyond the sensors’ measurements and these parts are missing in the terrain reconstruction result. This result is an incomplete terrain model. To solve this problem, we present a new ground segmentation method to detect non-ground data in the reconstructed voxel map. Our method uses height histograms to estimate the ground height range, and a Gibbs-Markov random field model to refine the segmentation results. To reconstruct a complete terrain model of the 3D environment, we develop a 3D boundary estimation method for non-ground objects. We apply a boundary detection technique to the 2D image, before estimating and refining the actual height values of the non-ground vertices in the reconstructed textured mesh. Our proposed methods were tested in an outdoor environment in which trees and buildings were not completely sensed. Our results show that the time required for ground segmentation is faster than that for data sensing, which is necessary for a real-time approach. In addition, those parts of objects that were not sensed are accurately recovered to retrieve their real-world appearances. PMID:23235454

  3. Intuitive terrain reconstruction using height observation-based ground segmentation and 3D object boundary estimation.

    PubMed

    Song, Wei; Cho, Kyungeun; Um, Kyhyun; Won, Chee Sun; Sim, Sungdae

    2012-12-12

    Mobile robot operators must make rapid decisions based on information about the robot's surrounding environment. This means that terrain modeling and photorealistic visualization are required for the remote operation of mobile robots. We have produced a voxel map and textured mesh from the 2D and 3D datasets collected by a robot's array of sensors, but some upper parts of objects are beyond the sensors' measurements and these parts are missing in the terrain reconstruction result. This result is an incomplete terrain model. To solve this problem, we present a new ground segmentation method to detect non-ground data in the reconstructed voxel map. Our method uses height histograms to estimate the ground height range, and a Gibbs-Markov random field model to refine the segmentation results. To reconstruct a complete terrain model of the 3D environment, we develop a 3D boundary estimation method for non-ground objects. We apply a boundary detection technique to the 2D image, before estimating and refining the actual height values of the non-ground vertices in the reconstructed textured mesh. Our proposed methods were tested in an outdoor environment in which trees and buildings were not completely sensed. Our results show that the time required for ground segmentation is faster than that for data sensing, which is necessary for a real-time approach. In addition, those parts of objects that were not sensed are accurately recovered to retrieve their real-world appearances.

  4. Recognition of Simple 3D Geometrical Objects under Partial Occlusion

    NASA Astrophysics Data System (ADS)

    Barchunova, Alexandra; Sommer, Gerald

    In this paper we present a novel procedure for contour-based recognition of partially occluded three-dimensional objects. In our approach we use images of real and rendered objects whose contours have been deformed by a restricted change of the viewpoint. The preparatory part consists of contour extraction, preprocessing, local structure analysis and feature extraction. The main part deals with an extended construction and functionality of the classifier ensemble Adaptive Occlusion Classifier (AOC). It relies on a hierarchical fragmenting algorithm to perform a local structure analysis which is essential when dealing with occlusions. In the experimental part of this paper we present classification results for five classes of simple geometrical figures: prism, cylinder, half cylinder, a cube, and a bridge. We compare classification results for three classical feature extractors: Fourier descriptors, pseudo Zernike and Zernike moments.

  5. Surface gloss and color perception of 3D objects

    PubMed Central

    Xiao, Bei; Brainard, David H.

    2008-01-01

    Two experiments explore the color perception of objects in complex scenes. The first experiment examines the color perception of objects across variation in surface gloss. Observers adjusted the color appearance of a matte sphere to match that of a test sphere. Across conditions we varied the body color and glossiness of the test sphere. The data indicate that observers do not simply match the average light reflected from the test. Indeed, the visual system compensates for the physical effect of varying the gloss, so that appearance is stabilized relative to what is predicted by the spatial average. The second experiment examines how people perceive color across locations on an object. We replaced the test sphere with a soccer ball that had one of its hexagonal faces colored. Observers were asked to adjust the match sphere have the same color appearance as this test patch. The test patch could be located at either an upper or lower location on the soccer ball. In addition, we varied the surface gloss of the entire soccer ball (including the test patch). The data show that there is an effect of test patch location on observers’ color matching, but this effect is small compared to the physical change in the average light reflected from the test patch across the two locations. In addition, the effect of glossy highlights on the color appearance of the test patch was consistent with the results from Experiment 1. PMID:18598406

  6. A New Algorithm for 3D Dendritic Spine Detection

    NASA Astrophysics Data System (ADS)

    Zhou, Wengang; Li, Houqiang; Zhou, Xiaobo; Wong, Stephen

    2007-11-01

    It has been shown in recent research that there is a close relationship between neurological functions of neuron and its morphology. As manual analysis of large data sets is too tedious and may be subjected to user bias, a computer aided processing method is urgently desired. In this paper, we propose an automatic approach for 3D dendritic spine detection, which can greatly help neuron-biologists to obtain morphological information about a neuron and its spines. The work mainly consists of segmentation and spine component detection. The segmentation of dendrite and spine components is carried out by means of 3D level set based on local binary fitting model, which yields better results than global threshold method. As for spine component detection, an efficient approach is presented which consists of backbone extraction, detached and attached spine components detection. The detection is robust to noise and the detected spines are well represented. We validate our algorithm with real 3D neuron images and the result reveals that it works well.

  7. Combining depth and color data for 3D object recognition

    NASA Astrophysics Data System (ADS)

    Joergensen, Thomas M.; Linneberg, Christian; Andersen, Allan W.

    1997-09-01

    This paper describes the shape recognition system that has been developed within the ESPRIT project 9052 ADAS on automatic disassembly of TV-sets using a robot cell. Depth data from a chirped laser radar are fused with color data from a video camera. The sensor data is pre-processed in several ways and the obtained representation is used to train a RAM neural network (memory based reasoning approach) to detect different components within TV-sets. The shape recognizing architecture has been implemented and tested in a demonstration setup.

  8. An object-oriented simulator for 3D digital breast tomosynthesis imaging system.

    PubMed

    Seyyedi, Saeed; Cengiz, Kubra; Kamasak, Mustafa; Yildirim, Isa

    2013-01-01

    Digital breast tomosynthesis (DBT) is an innovative imaging modality that provides 3D reconstructed images of breast to detect the breast cancer. Projections obtained with an X-ray source moving in a limited angle interval are used to reconstruct 3D image of breast. Several reconstruction algorithms are available for DBT imaging. Filtered back projection algorithm has traditionally been used to reconstruct images from projections. Iterative reconstruction algorithms such as algebraic reconstruction technique (ART) were later developed. Recently, compressed sensing based methods have been proposed in tomosynthesis imaging problem. We have developed an object-oriented simulator for 3D digital breast tomosynthesis (DBT) imaging system using C++ programming language. The simulator is capable of implementing different iterative and compressed sensing based reconstruction methods on 3D digital tomosynthesis data sets and phantom models. A user friendly graphical user interface (GUI) helps users to select and run the desired methods on the designed phantom models or real data sets. The simulator has been tested on a phantom study that simulates breast tomosynthesis imaging problem. Results obtained with various methods including algebraic reconstruction technique (ART) and total variation regularized reconstruction techniques (ART+TV) are presented. Reconstruction results of the methods are compared both visually and quantitatively by evaluating performances of the methods using mean structural similarity (MSSIM) values. PMID:24371468

  9. 3D reconstruction based on multiple views for close-range objects

    NASA Astrophysics Data System (ADS)

    Ji, Zheng; Zhang, Jianqing

    2007-06-01

    It is difficult for traditional photogrammetry techniques to reconstruct 3D model of close-range objects. To overcome the restriction and realize complex objects' 3D reconstruction, we present a realistic approach on the basis of multi-baseline stereo vision. This incorporates the image matching based on short-baseline-multi-views, and 3D measurement based on multi-ray intersection, and the 3D reconstruction of the object's based on TIN or parametric geometric model. Different complex object are reconstructed by this way. The results demonstrate the feasibility and effectivity of the method.

  10. Blind robust watermarking schemes for copyright protection of 3D mesh objects.

    PubMed

    Zafeiriou, Stefanos; Tefas, Anastasios; Pitas, Ioannis

    2005-01-01

    In this paper, two novel methods suitable for blind 3D mesh object watermarking applications are proposed. The first method is robust against 3D rotation, translation, and uniform scaling. The second one is robust against both geometric and mesh simplification attacks. A pseudorandom watermarking signal is cast in the 3D mesh object by deforming its vertices geometrically, without altering the vertex topology. Prior to watermark embedding and detection, the object is rotated and translated so that its center of mass and its principal component coincide with the origin and the z-axis of the Cartesian coordinate system. This geometrical transformation ensures watermark robustness to translation and rotation. Robustness to uniform scaling is achieved by restricting the vertex deformations to occur only along the r coordinate of the corresponding (r, theta, phi) spherical coordinate system. In the first method, a set of vertices that correspond to specific angles theta is used for watermark embedding. In the second method, the samples of the watermark sequence are embedded in a set of vertices that correspond to a range of angles in the theta domain in order to achieve robustness against mesh simplifications. Experimental results indicate the ability of the proposed method to deal with the aforementioned attacks.

  11. OB3D, a new set of 3D objects available for research: a web-based study

    PubMed Central

    Buffat, Stéphane; Chastres, Véronique; Bichot, Alain; Rider, Delphine; Benmussa, Frédéric; Lorenceau, Jean

    2014-01-01

    Studying object recognition is central to fundamental and clinical research on cognitive functions but suffers from the limitations of the available sets that cannot always be modified and adapted to meet the specific goals of each study. We here present a new set of 3D scans of real objects available on-line as ASCII files, OB3D. These files are lists of dots, each defined by a triplet of spatial coordinates and their normal that allow simple and highly versatile transformations and adaptations. We performed a web-based experiment to evaluate the minimal number of dots required for the denomination and categorization of these objects, thus providing a reference threshold. We further analyze several other variables derived from this data set, such as the correlations with object complexity. This new stimulus set, which was found to activate the Lower Occipital Complex (LOC) in another study, may be of interest for studies of cognitive functions in healthy participants and patients with cognitive impairments, including visual perception, language, memory, etc. PMID:25339920

  12. Reducing Non-Uniqueness in Satellite Gravity Inversion using 3D Object Oriented Image Analysis Techniques

    NASA Astrophysics Data System (ADS)

    Fadel, I.; van der Meijde, M.; Kerle, N.

    2013-12-01

    Non-uniqueness of satellite gravity interpretation has been usually reduced by using a priori information from various sources, e.g. seismic tomography models. The reduction in non-uniqueness has been based on velocity-density conversion formulas or user interpretation for 3D subsurface structures (objects) in seismic tomography models. However, these processes introduce additional uncertainty through the conversion relations due to the dependency on the other physical parameters such as temperature and pressure, or through the bias in the interpretation due to user choices and experience. In this research, a new methodology is introduced to extract the 3D subsurface structures from 3D geophysical data using a state-of-art 3D Object Oriented Image Analysis (OOA) technique. 3D OOA is tested using a set of synthetic models that simulate the real situation in the study area of this research. Then, 3D OOA is used to extract 3D subsurface objects from a real 3D seismic tomography model. The extracted 3D objects are used to reconstruct a forward model and its response is compared with the measured satellite gravity. Finally, the result of the forward modelling, based on the extracted 3D objects, is used to constrain the inversion process of satellite gravity data. Through this work, a new object-based approach is introduced to interpret and extract the 3D subsurface objects from 3D geophysical data. This can be used to constrain modelling and inversion of potential field data using the extracted 3D subsurface structures from other methods. In summary, a new approach is introduced to constrain inversion of satellite gravity measurements and enhance interpretation capabilities.

  13. Probabilistic 3D object recognition and pose estimation using multiple interpretations generation.

    PubMed

    Lu, Zhaojin; Lee, Sukhan

    2011-12-01

    This paper presents a probabilistic object recognition and pose estimation method using multiple interpretation generation in cluttered indoor environments. How to handle pose ambiguity and uncertainty is the main challenge in most recognition systems. In order to solve this problem, we approach it in a probabilistic manner. First, given a three-dimensional (3D) polyhedral object model, the parallel and perpendicular line pairs, which are detected from stereo images and 3D point clouds, generate pose hypotheses as multiple interpretations, with ambiguity from partial occlusion and fragmentation of 3D lines especially taken into account. Different from the previous methods, each pose interpretation is represented as a region instead of a point in pose space reflecting the measurement uncertainty. Then, for each pose interpretation, more features around the estimated pose are further utilized as additional evidence for computing the probability using the Bayesian principle in terms of likelihood and unlikelihood. Finally, fusion strategy is applied to the top ranked interpretations with high probabilities, which are further verified and refined to give a more accurate pose estimation in real time. The experimental results show the performance and potential of the proposed approach in real cluttered domestic environments.

  14. Robust object tracking techniques for vision-based 3D motion analysis applications

    NASA Astrophysics Data System (ADS)

    Knyaz, Vladimir A.; Zheltov, Sergey Y.; Vishnyakov, Boris V.

    2016-04-01

    Automated and accurate spatial motion capturing of an object is necessary for a wide variety of applications including industry and science, virtual reality and movie, medicine and sports. For the most part of applications a reliability and an accuracy of the data obtained as well as convenience for a user are the main characteristics defining the quality of the motion capture system. Among the existing systems for 3D data acquisition, based on different physical principles (accelerometry, magnetometry, time-of-flight, vision-based), optical motion capture systems have a set of advantages such as high speed of acquisition, potential for high accuracy and automation based on advanced image processing algorithms. For vision-based motion capture accurate and robust object features detecting and tracking through the video sequence are the key elements along with a level of automation of capturing process. So for providing high accuracy of obtained spatial data the developed vision-based motion capture system "Mosca" is based on photogrammetric principles of 3D measurements and supports high speed image acquisition in synchronized mode. It includes from 2 to 4 technical vision cameras for capturing video sequences of object motion. The original camera calibration and external orientation procedures provide the basis for high accuracy of 3D measurements. A set of algorithms as for detecting, identifying and tracking of similar targets, so for marker-less object motion capture is developed and tested. The results of algorithms' evaluation show high robustness and high reliability for various motion analysis tasks in technical and biomechanics applications.

  15. Whole versus Part Presentations of the Interactive 3D Graphics Learning Objects

    ERIC Educational Resources Information Center

    Azmy, Nabil Gad; Ismaeel, Dina Ahmed

    2010-01-01

    The purpose of this study is to present an analysis of how the structure and design of the Interactive 3D Graphics Learning Objects can be effective and efficient in terms of Performance, Time on task, and Learning Efficiency. The study explored two treatments, namely whole versus Part Presentations of the Interactive 3D Graphics Learning Objects,…

  16. Feature detection on 3D images of dental imprints

    NASA Astrophysics Data System (ADS)

    Mokhtari, Marielle; Laurendeau, Denis

    1994-09-01

    A computer vision approach for the extraction of feature points on 3D images of dental imprints is presented. The position of feature points are needed for the measurement of a set of parameters for automatic diagnosis of malocclusion problems in orthodontics. The system for the acquisition of the 3D profile of the imprint, the procedure for the detection of the interstices between teeth, and the approach for the identification of the type of tooth are described, as well as the algorithm for the reconstruction of the surface of each type of tooth. A new approach for the detection of feature points, called the watershed algorithm, is described in detail. The algorithm is a two-stage procedure which tracks the position of local minima at four different scales and produces a final map of the position of the minima. Experimental results of the application of the watershed algorithm on actual 3D images of dental imprints are presented for molars, premolars and canines. The segmentation approach for the analysis of the shape of incisors is also described in detail.

  17. Non-destructive 3D shape measurement of transparent and black objects with thermal fringes

    NASA Astrophysics Data System (ADS)

    Brahm, Anika; Rößler, Conrad; Dietrich, Patrick; Heist, Stefan; Kühmstedt, Peter; Notni, Gunther

    2016-05-01

    Fringe projection is a well-established optical method for the non-destructive contactless three-dimensional (3D) measurement of object surfaces. Typically, fringe sequences in the visible wavelength range (VIS) are projected onto the surfaces of objects to be measured and are observed by two cameras in a stereo vision setup. The reconstruction is done by finding corresponding pixels in both cameras followed by triangulation. Problems can occur if the properties of some materials disturb the measurements. If the objects are transparent, translucent, reflective, or strongly absorbing in the VIS range, the projected patterns cannot be recorded properly. To overcome these challenges, we present a new alternative approach in the infrared (IR) region of the electromagnetic spectrum. For this purpose, two long-wavelength infrared (LWIR) cameras (7.5 - 13 μm) are used to detect the emitted heat radiation from surfaces which is induced by a pattern projection unit driven by a CO2 laser (10.6 μm). Thus, materials like glass or black objects, e.g. carbon fiber materials, can be measured non-destructively without the need of any additional paintings. We will demonstrate the basic principles of this heat pattern approach and show two types of 3D systems based on a freeform mirror and a GOBO wheel (GOes Before Optics) projector unit.

  18. 3d Modeling of cultural heritage objects with a structured light system.

    NASA Astrophysics Data System (ADS)

    Akca, Devrim

    3D modeling of cultural heritage objects is an expanding application area. The selection of the right technology is very important and strictly related to the project requirements, budget and user's experience. The triangulation based active sensors, e.g. structured light systems are used for many kinds of 3D object reconstruction tasks and in particular for 3D recording of cultural heritage objects. This study presents the experiences in the results of two such projects in which a close-range structured light system is used for the 3D digitization. The paper includes the essential steps of the 3D object modeling pipeline, i.e. digitization, registration, surface triangulation, editing, texture mapping and visualization. The capabilities of the used hardware and software are addressed. Particular emphasis is given to a coded structured light system as an option for data acquisition.

  19. A method of 3D object recognition and localization in a cloud of points

    NASA Astrophysics Data System (ADS)

    Bielicki, Jerzy; Sitnik, Robert

    2013-12-01

    The proposed method given in this article is prepared for analysis of data in the form of cloud of points directly from 3D measurements. It is designed for use in the end-user applications that can directly be integrated with 3D scanning software. The method utilizes locally calculated feature vectors (FVs) in point cloud data. Recognition is based on comparison of the analyzed scene with reference object library. A global descriptor in the form of a set of spatially distributed FVs is created for each reference model. During the detection process, correlation of subsets of reference FVs with FVs calculated in the scene is computed. Features utilized in the algorithm are based on parameters, which qualitatively estimate mean and Gaussian curvatures. Replacement of differentiation with averaging in the curvatures estimation makes the algorithm more resistant to discontinuities and poor quality of the input data. Utilization of the FV subsets allows to detect partially occluded and cluttered objects in the scene, while additional spatial information maintains false positive rate at a reasonably low level.

  20. 3D video analysis of the novel object recognition test in rats.

    PubMed

    Matsumoto, Jumpei; Uehara, Takashi; Urakawa, Susumu; Takamura, Yusaku; Sumiyoshi, Tomiki; Suzuki, Michio; Ono, Taketoshi; Nishijo, Hisao

    2014-10-01

    The novel object recognition (NOR) test has been widely used to test memory function. We developed a 3D computerized video analysis system that estimates nose contact with an object in Long Evans rats to analyze object exploration during NOR tests. The results indicate that the 3D system reproducibly and accurately scores the NOR test. Furthermore, the 3D system captures a 3D trajectory of the nose during object exploration, enabling detailed analyses of spatiotemporal patterns of object exploration. The 3D trajectory analysis revealed a specific pattern of object exploration in the sample phase of the NOR test: normal rats first explored the lower parts of objects and then gradually explored the upper parts. A systematic injection of MK-801 suppressed changes in these exploration patterns. The results, along with those of previous studies, suggest that the changes in the exploration patterns reflect neophobia to a novel object and/or changes from spatial learning to object learning. These results demonstrate that the 3D tracking system is useful not only for detailed scoring of animal behaviors but also for investigation of characteristic spatiotemporal patterns of object exploration. The system has the potential to facilitate future investigation of neural mechanisms underlying object exploration that result from dynamic and complex brain activity. PMID:24991752

  1. Visual Short-Term Memory Benefit for Objects on Different 3-D Surfaces

    ERIC Educational Resources Information Center

    Xu, Yaoda; Nakayama, Ken

    2007-01-01

    Visual short-term memory (VSTM) plays an important role in visual cognition. Although objects are located on different 3-dimensional (3-D) surfaces in the real world, how VSTM capacity may be influenced by the presence of multiple 3-D surfaces has never been examined. By manipulating binocular disparities of visual displays, the authors found that…

  2. A Gaussian Mixture Model-Based Continuous Boundary Detection for 3D Sensor Networks

    PubMed Central

    Chen, Jiehui; Salim, Mariam B.; Matsumoto, Mitsuji

    2010-01-01

    This paper proposes a high precision Gaussian Mixture Model-based novel Boundary Detection 3D (BD3D) scheme with reasonable implementation cost for 3D cases by selecting a minimum number of Boundary sensor Nodes (BNs) in continuous moving objects. It shows apparent advantages in that two classes of boundary and non-boundary sensor nodes can be efficiently classified using the model selection techniques for finite mixture models; furthermore, the set of sensor readings within each sensor node’s spatial neighbors is formulated using a Gaussian Mixture Model; different from DECOMO [1] and COBOM [2], we also formatted a BN Array with an additional own sensor reading to benefit selecting Event BNs (EBNs) and non-EBNs from the observations of BNs. In particular, we propose a Thick Section Model (TSM) to solve the problem of transition between 2D and 3D. It is verified by simulations that the BD3D 2D model outperforms DECOMO and COBOM in terms of average residual energy and the number of BNs selected, while the BD3D 3D model demonstrates sound performance even for sensor networks with low densities especially when the value of the sensor transmission range (r) is larger than the value of Section Thickness (d) in TSM. We have also rigorously proved its correctness for continuous geometric domains and full robustness for sensor networks over 3D terrains. PMID:22163619

  3. 3D object recognition using kernel construction of phase wrapped images

    NASA Astrophysics Data System (ADS)

    Zhang, Hong; Su, Hongjun

    2011-06-01

    Kernel methods are effective machine learning techniques for many image based pattern recognition problems. Incorporating 3D information is useful in such applications. The optical profilometries and interforometric techniques provide 3D information in an implicit form. Typically phase unwrapping process, which is often hindered by the presence of noises, spots of low intensity modulation, and instability of the solutions, is applied to retrieve the proper depth information. In certain applications such as pattern recognition problems, the goal is to classify the 3D objects in the image, rather than to simply display or reconstruct them. In this paper we present a technique for constructing kernels on the measured data directly without explicit phase unwrapping. Such a kernel will naturally incorporate the 3D depth information and can be used to improve the systems involving 3D object analysis and classification.

  4. Recognizing objects in 3D point clouds with multi-scale local features.

    PubMed

    Lu, Min; Guo, Yulan; Zhang, Jun; Ma, Yanxin; Lei, Yinjie

    2014-01-01

    Recognizing 3D objects from point clouds in the presence of significant clutter and occlusion is a highly challenging task. In this paper, we present a coarse-to-fine 3D object recognition algorithm. During the phase of offline training, each model is represented with a set of multi-scale local surface features. During the phase of online recognition, a set of keypoints are first detected from each scene. The local surfaces around these keypoints are further encoded with multi-scale feature descriptors. These scene features are then matched against all model features to generate recognition hypotheses, which include model hypotheses and pose hypotheses. Finally, these hypotheses are verified to produce recognition results. The proposed algorithm was tested on two standard datasets, with rigorous comparisons to the state-of-the-art algorithms. Experimental results show that our algorithm was fully automatic and highly effective. It was also very robust to occlusion and clutter. It achieved the best recognition performance on all of these datasets, showing its superiority compared to existing algorithms.

  5. Extraction and classification of 3D objects from volumetric CT data

    NASA Astrophysics Data System (ADS)

    Song, Samuel M.; Kwon, Junghyun; Ely, Austin; Enyeart, John; Johnson, Chad; Lee, Jongkyu; Kim, Namho; Boyd, Douglas P.

    2016-05-01

    We propose an Automatic Threat Detection (ATD) algorithm for Explosive Detection System (EDS) using our multistage Segmentation Carving (SC) followed by Support Vector Machine (SVM) classifier. The multi-stage Segmentation and Carving (SC) step extracts all suspect 3-D objects. The feature vector is then constructed for all extracted objects and the feature vector is classified by the Support Vector Machine (SVM) previously learned using a set of ground truth threat and benign objects. The learned SVM classifier has shown to be effective in classification of different types of threat materials. The proposed ATD algorithm robustly deals with CT data that are prone to artifacts due to scatter, beam hardening as well as other systematic idiosyncrasies of the CT data. Furthermore, the proposed ATD algorithm is amenable for including newly emerging threat materials as well as for accommodating data from newly developing sensor technologies. Efficacy of the proposed ATD algorithm with the SVM classifier is demonstrated by the Receiver Operating Characteristics (ROC) curve that relates Probability of Detection (PD) as a function of Probability of False Alarm (PFA). The tests performed using CT data of passenger bags shows excellent performance characteristics.

  6. Electrophysiological evidence of separate pathways for the perception of depth and 3D objects.

    PubMed

    Gao, Feng; Cao, Bihua; Cao, Yunfei; Li, Fuhong; Li, Hong

    2015-05-01

    Previous studies have investigated the neural mechanism of 3D perception, but the neural distinction between 3D-objects and depth processing remains unclear. In the present study, participants viewed three types of graphics (planar graphics, perspective drawings, and 3D objects) while event-related potentials (ERP) were recorded. The ERP results revealed the following: (1) 3D objects elicited a larger and delayed N1 component than the other two types of stimuli; (2) during the P2 time window, significant differences between 3D objects and the perspective drawings were found mainly over a group of electrode sites in the left lateral occipital region; and (3) during the N2 complex, differences between planar graphics and perspective drawings were found over a group of electrode sites in the right hemisphere, whereas differences between perspective drawings and 3D objects were observed at another group of electrode sites in the left hemisphere. These findings support the claim that depth processing and object identification might be processed by separate pathways and at different latencies.

  7. Representing 3D virtual objects: interaction between visuo-spatial ability and type of exploration.

    PubMed

    Meijer, Frank; van den Broek, Egon L

    2010-03-17

    We investigated individual differences in interactively exploring 3D virtual objects. 36 participants explored 24 simple and 24 difficult objects (composed of respectively three and five Biederman geons) actively, passively, or not at all. Both their 3D mental representation of the objects and visuo-spatial ability was assessed. Results show that, regardless of the object's complexity, people with a low VSA benefit from active exploration of objects, where people with a middle or high VSA do not. These findings extend and refine earlier research on interactively learning visuo-spatial information and underline the importance to take individual differences into account. PMID:20116394

  8. Representing 3D virtual objects: interaction between visuo-spatial ability and type of exploration.

    PubMed

    Meijer, Frank; van den Broek, Egon L

    2010-03-17

    We investigated individual differences in interactively exploring 3D virtual objects. 36 participants explored 24 simple and 24 difficult objects (composed of respectively three and five Biederman geons) actively, passively, or not at all. Both their 3D mental representation of the objects and visuo-spatial ability was assessed. Results show that, regardless of the object's complexity, people with a low VSA benefit from active exploration of objects, where people with a middle or high VSA do not. These findings extend and refine earlier research on interactively learning visuo-spatial information and underline the importance to take individual differences into account.

  9. Three-dimensional object recognition using gradient descent and the universal 3-D array grammar

    NASA Astrophysics Data System (ADS)

    Baird, Leemon C., III; Wang, Patrick S. P.

    1992-02-01

    A new algorithm is presented for applying Marill's minimum standard deviation of angles (MSDA) principle for interpreting line drawings without models. Even though no explicit models or additional heuristics are included, the algorithm tends to reach the same 3-D interpretations of 2-D line drawings that humans do. Marill's original algorithm repeatedly generated a set of interpretations and chose the one with the lowest standard deviation of angles (SDA). The algorithm presented here explicitly calculates the partial derivatives of SDA with respect to all adjustable parameters, and follows this gradient to minimize SDA. For a picture with lines meeting at m points forming n angles, the gradient descent algorithm requires O(n) time to adjust all the points, while the original algorithm required O(mn) time to do so. For the pictures described by Marill, this gradient descent algorithm running on a Macintosh II was found to be one to two orders of magnitude faster than the original algorithm running on a Symbolics, while still giving comparable results. Once the 3-D interpretation of the line drawing has been found, the 3-D object can be reduced to a description string using the Universal 3-D Array Grammar. This is a general grammar which allows any connected object represented as a 3-D array of pixels to be reduced to a description string. The algorithm based on this grammar is well suited to parallel computation, and could run efficiently on parallel hardware. This paper describes both the MSDA gradient descent algorithm and the Universal 3-D Array Grammar algorithm. Together, they transform a 2-D line drawing represented as a list of line segments into a string describing the 3-D object pictured. The strings could then be used for object recognition, learning, or storage for later manipulation.

  10. 3D object retrieval with multitopic model combining relevance feedback and LDA model.

    PubMed

    Leng, Biao; Zeng, Jiabei; Yao, Ming; Xiong, Zhang

    2015-01-01

    View-based 3D model retrieval uses a set of views to represent each object. Discovering the complex relationship between multiple views remains challenging in 3D object retrieval. Recent progress in the latent Dirichlet allocation (LDA) model leads us to propose its use for 3D object retrieval. This LDA approach explores the hidden relationships between extracted primordial features of these views. Since LDA is limited to a fixed number of topics, we further propose a multitopic model to improve retrieval performance. We take advantage of a relevance feedback mechanism to balance the contributions of multiple topic models with specified numbers of topics. We demonstrate our improved retrieval performance over the state-of-the-art approaches.

  11. High-purity 3D nano-objects grown by focused-electron-beam induced deposition

    NASA Astrophysics Data System (ADS)

    Córdoba, Rosa; Sharma, Nidhi; Kölling, Sebastian; Koenraad, Paul M.; Koopmans, Bert

    2016-09-01

    To increase the efficiency of current electronics, a specific challenge for the next generation of memory, sensing and logic devices is to find suitable strategies to move from two- to three-dimensional (3D) architectures. However, the creation of real 3D nano-objects is not trivial. Emerging non-conventional nanofabrication tools are required for this purpose. One attractive method is focused-electron-beam induced deposition (FEBID), a direct-write process of 3D nano-objects. Here, we grow 3D iron and cobalt nanopillars by FEBID using diiron nonacarbonyl Fe2(CO)9, and dicobalt octacarbonyl Co2(CO)8, respectively, as starting materials. In addition, we systematically study the composition of these nanopillars at the sub-nanometer scale by atom probe tomography, explicitly mapping the homogeneity of the radial and longitudinal composition distributions. We show a way of fabricating high-purity 3D vertical nanostructures of ∼50 nm in diameter and a few micrometers in length. Our results suggest that the purity of such 3D nanoelements (above 90 at% Fe and above 95 at% Co) is directly linked to their growth regime, in which the selected deposition conditions are crucial for the final quality of the nanostructure. Moreover, we demonstrate that FEBID and the proposed characterization technique not only allow for growth and chemical analysis of single-element structures, but also offers a new way to directly study 3D core–shell architectures. This straightforward concept could establish a promising route to the design of 3D elements for future nano-electronic devices.

  12. High-purity 3D nano-objects grown by focused-electron-beam induced deposition

    NASA Astrophysics Data System (ADS)

    Córdoba, Rosa; Sharma, Nidhi; Kölling, Sebastian; Koenraad, Paul M.; Koopmans, Bert

    2016-09-01

    To increase the efficiency of current electronics, a specific challenge for the next generation of memory, sensing and logic devices is to find suitable strategies to move from two- to three-dimensional (3D) architectures. However, the creation of real 3D nano-objects is not trivial. Emerging non-conventional nanofabrication tools are required for this purpose. One attractive method is focused-electron-beam induced deposition (FEBID), a direct-write process of 3D nano-objects. Here, we grow 3D iron and cobalt nanopillars by FEBID using diiron nonacarbonyl Fe2(CO)9, and dicobalt octacarbonyl Co2(CO)8, respectively, as starting materials. In addition, we systematically study the composition of these nanopillars at the sub-nanometer scale by atom probe tomography, explicitly mapping the homogeneity of the radial and longitudinal composition distributions. We show a way of fabricating high-purity 3D vertical nanostructures of ˜50 nm in diameter and a few micrometers in length. Our results suggest that the purity of such 3D nanoelements (above 90 at% Fe and above 95 at% Co) is directly linked to their growth regime, in which the selected deposition conditions are crucial for the final quality of the nanostructure. Moreover, we demonstrate that FEBID and the proposed characterization technique not only allow for growth and chemical analysis of single-element structures, but also offers a new way to directly study 3D core-shell architectures. This straightforward concept could establish a promising route to the design of 3D elements for future nano-electronic devices.

  13. Detection of Curved Robots using 3D Ultrasound.

    PubMed

    Ren, Hongliang; Vasilyev, Nikolay V; Dupont, Pierre E

    2011-09-25

    Three-dimensional ultrasound can be an effective imaging modality for image-guided interventions since it enables visualization of both the instruments and the tissue. For robotic applications, its realtime frame rates create the potential for image-based instrument tracking and servoing. These capabilities can enable improved instrument visualization, compensation for tissue motion as well as surgical task automation. Continuum robots, whose shape comprises a smooth curve along their length, are well suited for minimally invasive procedures. Existing techniques for ultrasound tracking, however, are limited to straight, laparoscopic-type instruments and thus are not applicable to continuum robot tracking. Toward the goal of developing tracking algorithms for continuum robots, this paper presents a method for detecting a robot comprised of a single constant curvature in a 3D ultrasound volume. Computational efficiency is achieved by decomposing the six-dimensional circle estimation problem into two sequential three-dimensional estimation problems. Simulation and experiment are used to evaluate the proposed method. PMID:22229110

  14. Detection of Disease Symptoms on Hyperspectral 3d Plant Models

    NASA Astrophysics Data System (ADS)

    Roscher, Ribana; Behmann, Jan; Mahlein, Anne-Katrin; Dupuis, Jan; Kuhlmann, Heiner; Plümer, Lutz

    2016-06-01

    We analyze the benefit of combining hyperspectral images information with 3D geometry information for the detection of Cercospora leaf spot disease symptoms on sugar beet plants. Besides commonly used one-class Support Vector Machines, we utilize an unsupervised sparse representation-based approach with group sparsity prior. Geometry information is incorporated by representing each sample of interest with an inclination-sorted dictionary, which can be seen as an 1D topographic dictionary. We compare this approach with a sparse representation based approach without geometry information and One-Class Support Vector Machines. One-Class Support Vector Machines are applied to hyperspectral data without geometry information as well as to hyperspectral images with additional pixelwise inclination information. Our results show a gain in accuracy when using geometry information beside spectral information regardless of the used approach. However, both methods have different demands on the data when applied to new test data sets. One-Class Support Vector Machines require full inclination information on test and training data whereas the topographic dictionary approach only need spectral information for reconstruction of test data once the dictionary is build by spectra with inclination.

  15. Detection of Curved Robots using 3D Ultrasound.

    PubMed

    Ren, Hongliang; Vasilyev, Nikolay V; Dupont, Pierre E

    2011-09-25

    Three-dimensional ultrasound can be an effective imaging modality for image-guided interventions since it enables visualization of both the instruments and the tissue. For robotic applications, its realtime frame rates create the potential for image-based instrument tracking and servoing. These capabilities can enable improved instrument visualization, compensation for tissue motion as well as surgical task automation. Continuum robots, whose shape comprises a smooth curve along their length, are well suited for minimally invasive procedures. Existing techniques for ultrasound tracking, however, are limited to straight, laparoscopic-type instruments and thus are not applicable to continuum robot tracking. Toward the goal of developing tracking algorithms for continuum robots, this paper presents a method for detecting a robot comprised of a single constant curvature in a 3D ultrasound volume. Computational efficiency is achieved by decomposing the six-dimensional circle estimation problem into two sequential three-dimensional estimation problems. Simulation and experiment are used to evaluate the proposed method.

  16. Surveillance, detection, and 3D infrared tracking of bullets, rockets, mortars, and artillery

    NASA Astrophysics Data System (ADS)

    Leslie, Daniel H.; Hyman, Howard; Moore, Fritz; Squire, Mark D.

    2001-09-01

    We describe test results using the FIRST (Fast InfraRed Sniper Tracker) to detect, track, and range to bullets in flight for determining the location of the bullet launch point. The technology developed for the FIRST system can be used to provide detection and accurate 3D track data for other small threat objects including rockets, mortars, and artillery in addition to bullets. We discuss the radiometry and detection range for these objects, and discuss the trade-offs involved in design of the very fast optical system for acquisition, tracking, and ranging of these targets.

  17. A convolutional learning system for object classification in 3-D Lidar data.

    PubMed

    Prokhorov, Danil

    2010-05-01

    In this brief, a convolutional learning system for classification of segmented objects represented in 3-D as point clouds of laser reflections is proposed. Several novelties are discussed: (1) extension of the existing convolutional neural network (CNN) framework to direct processing of 3-D data in a multiview setting which may be helpful for rotation-invariant consideration, (2) improvement of CNN training effectiveness by employing a stochastic meta-descent (SMD) method, and (3) combination of unsupervised and supervised training for enhanced performance of CNN. CNN performance is illustrated on a two-class data set of objects in a segmented outdoor environment.

  18. 3D-Web-GIS RFID location sensing system for construction objects.

    PubMed

    Ko, Chien-Ho

    2013-01-01

    Construction site managers could benefit from being able to visualize on-site construction objects. Radio frequency identification (RFID) technology has been shown to improve the efficiency of construction object management. The objective of this study is to develop a 3D-Web-GIS RFID location sensing system for construction objects. An RFID 3D location sensing algorithm combining Simulated Annealing (SA) and a gradient descent method is proposed to determine target object location. In the algorithm, SA is used to stabilize the search process and the gradient descent method is used to reduce errors. The locations of the analyzed objects are visualized using the 3D-Web-GIS system. A real construction site is used to validate the applicability of the proposed method, with results indicating that the proposed approach can provide faster, more accurate, and more stable 3D positioning results than other location sensing algorithms. The proposed system allows construction managers to better understand worksite status, thus enhancing managerial efficiency.

  19. The volume hologram printer to record the wavefront of a 3D object

    NASA Astrophysics Data System (ADS)

    Miyamoto, Osamu; Yamaguchi, Takeshi; Yoshikawa, Hiroshi

    2012-03-01

    A computer-generated hologram (CGH) is well-known to reconstruct 3D image truly, and several CGH printers are reported. Since those printers can only output a transmission hologram, the large-scale optical system is necessary to reconstruct the full parallax and full color image. As a method of a simple reconstruction, it is only necessary to use a volume reflection hologram. However, the making of a volume hologram needs to transfer a CGH by use of an optical system. On the other hand, there are the printers which output volume type holographic stereogram reconstructing the full parallax and full color image. However, the reconstructed image whose depth is large gets blurred due to the insufficient sampling rays of a 3D object. In this study, the authors propose the volume hologram printer to record the wavefront of a 3D object. By transferring the CGH which is displayed on the LCoS, the proposed printer can output a volume hologram. In addition, the large volume hologram can be printed by transferring plural CGH that recorded partial 3D object in turn. As a result, the printed volume hologram has been able to reconstruct a monochrome 3D image by white light, and realized the full parallax image.

  20. Higher-Order Neural Networks Applied to 2D and 3D Object Recognition

    NASA Technical Reports Server (NTRS)

    Spirkovska, Lilly; Reid, Max B.

    1994-01-01

    A Higher-Order Neural Network (HONN) can be designed to be invariant to geometric transformations such as scale, translation, and in-plane rotation. Invariances are built directly into the architecture of a HONN and do not need to be learned. Thus, for 2D object recognition, the network needs to be trained on just one view of each object class, not numerous scaled, translated, and rotated views. Because the 2D object recognition task is a component of the 3D object recognition task, built-in 2D invariance also decreases the size of the training set required for 3D object recognition. We present results for 2D object recognition both in simulation and within a robotic vision experiment and for 3D object recognition in simulation. We also compare our method to other approaches and show that HONNs have distinct advantages for position, scale, and rotation-invariant object recognition. The major drawback of HONNs is that the size of the input field is limited due to the memory required for the large number of interconnections in a fully connected network. We present partial connectivity strategies and a coarse-coding technique for overcoming this limitation and increasing the input field to that required by practical object recognition problems.

  1. Contribution of 3-D electrical resistivity tomography for landmines detection

    NASA Astrophysics Data System (ADS)

    Metwaly, M.; El-Qady, G.; Matsushima, J.; Szalai, S.; Al-Arifi, N. S. N.; Taha, A.

    2008-12-01

    Landmines are a type of inexpensive weapons widely used in the pre-conflicted areas in many countries worldwide. The two main types are the metallic and non-metallic (mostly plastic) landmines. They are most commonly investigated by magnetic, ground penetrating radar (GPR), and metal detector (MD) techniques. These geophysical techniques however have significant limitations in resolving the non-metallic landmines and wherever the host materials are conductive. In this work, the 3-D electric resistivity tomography (ERT) technique is evaluated as an alternative and/or confirmation detection system for both landmine types, which are buried in different soil conditions and at different depths. This can be achieved using the capacitive resistivity imaging system, which does not need direct contact with the ground surface. Synthetic models for each case have been introduced using metallic and non-metallic bodies buried in wet and dry environments. The inversion results using the L1 norm least-squares optimization method tend to produce robust blocky models of the landmine body. The dipole axial and the dipole equatorial arrays tend to have the most favorable geometry by applying dynamic capacitive electrode and they show significant signal strength for data sets with up to 5% noise. Increasing the burial depth relative to the electrode spacing as well as the noise percentage in the resistivity data is crucial in resolving the landmines at different environments. The landmine with dimension and burial depth of one electrode separation unit is over estimated while the spatial resolutions decrease as the burial depth and noise percentage increase.

  2. A Skeleton-Based 3D Shape Reconstruction of Free-Form Objects with Stereo Vision

    NASA Astrophysics Data System (ADS)

    Saini, Deepika; Kumar, Sanjeev

    2015-12-01

    In this paper, an efficient approach is proposed for recovering the 3D shape of a free-form object from its arbitrary pair of stereo images. In particular, the reconstruction problem is treated as the reconstruction of the skeleton and the external boundary of the object. The reconstructed skeleton is termed as the line-like representation or curve-skeleton of the 3D object. The proposed solution for object reconstruction is based on this evolved curve-skeleton. It is used as a seed for recovering shape of the 3D object, and the extracted boundary is used for terminating the growing process of the object. NURBS-skeleton is used to extract the skeleton of both views. Affine invariant property of the convex hulls is used to establish the correspondence between the skeletons and boundaries in the stereo images. In the growing process, a distance field is defined for each skeleton point as the smallest distance from that point to the boundary of the object. A sphere centered at a skeleton point of radius equal to the minimum distance to the boundary is tangential to the boundary. Filling in the spheres centered at each skeleton point reconstructs the object. Several results are presented in order to check the applicability and validity of the proposed algorithm.

  3. 2D noise propagation in 3D object position determination from a single-perspective projection

    NASA Astrophysics Data System (ADS)

    Habets, Damiaan F.; Pollmann, Steven; Holdsworth, David W.

    2002-05-01

    Image guidance during endovascular intervention is predominantly provided by two-dimensional (2D) digital radiographic systems used for vessel visualization and localization of clips and coils. This paper describes the propagation of 2D noise in the determination of three-dimensional (3D) object position from a single perspective view. In our system, a view is obtained by a digital fluoroscopic x-ray system, corrected for XRII distortions (+/- 0.035mm) and mechanical C-arm shifts (+/- 0.080mm). The tracked object contains high-contrast markers with known relative spacing, allowing for identification and centroid calculation. A least-square projection-Procrustes analysis of the 2D perspective projection is used to determine the 3D position of the object. The effect of uncertainty in 2D marker position on the precision of the 3D object localization using simulations and phantoms was investigated and a nearly linear relationship was found; however, the slope of this relationship is not unity. The slope found indicates a significant amplification of error due to the least-square solution, which is not equally distributed among the 3 major axes. In order to obtain a 3D localization error of less than +/- 1mm, the 2D localization precision must be better than +/- 0.2mm for each marker.

  4. Recognition by Humans and Pigeons of Novel Views of 3-D Objects and Their Photographs

    ERIC Educational Resources Information Center

    Friedman, Alinda; Spetch, Marcia L.; Ferrey, Anne

    2005-01-01

    Humans and pigeons were trained to discriminate between 2 views of actual 3-D objects or their photographs. They were tested on novel views that were either within the closest rotational distance between the training views (interpolated) or outside of that range (extrapolated). When training views were 60? apart, pigeons, but not humans,…

  5. Object Recognition in Flight: How Do Bees Distinguish between 3D Shapes?

    PubMed

    Werner, Annette; Stürzl, Wolfgang; Zanker, Johannes

    2016-01-01

    Honeybees (Apis mellifera) discriminate multiple object features such as colour, pattern and 2D shape, but it remains unknown whether and how bees recover three-dimensional shape. Here we show that bees can recognize objects by their three-dimensional form, whereby they employ an active strategy to uncover the depth profiles. We trained individual, free flying honeybees to collect sugar water from small three-dimensional objects made of styrofoam (sphere, cylinder, cuboids) or folded paper (convex, concave, planar) and found that bees can easily discriminate between these stimuli. We also tested possible strategies employed by the bees to uncover the depth profiles. For the card stimuli, we excluded overall shape and pictorial features (shading, texture gradients) as cues for discrimination. Lacking sufficient stereo vision, bees are known to use speed gradients in optic flow to detect edges; could the bees apply this strategy also to recover the fine details of a surface depth profile? Analysing the bees' flight tracks in front of the stimuli revealed specific combinations of flight maneuvers (lateral translations in combination with yaw rotations), which are particularly suitable to extract depth cues from motion parallax. We modelled the generated optic flow and found characteristic patterns of angular displacement corresponding to the depth profiles of our stimuli: optic flow patterns from pure translations successfully recovered depth relations from the magnitude of angular displacements, additional rotation provided robust depth information based on the direction of the displacements; thus, the bees flight maneuvers may reflect an optimized visuo-motor strategy to extract depth structure from motion signals. The robustness and simplicity of this strategy offers an efficient solution for 3D-object-recognition without stereo vision, and could be employed by other flying insects, or mobile robots. PMID:26886006

  6. Object Recognition in Flight: How Do Bees Distinguish between 3D Shapes?

    PubMed

    Werner, Annette; Stürzl, Wolfgang; Zanker, Johannes

    2016-01-01

    Honeybees (Apis mellifera) discriminate multiple object features such as colour, pattern and 2D shape, but it remains unknown whether and how bees recover three-dimensional shape. Here we show that bees can recognize objects by their three-dimensional form, whereby they employ an active strategy to uncover the depth profiles. We trained individual, free flying honeybees to collect sugar water from small three-dimensional objects made of styrofoam (sphere, cylinder, cuboids) or folded paper (convex, concave, planar) and found that bees can easily discriminate between these stimuli. We also tested possible strategies employed by the bees to uncover the depth profiles. For the card stimuli, we excluded overall shape and pictorial features (shading, texture gradients) as cues for discrimination. Lacking sufficient stereo vision, bees are known to use speed gradients in optic flow to detect edges; could the bees apply this strategy also to recover the fine details of a surface depth profile? Analysing the bees' flight tracks in front of the stimuli revealed specific combinations of flight maneuvers (lateral translations in combination with yaw rotations), which are particularly suitable to extract depth cues from motion parallax. We modelled the generated optic flow and found characteristic patterns of angular displacement corresponding to the depth profiles of our stimuli: optic flow patterns from pure translations successfully recovered depth relations from the magnitude of angular displacements, additional rotation provided robust depth information based on the direction of the displacements; thus, the bees flight maneuvers may reflect an optimized visuo-motor strategy to extract depth structure from motion signals. The robustness and simplicity of this strategy offers an efficient solution for 3D-object-recognition without stereo vision, and could be employed by other flying insects, or mobile robots.

  7. Object Recognition in Flight: How Do Bees Distinguish between 3D Shapes?

    PubMed Central

    Werner, Annette; Stürzl, Wolfgang; Zanker, Johannes

    2016-01-01

    Honeybees (Apis mellifera) discriminate multiple object features such as colour, pattern and 2D shape, but it remains unknown whether and how bees recover three-dimensional shape. Here we show that bees can recognize objects by their three-dimensional form, whereby they employ an active strategy to uncover the depth profiles. We trained individual, free flying honeybees to collect sugar water from small three-dimensional objects made of styrofoam (sphere, cylinder, cuboids) or folded paper (convex, concave, planar) and found that bees can easily discriminate between these stimuli. We also tested possible strategies employed by the bees to uncover the depth profiles. For the card stimuli, we excluded overall shape and pictorial features (shading, texture gradients) as cues for discrimination. Lacking sufficient stereo vision, bees are known to use speed gradients in optic flow to detect edges; could the bees apply this strategy also to recover the fine details of a surface depth profile? Analysing the bees’ flight tracks in front of the stimuli revealed specific combinations of flight maneuvers (lateral translations in combination with yaw rotations), which are particularly suitable to extract depth cues from motion parallax. We modelled the generated optic flow and found characteristic patterns of angular displacement corresponding to the depth profiles of our stimuli: optic flow patterns from pure translations successfully recovered depth relations from the magnitude of angular displacements, additional rotation provided robust depth information based on the direction of the displacements; thus, the bees flight maneuvers may reflect an optimized visuo-motor strategy to extract depth structure from motion signals. The robustness and simplicity of this strategy offers an efficient solution for 3D-object-recognition without stereo vision, and could be employed by other flying insects, or mobile robots. PMID:26886006

  8. Printing of metallic 3D micro-objects by laser induced forward transfer.

    PubMed

    Zenou, Michael; Kotler, Zvi

    2016-01-25

    Digital printing of 3D metal micro-structures by laser induced forward transfer under ambient conditions is reviewed. Recent progress has allowed drop on demand transfer of molten, femto-liter, metal droplets with a high jetting directionality. Such small volume droplets solidify instantly, on a nanosecond time scale, as they touch the substrate. This fast solidification limits their lateral spreading and allows the fabrication of high aspect ratio and complex 3D metal structures. Several examples of micron-scale resolution metal objects printed using this method are presented and discussed. PMID:26832524

  9. Close-Range Photogrammetric Tools for Small 3d Archeological Objects

    NASA Astrophysics Data System (ADS)

    Samaan, M.; Héno, R.; Pierrot-Deseilligny, M.

    2013-07-01

    This article will focus on the first experiments carried out for our PHD thesis, which is meant to make the new image-based methods available for archeologists. As a matter of fact, efforts need to be made to find cheap, efficient and user-friendly procedures for image acquisition, data processing and quality control. Among the numerous tasks that archeologists have to face daily is the 3D recording of very small objects. The Apero/MicMac tools were used for the georeferencing and the dense correlation procedures. Relatively standard workflows lead to depth maps, which can be represented either as 3D point clouds or shaded relief images.

  10. 3D models automatic reconstruction of selected close range objects. (Polish Title: Automatyczna rekonstrukcja modeli 3D małych obiektów bliskiego zasiegu)

    NASA Astrophysics Data System (ADS)

    Zaweiska, D.

    2013-12-01

    Reconstruction of three-dimensional, realistic models of objects from digital images has been the topic of research in many areas of science for many years. This development is stimulated by new technologies and tools, which appeared recently, such as digital photography, laser scanners, increase in the equipment efficiency and Internet. The objective of this paper is to present results of automatic modeling of selected close range objects, with the use of digital photographs acquired by the Hasselblad H4D50 camera. The author's software tool was utilized for calculations; it performs successive stages of the 3D model creation. The modeling process was presented as the complete process which starts from acquisition of images and which is completed by creation of a photorealistic 3D model in the same software environment. Experiments were performed for selected close range objects, with appropriately arranged image geometry, creating a ring around the measured object. The Area Base Matching (CC/LSM) method, the RANSAC algorithm, with the use of tensor calculus, were utilized form automatic matching of points detected with the SUSAN algorithm. Reconstruction of the surface of model generation is one of the important stages of 3D modeling. Reconstruction of precise surfaces, performed on the basis of a non-organized cloud of points, acquired from automatic processing of digital images, is a difficult task, which has not been finally solved. Creation of poly-angular models, which may meet high requirements concerning modeling and visualization is required in many applications. The polynomial method is usually the best way to precise representation of measurement results, and, at the same time, to achieving the optimum description of the surface. Three algorithm were tested: the volumetric method (VCG), the Poisson method and the Ball pivoting method. Those methods are mostly applied to modeling of uniform grids of points. Results of experiments proved that incorrect

  11. The Visual Representation of 3D Object Orientation in Parietal Cortex

    PubMed Central

    Cowan, Noah J.; Angelaki, Dora E.

    2013-01-01

    An accurate representation of three-dimensional (3D) object orientation is essential for interacting with the environment. Where and how the brain visually encodes 3D object orientation remains unknown, but prior studies suggest the caudal intraparietal area (CIP) may be involved. Here, we develop rigorous analytical methods for quantifying 3D orientation tuning curves, and use these tools to the study the neural coding of surface orientation. Specifically, we show that single neurons in area CIP of the rhesus macaque jointly encode the slant and tilt of a planar surface, and that across the population, the distribution of preferred slant-tilts is not statistically different from uniform. This suggests that all slant-tilt combinations are equally represented in area CIP. Furthermore, some CIP neurons are found to also represent the third rotational degree of freedom that determines the orientation of the image pattern on the planar surface. Together, the present results suggest that CIP is a critical neural locus for the encoding of all three rotational degrees of freedom specifying an object's 3D spatial orientation. PMID:24305830

  12. Segmentation of 3D tubular objects with adaptive front propagation and minimal tree extraction for 3D medical imaging.

    PubMed

    Cohen, Laurent D; Deschamps, Thomas

    2007-08-01

    We present a new fast approach for segmentation of thin branching structures, like vascular trees, based on Fast-Marching (FM) and Level Set (LS) methods. FM allows segmentation of tubular structures by inflating a "long balloon" from a user given single point. However, when the tubular shape is rather long, the front propagation may blow up through the boundary of the desired shape close to the starting point. Our contribution is focused on a method to propagate only the useful part of the front while freezing the rest of it. We demonstrate its ability to segment quickly and accurately tubular and tree-like structures. We also develop a useful stopping criterion for the causal front propagation. We finally derive an efficient algorithm for extracting an underlying 1D skeleton of the branching objects, with minimal path techniques. Each branch being represented by its centerline, we automatically detect the bifurcations, leading to the "Minimal Tree" representation. This so-called "Minimal Tree" is very useful for visualization and quantification of the pathologies in our anatomical data sets. We illustrate our algorithms by applying it to several arteries datasets.

  13. Segmentation of 3D tubular objects with adaptive front propagation and minimal tree extraction for 3D medical imaging.

    PubMed

    Cohen, Laurent D; Deschamps, Thomas

    2007-08-01

    We present a new fast approach for segmentation of thin branching structures, like vascular trees, based on Fast-Marching (FM) and Level Set (LS) methods. FM allows segmentation of tubular structures by inflating a "long balloon" from a user given single point. However, when the tubular shape is rather long, the front propagation may blow up through the boundary of the desired shape close to the starting point. Our contribution is focused on a method to propagate only the useful part of the front while freezing the rest of it. We demonstrate its ability to segment quickly and accurately tubular and tree-like structures. We also develop a useful stopping criterion for the causal front propagation. We finally derive an efficient algorithm for extracting an underlying 1D skeleton of the branching objects, with minimal path techniques. Each branch being represented by its centerline, we automatically detect the bifurcations, leading to the "Minimal Tree" representation. This so-called "Minimal Tree" is very useful for visualization and quantification of the pathologies in our anatomical data sets. We illustrate our algorithms by applying it to several arteries datasets. PMID:17671862

  14. Numerical Analysis of Electromagnetic Scattering from 3-D Dielectric Objects Using the Yasuura Method

    NASA Astrophysics Data System (ADS)

    Koba, Koichi; Ikuno, Hiroyoshi; Kawano, Mitsunori

    In order to calculate 3-D electromagnetic scattering problems by dielectric objects which we need to solve a big size simultaneous linear equation, we present a rapid algorithm on the Yasuura method where we accelerate the convergence rate of solution by using an array of multipoles as well as a conventional multipole. As a result, we can obtain the radar cross sections of dielectric objects in the optical wave region over a relative wide frequency range and a TDG pulse response. Furthermore, we analyze the scattering data about dielectric objects by using the pulse responses cut by an appropriate window function in the time domain and clarify the scattering processes on dielectric objects.

  15. Neural network techniques for invariant recognition and motion tracking of 3-D objects

    SciTech Connect

    Hwang, J.N.; Tseng, Y.H.

    1995-12-31

    Invariant recognition and motion tracking of 3-D objects under partial object viewing are difficult tasks. In this paper, we introduce a new neural network solution that is robust to noise corruption and partial viewing of objects. This method directly utilizes the acquired range data and requires no feature extraction. In the proposed approach, the object is first parametrically represented by a continuous distance transformation neural network (CDTNN) which is trained by the surface points of the exemplar object. When later presented with the surface points of an unknown object, this parametric representation allows the mismatch information to back-propagate through the CDTNN to gradually determine the best similarity transformation (translation and rotation) of the unknown object. The mismatch can be directly measured in the reconstructed representation domain between the model and the unknown object.

  16. a Low-Cost and Portable System for 3d Reconstruction of Texture-Less Objects

    NASA Astrophysics Data System (ADS)

    Hosseininaveh, A.; Yazdan, R.; Karami, A.; Moradi, M.; Ghorbani, F.

    2015-12-01

    The optical methods for 3D modelling of objects can be classified into two categories including image-based and range-based methods. Structure from Motion is one of the image-based methods implemented in commercial software. In this paper, a low-cost and portable system for 3D modelling of texture-less objects is proposed. This system includes a rotating table designed and developed by using a stepper motor and a very light rotation plate. The system also has eight laser light sources with very dense and strong beams which provide a relatively appropriate pattern on texture-less objects. In this system, regarding to the step of stepper motor, images are semi automatically taken by a camera. The images can be used in structure from motion procedures implemented in Agisoft software.To evaluate the performance of the system, two dark objects were used. The point clouds of these objects were obtained by spraying a light powders on the objects and exploiting a GOM laser scanner. Then these objects were placed on the proposed turntable. Several convergent images were taken from each object while the laser light sources were projecting the pattern on the objects. Afterward, the images were imported in VisualSFM as a fully automatic software package for generating an accurate and complete point cloud. Finally, the obtained point clouds were compared to the point clouds generated by the GOM laser scanner. The results showed the ability of the proposed system to produce a complete 3D model from texture-less objects.

  17. Registration of untypical 3D objects in Polish cadastre - do we need 3D cadastre? / Rejestracja nietypowych obiektów 3D w polskim katastrze - czy istnieje potrzeba wdrożenia katastru 3D?

    NASA Astrophysics Data System (ADS)

    Marcin, Karabin

    2012-11-01

    Polish cadastral system consists of two registers: cadastre and land register. The cadastre register data on cadastral objects (land, buildings and premises) in particular location (in a two-dimensional coordinate system) and their attributes as well as data about the owners. The land register contains data concerned ownerships and other rights to the property. Registration of a land parcel without spatial objects located on the surface is not problematic. Registration of buildings and premises in typical cases is not a problem either. The situation becomes more complicated in cases of multiple use of space above the parcel and with more complex construction of the buildings. The paper presents rules concerning the registration of various untypical 3D objects located within the city of Warsaw. The analysis of the data concerning those objects registered in the cadastre and land register is presented in the paper. And this is the next part of the author's detailed research. The aim of this paper is to answer the question if we really need 3D cadastre in Poland. Polski system katastralny składa się z dwóch rejestrów: ewidencji gruntów i budynków (katastru nieruchomosci) oraz ksiąg wieczystych. W ewidencji gruntów i budynków (katastrze nieruchomości) rejestrowane są dane o położeniu (w dwuwymiarowym układzie współrzędnych), atrybuty oraz dane o właścicielach obiektów katastralnych (działek, budynków i lokali), w księgach wieczystych oprócz danych właścicielskich, inne prawa do nieruchomości. Rejestracja działki bez obiektów przestrzennych położonych na jej powierzchni nie stanowi problemu. Także rejestracja budynków i lokali w typowych przypadkach nie stanowi trudności. Sytuacja staje się bardziej skomplikowana w przypadku wielokrotnego użytkowania przestrzeni powyzej lub poniżej powierzchni działki oraz w przypadku budynków o złożonej konstrukcji. W artykule przedstawiono zasady związane z rejestracją nietypowych obiektów 3

  18. Learning the 3-D structure of objects from 2-D views depends on shape, not format

    PubMed Central

    Tian, Moqian; Yamins, Daniel; Grill-Spector, Kalanit

    2016-01-01

    Humans can learn to recognize new objects just from observing example views. However, it is unknown what structural information enables this learning. To address this question, we manipulated the amount of structural information given to subjects during unsupervised learning by varying the format of the trained views. We then tested how format affected participants' ability to discriminate similar objects across views that were rotated 90° apart. We found that, after training, participants' performance increased and generalized to new views in the same format. Surprisingly, the improvement was similar across line drawings, shape from shading, and shape from shading + stereo even though the latter two formats provide richer depth information compared to line drawings. In contrast, participants' improvement was significantly lower when training used silhouettes, suggesting that silhouettes do not have enough information to generate a robust 3-D structure. To test whether the learned object representations were format-specific or format-invariant, we examined if learning novel objects from example views transfers across formats. We found that learning objects from example line drawings transferred to shape from shading and vice versa. These results have important implications for theories of object recognition because they suggest that (a) learning the 3-D structure of objects does not require rich structural cues during training as long as shape information of internal and external features is provided and (b) learning generates shape-based object representations independent of the training format. PMID:27153196

  19. Minimal camera networks for 3D image based modeling of cultural heritage objects.

    PubMed

    Alsadik, Bashar; Gerke, Markus; Vosselman, George; Daham, Afrah; Jasim, Luma

    2014-03-25

    3D modeling of cultural heritage objects like artifacts, statues and buildings is nowadays an important tool for virtual museums, preservation and restoration. In this paper, we introduce a method to automatically design a minimal imaging network for the 3D modeling of cultural heritage objects. This becomes important for reducing the image capture time and processing when documenting large and complex sites. Moreover, such a minimal camera network design is desirable for imaging non-digitally documented artifacts in museums and other archeological sites to avoid disturbing the visitors for a long time and/or moving delicate precious objects to complete the documentation task. The developed method is tested on the Iraqi famous statue "Lamassu". Lamassu is a human-headed winged bull of over 4.25 m in height from the era of Ashurnasirpal II (883-859 BC). Close-range photogrammetry is used for the 3D modeling task where a dense ordered imaging network of 45 high resolution images were captured around Lamassu with an object sample distance of 1 mm. These images constitute a dense network and the aim of our study was to apply our method to reduce the number of images for the 3D modeling and at the same time preserve pre-defined point accuracy. Temporary control points were fixed evenly on the body of Lamassu and measured by using a total station for the external validation and scaling purpose. Two network filtering methods are implemented and three different software packages are used to investigate the efficiency of the image orientation and modeling of the statue in the filtered (reduced) image networks. Internal and external validation results prove that minimal image networks can provide highly accurate records and efficiency in terms of visualization, completeness, processing time (>60% reduction) and the final accuracy of 1 mm.

  20. Minimal Camera Networks for 3D Image Based Modeling of Cultural Heritage Objects

    PubMed Central

    Alsadik, Bashar; Gerke, Markus; Vosselman, George; Daham, Afrah; Jasim, Luma

    2014-01-01

    3D modeling of cultural heritage objects like artifacts, statues and buildings is nowadays an important tool for virtual museums, preservation and restoration. In this paper, we introduce a method to automatically design a minimal imaging network for the 3D modeling of cultural heritage objects. This becomes important for reducing the image capture time and processing when documenting large and complex sites. Moreover, such a minimal camera network design is desirable for imaging non-digitally documented artifacts in museums and other archeological sites to avoid disturbing the visitors for a long time and/or moving delicate precious objects to complete the documentation task. The developed method is tested on the Iraqi famous statue “Lamassu”. Lamassu is a human-headed winged bull of over 4.25 m in height from the era of Ashurnasirpal II (883–859 BC). Close-range photogrammetry is used for the 3D modeling task where a dense ordered imaging network of 45 high resolution images were captured around Lamassu with an object sample distance of 1 mm. These images constitute a dense network and the aim of our study was to apply our method to reduce the number of images for the 3D modeling and at the same time preserve pre-defined point accuracy. Temporary control points were fixed evenly on the body of Lamassu and measured by using a total station for the external validation and scaling purpose. Two network filtering methods are implemented and three different software packages are used to investigate the efficiency of the image orientation and modeling of the statue in the filtered (reduced) image networks. Internal and external validation results prove that minimal image networks can provide highly accurate records and efficiency in terms of visualization, completeness, processing time (>60% reduction) and the final accuracy of 1 mm. PMID:24670718

  1. 3D change detection at street level using mobile laser scanning point clouds and terrestrial images

    NASA Astrophysics Data System (ADS)

    Qin, Rongjun; Gruen, Armin

    2014-04-01

    Automatic change detection and geo-database updating in the urban environment are difficult tasks. There has been much research on detecting changes with satellite and aerial images, but studies have rarely been performed at the street level, which is complex in its 3D geometry. Contemporary geo-databases include 3D street-level objects, which demand frequent data updating. Terrestrial images provides rich texture information for change detection, but the change detection with terrestrial images from different epochs sometimes faces problems with illumination changes, perspective distortions and unreliable 3D geometry caused by the lack of performance of automatic image matchers, while mobile laser scanning (MLS) data acquired from different epochs provides accurate 3D geometry for change detection, but is very expensive for periodical acquisition. This paper proposes a new method for change detection at street level by using combination of MLS point clouds and terrestrial images: the accurate but expensive MLS data acquired from an early epoch serves as the reference, and terrestrial images or photogrammetric images captured from an image-based mobile mapping system (MMS) at a later epoch are used to detect the geometrical changes between different epochs. The method will automatically mark the possible changes in each view, which provides a cost-efficient method for frequent data updating. The methodology is divided into several steps. In the first step, the point clouds are recorded by the MLS system and processed, with data cleaned and classified by semi-automatic means. In the second step, terrestrial images or mobile mapping images at a later epoch are taken and registered to the point cloud, and then point clouds are projected on each image by a weighted window based z-buffering method for view dependent 2D triangulation. In the next step, stereo pairs of the terrestrial images are rectified and re-projected between each other to check the geometrical

  2. Rapid object indexing using locality sensitive hashing and joint 3D-signature space estimation.

    PubMed

    Matei, Bogdan; Shan, Ying; Sawhney, Harpreet S; Tan, Yi; Kumar, Rakesh; Huber, Daniel; Hebert, Martial

    2006-07-01

    We propose a new method for rapid 3D object indexing that combines feature-based methods with coarse alignment-based matching techniques. Our approach achieves a sublinear complexity on the number of models, maintaining at the same time a high degree of performance for real 3D sensed data that is acquired in largely uncontrolled settings. The key component of our method is to first index surface descriptors computed at salient locations from the scene into the whole model database using the Locality Sensitive Hashing (LSH), a probabilistic approximate nearest neighbor method. Progressively complex geometric constraints are subsequently enforced to further prune the initial candidates and eliminate false correspondences due to inaccuracies in the surface descriptors and the errors of the LSH algorithm. The indexed models are selected based on the MAP rule using posterior probability of the models estimated in the joint 3D-signature space. Experiments with real 3D data employing a large database of vehicles, most of them very similar in shape, containing 1,000,000 features from more than 365 models demonstrate a high degree of performance in the presence of occlusion and obscuration, unmodeled vehicle interiors and part articulations, with an average processing time between 50 and 100 seconds per query.

  3. Determining the 3-D structure and motion of objects using a scanning laser range sensor

    NASA Technical Reports Server (NTRS)

    Nandhakumar, N.; Smith, Philip W.

    1993-01-01

    In order for the EVAHR robot to autonomously track and grasp objects, its vision system must be able to determine the 3-D structure and motion of an object from a sequence of sensory images. This task is accomplished by the use of a laser radar range sensor which provides dense range maps of the scene. Unfortunately, the currently available laser radar range cameras use a sequential scanning approach which complicates image analysis. Although many algorithms have been developed for recognizing objects from range images, none are suited for use with single beam, scanning, time-of-flight sensors because all previous algorithms assume instantaneous acquisition of the entire image. This assumption is invalid since the EVAHR robot is equipped with a sequential scanning laser range sensor. If an object is moving while being imaged by the device, the apparent structure of the object can be significantly distorted due to the significant non-zero delay time between sampling each image pixel. If an estimate of the motion of the object can be determined, this distortion can be eliminated; but, this leads to the motion-structure paradox - most existing algorithms for 3-D motion estimation use the structure of objects to parameterize their motions. The goal of this research is to design a rigid-body motion recovery technique which overcomes this limitation. The method being developed is an iterative, linear, feature-based approach which uses the non-zero image acquisition time constraint to accurately recover the motion parameters from the distorted structure of the 3-D range maps. Once the motion parameters are determined, the structural distortion in the range images is corrected.

  4. New 3D thermal evolution model for icy bodies application to trans-Neptunian objects

    NASA Astrophysics Data System (ADS)

    Guilbert-Lepoutre, A.; Lasue, J.; Federico, C.; Coradini, A.; Orosei, R.; Rosenberg, E. D.

    2011-05-01

    Context. Thermal evolution models have been developed over the years to investigate the evolution of thermal properties based on the transfer of heat fluxes or transport of gas through a porous matrix, among others. Applications of such models to trans-Neptunian objects (TNOs) and Centaurs has shown that these bodies could be strongly differentiated from the point of view of chemistry (i.e. loss of most volatile ices), as well as from physics (e.g. melting of water ice), resulting in stratified internal structures with differentiated cores and potential pristine material close to the surface. In this context, some observational results, such as the detection of crystalline water ice or volatiles, remain puzzling. Aims: In this paper, we would like to present a new fully three-dimensional thermal evolution model. With this model, we aim to improve determination of the temperature distribution inside icy bodies such as TNOs by accounting for lateral heat fluxes, which have been proven to be important for accurate simulations. We also would like to be able to account for heterogeneous boundary conditions at the surface through various albedo properties, for example, that might induce different local temperature distributions. Methods: In a departure from published modeling approaches, the heat diffusion problem and its boundary conditions are represented in terms of real spherical harmonics, increasing the numerical efficiency by roughly an order of magnitude. We then compare this new model and another 3D model recently published to illustrate the advantages and limits of the new model. We try to put some constraints on the presence of crystalline water ice at the surface of TNOs. Results: The results obtained with this new model are in excellent agreement with results obtained by different groups with various models. Small TNOs could remain primitive unless they are formed quickly (less than 2 Myr) or are debris from the disruption of larger bodies. We find that, for

  5. Determining canonical views of 3D object using minimum description length criterion and compressive sensing method

    NASA Astrophysics Data System (ADS)

    Chen, Ping-Feng; Krim, Hamid

    2008-02-01

    In this paper, we propose using two methods to determine the canonical views of 3D objects: minimum description length (MDL) criterion and compressive sensing method. MDL criterion searches for the description length that achieves the balance between model accuracy and parsimony. It takes the form of the sum of a likelihood and a penalizing term, where the likelihood is in favor of model accuracy such that more views assists the description of an object, while the second term penalizes lengthy description to prevent overfitting of the model. In order to devise the likelihood term, we propose a model to represent a 3D object as the weighted sum of multiple range images, which is used in the second method to determine the canonical views as well. In compressive sensing method, an intelligent way of parsimoniously sampling an object is presented. We make direct inference from Donoho1 and Candes'2 work, and adapt it to our model. Each range image is viewed as a projection, or a sample, of a 3D model, and by using compressive sensing theory, we are able to reconstruct the object with an overwhelming probability by scarcely sensing the object in a random manner. Compressive sensing is different from traditional compressing method in the sense that the former compress things in the sampling stage while the later collects a large number of samples and then compressing mechanism is carried out thereafter. Compressive sensing scheme is particularly useful when the number of sensors are limited or the sampling machinery cost much resource or time.

  6. Computer-aided detection of clustered microcalcifications in digital breast tomosynthesis: A 3D approach

    PubMed Central

    Sahiner, Berkman; Chan, Heang-Ping; Hadjiiski, Lubomir M.; Helvie, Mark A.; Wei, Jun; Zhou, Chuan; Lu, Yao

    2012-01-01

    Purpose: To design a computer-aided detection (CADe) system for clustered microcalcifications in reconstructed digital breast tomosynthesis (DBT) volumes and to perform a preliminary evaluation of the CADe system. Methods: IRB approval and informed consent were obtained in this study. A data set of two-view DBT of 72 breasts containing microcalcification clusters was collected from 72 subjects who were scheduled to undergo breast biopsy. Based on tissue sampling results, 17 cases had breast cancer and 55 were benign. A separate data set of two-view DBT of 38 breasts free of clustered microcalcifications from 38 subjects was collected to independently estimate the number of false-positives (FPs) generated by the CADe system. A radiologist experienced in breast imaging marked the biopsied cluster of microcalcifications with a 3D bounding box using all available clinical and imaging information. A CADe system was designed to detect microcalcification clusters in the reconstructed volume. The system consisted of prescreening, clustering, and false-positive reduction stages. In the prescreening stage, the conspicuity of microcalcification-like objects was increased by an enhancement-modulated 3D calcification response function. An iterative thresholding and 3D object growing method was used to detect cluster seed objects, which were used as potential centers of microcalcification clusters. In the cluster detection stage, microcalcification candidates were identified using a second iterative thresholding procedure, which was applied to the signal-to-noise ratio (SNR) enhanced image voxels with a positive calcification response. Starting with each cluster seed object as the initial cluster center, a dynamic clustering algorithm formed a cluster candidate by including microcalcification candidates within a 3D neighborhood of the cluster seed object that satisfied the clustering criteria. The number, size, and SNR of the microcalcifications in a cluster candidate and the

  7. Detectability limitations with 3-D point reconstruction algorithms using digital radiography

    SciTech Connect

    Lindgren, Erik

    2015-03-31

    The estimated impact of pores in clusters on component fatigue will be highly conservative when based on 2-D rather than 3-D pore positions. To 3-D position and size defects using digital radiography and 3-D point reconstruction algorithms in general require a lower inspection time and in some cases work better with planar geometries than X-ray computed tomography. However, the increase in prior assumptions about the object and the defects will increase the intrinsic uncertainty in the resulting nondestructive evaluation output. In this paper this uncertainty arising when detecting pore defect clusters with point reconstruction algorithms is quantified using simulations. The simulation model is compared to and mapped to experimental data. The main issue with the uncertainty is the possible masking (detectability zero) of smaller defects around some other slightly larger defect. In addition, the uncertainty is explored in connection to the expected effects on the component fatigue life and for different amount of prior object-defect assumptions made.

  8. Comparison of simulated and experimental 3D laser images using a GmAPD array: application to long range detection

    NASA Astrophysics Data System (ADS)

    Coyac, Antoine; Riviere, Nicolas; Hespel, Laurent; Briottet, Xavier

    2016-05-01

    In this paper, we show the feasibility and the benefit to use a Geiger-mode Avalanche Photo-Diode (GmAPD) array for long range detection, up to several kilometers. A simulation of a Geiger detection sensor is described, which is a part of our end-to-end laser simulator, to generate simulated 3D laser images from synthetic scenes. Resulting 3D point clouds have been compared to experimental acquisitions, performed with our GmAPD 3D camera on similar scenarios. An operational case of long range detection is presented: a copper cable outstretched above the ground, 1 kilometer away the experimental system and with a horizontal line-of-sight (LOS). The detection of such a small object from long distance observation strongly suggests that GmAPD focal plane arrays could be easily used for real-time 3D mapping or surveillance applications from airborne platforms, with good spatial and temporal resolutions.

  9. Study of improved ray tracing parallel algorithm for CGH of 3D objects on GPU

    NASA Astrophysics Data System (ADS)

    Cong, Bin; Jiang, Xiaoyu; Yao, Jun; Zhao, Kai

    2014-11-01

    An improved parallel algorithm for holograms of three-dimensional objects was presented. According to the physical characteristics and mathematical properties of the original ray tracing algorithm for computer generated holograms (CGH), using transform approximation and numerical analysis methods, we extract parts of ray tracing algorithm which satisfy parallelization features and implement them on graphics processing unit (GPU). Meanwhile, through proper design of parallel numerical procedure, we did parallel programming to the two-dimensional slices of three-dimensional object with CUDA. According to the experiments, an effective method of dealing with occlusion problem in ray tracing is proposed, as well as generating the holograms of 3D objects with additive property. Our results indicate that the improved algorithm can effectively shorten the computing time. Due to the different sizes of spatial object points and hologram pixels, the speed has increased 20 to 70 times comparing with original ray tracing algorithm.

  10. The 3-D alignment of objects in dynamic PET scans using filtered sinusoidal trajectories of sinogram

    NASA Astrophysics Data System (ADS)

    Kostopoulos, Aristotelis E.; Happonen, Antti P.; Ruotsalainen, Ulla

    2006-12-01

    In this study, our goal is to employ a novel 3-D alignment method for dynamic positron emission tomography (PET) scans. Because the acquired data (i.e. sinograms) often contain noise considerably, filtering of the data prior to the alignment presumably improves the final results. In this study, we utilized a novel 3-D stackgram domain approach. In the stackgram domain, the signals along the sinusoidal trajectory signals of the sinogram can be processed separately. In this work, we performed angular stackgram domain filtering by employing well known 1-D filters: the Gaussian low-pass filter and the median filter. In addition, we employed two wavelet de-noising techniques. After filtering we performed alignment of objects in the stackgram domain. The local alignment technique we used is based on similarity comparisons between locus vectors (i.e. the signals along the sinusoidal trajectories of the sinogram) in a 3-D neighborhood of sequences of the stackgrams. Aligned stackgrams can be transformed back to sinograms (Method 1), or alternatively directly to filtered back-projected images (Method 2). In order to evaluate the alignment process, simulated data with different kinds of additive noises were used. The results indicated that the filtering prior to the alignment can be important concerning the accuracy.

  11. Fast 3-D Tomographic Microwave Imaging for Breast Cancer Detection

    PubMed Central

    Meaney, Paul M.; Kaufman, Peter A.; diFlorio-Alexander, Roberta M.; Paulsen, Keith D.

    2013-01-01

    Microwave breast imaging (using electromagnetic waves of frequencies around 1 GHz) has mostly remained at the research level for the past decade, gaining little clinical acceptance. The major hurdles limiting patient use are both at the hardware level (challenges in collecting accurate and noncorrupted data) and software level (often plagued by unrealistic reconstruction times in the tens of hours). In this paper we report improvements that address both issues. First, the hardware is able to measure signals down to levels compatible with sub-centimeter image resolution while keeping an exam time under 2 min. Second, the software overcomes the enormous time burden and produces similarly accurate images in less than 20 min. The combination of the new hardware and software allows us to produce and report here the first clinical 3-D microwave tomographic images of the breast. Two clinical examples are selected out of 400+ exams conducted at the Dartmouth Hitchcock Medical Center (Lebanon, NH). The first example demonstrates the potential usefulness of our system for breast cancer screening while the second example focuses on therapy monitoring. PMID:22562726

  12. Prototyping a Sensor Enabled 3d Citymodel on Geospatial Managed Objects

    NASA Astrophysics Data System (ADS)

    Kjems, E.; Kolář, J.

    2013-09-01

    One of the major development efforts within the GI Science domain are pointing at sensor based information and the usage of real time information coming from geographic referenced features in general. At the same time 3D City models are mostly justified as being objects for visualization purposes rather than constituting the foundation of a geographic data representation of the world. The combination of 3D city models and real time information based systems though can provide a whole new setup for data fusion within an urban environment and provide time critical information preserving our limited resources in the most sustainable way. Using 3D models with consistent object definitions give us the possibility to avoid troublesome abstractions of reality, and design even complex urban systems fusing information from various sources of data. These systems are difficult to design with the traditional software development approach based on major software packages and traditional data exchange. The data stream is varying from urban domain to urban domain and from system to system why it is almost impossible to design a complete system taking care of all thinkable instances now and in the future within one constraint software design complex. On several occasions we have been advocating for a new end advanced formulation of real world features using the concept of Geospatial Managed Objects (GMO). This paper presents the outcome of the InfraWorld project, a 4 million Euro project financed primarily by the Norwegian Research Council where the concept of GMO's have been applied in various situations on various running platforms of an urban system. The paper will be focusing on user experiences and interfaces rather then core technical and developmental issues. The project was primarily focusing on prototyping rather than realistic implementations although the results concerning applicability are quite clear.

  13. Efficient Use of Video for 3d Modelling of Cultural Heritage Objects

    NASA Astrophysics Data System (ADS)

    Alsadik, B.; Gerke, M.; Vosselman, G.

    2015-03-01

    Currently, there is a rapid development in the techniques of the automated image based modelling (IBM), especially in advanced structure-from-motion (SFM) and dense image matching methods, and camera technology. One possibility is to use video imaging to create 3D reality based models of cultural heritage architectures and monuments. Practically, video imaging is much easier to apply when compared to still image shooting in IBM techniques because the latter needs a thorough planning and proficiency. However, one is faced with mainly three problems when video image sequences are used for highly detailed modelling and dimensional survey of cultural heritage objects. These problems are: the low resolution of video images, the need to process a large number of short baseline video images and blur effects due to camera shake on a significant number of images. In this research, the feasibility of using video images for efficient 3D modelling is investigated. A method is developed to find the minimal significant number of video images in terms of object coverage and blur effect. This reduction in video images is convenient to decrease the processing time and to create a reliable textured 3D model compared with models produced by still imaging. Two experiments for modelling a building and a monument are tested using a video image resolution of 1920×1080 pixels. Internal and external validations of the produced models are applied to find out the final predicted accuracy and the model level of details. Related to the object complexity and video imaging resolution, the tests show an achievable average accuracy between 1 - 5 cm when using video imaging, which is suitable for visualization, virtual museums and low detailed documentation.

  14. Microchip-based electrochemical detection using a 3-D printed wall-jet electrode device.

    PubMed

    Munshi, Akash S; Martin, R Scott

    2016-02-01

    Three dimensional (3-D) printing technology has evolved dramatically in the last few years, offering the capability of printing objects with a variety of materials. Printing microfluidic devices using this technology offers various advantages such as ease and uniformity of fabrication, file sharing between laboratories, and increased device-to-device reproducibility. One unique aspect of this technology, when used with electrochemical detection, is the ability to produce a microfluidic device as one unit while also allowing the reuse of the device and electrode for multiple analyses. Here we present an alternate electrode configuration for microfluidic devices, a wall-jet electrode (WJE) approach, created by 3-D printing. Using microchip-based flow injection analysis, we compared the WJE design with the conventionally used thin-layer electrode (TLE) design. It was found that the optimized WJE system enhances analytical performance (as compared to the TLE design), with improvements in sensitivity and the limit of detection. Experiments were conducted using two working electrodes - 500 μm platinum and 1 mm glassy carbon. Using the 500 μm platinum electrode the calibration sensitivity was 16 times higher for the WJE device (as compared to the TLE design). In addition, use of the 1 mm glassy carbon electrode led to limit of detection of 500 nM for catechol, as compared to 6 μM for the TLE device. Finally, to demonstrate the versatility and applicability of the 3-D printed WJE approach, the device was used as an inexpensive electrochemical detector for HPLC. The number of theoretical plates was comparable to the use of commercially available UV and MS detectors, with the WJE device being inexpensive to utilize. These results show that 3-D-printing can be a powerful tool to fabricate reusable and integrated microfluidic detectors in configurations that are not easily achieved with more traditional lithographic methods. PMID:26649363

  15. Combining laser scan and photogrammetry for 3D object modeling using a single digital camera

    NASA Astrophysics Data System (ADS)

    Xiong, Hanwei; Zhang, Hong; Zhang, Xiangwei

    2009-07-01

    In the fields of industrial design, artistic design and heritage conservation, physical objects are usually digitalized by reverse engineering through some 3D scanning methods. Laser scan and photogrammetry are two main methods to be used. For laser scan, a video camera and a laser source are necessary, and for photogrammetry, a digital still camera with high resolution pixels is indispensable. In some 3D modeling tasks, two methods are often integrated to get satisfactory results. Although many research works have been done on how to combine the results of the two methods, no work has been reported to design an integrated device at low cost. In this paper, a new 3D scan system combining laser scan and photogrammetry using a single consumer digital camera is proposed. Nowadays there are many consumer digital cameras, such as Canon EOS 5D Mark II, they usually have features of more than 10M pixels still photo recording and full 1080p HD movie recording, so a integrated scan system can be designed using such a camera. A square plate glued with coded marks is used to place the 3d objects, and two straight wood rulers also glued with coded marks can be laid on the plate freely. In the photogrammetry module, the coded marks on the plate make up a world coordinate and can be used as control network to calibrate the camera, and the planes of two rulers can also be determined. The feature points of the object and the rough volume representation from the silhouettes can be obtained in this module. In the laser scan module, a hand-held line laser is used to scan the object, and the two straight rulers are used as reference planes to determine the position of the laser. The laser scan results in dense points cloud which can be aligned together automatically through calibrated camera parameters. The final complete digital model is obtained through a new a patchwise energy functional method by fusion of the feature points, rough volume and the dense points cloud. The design

  16. Measuring the 3D shape of high temperature objects using blue sinusoidal structured light

    NASA Astrophysics Data System (ADS)

    Zhao, Xianling; Liu, Jiansheng; Zhang, Huayu; Wu, Yingchun

    2015-12-01

    The visible light radiated by some high temperature objects (less than 1200 °C) almost lies in the red and infrared waves. It will interfere with structured light projected on a forging surface if phase measurement profilometry (PMP) is used to measure the shapes of objects. In order to obtain a clear deformed pattern image, a 3D measurement method based on blue sinusoidal structured light is proposed in this present work. Moreover, a method for filtering deformed pattern images is presented for correction of the unwrapping phase. Blue sinusoidal phase-shifting fringe pattern images are projected on the surface by a digital light processing (DLP) projector, and then the deformed patterns are captured by a 3-CCD camera. The deformed pattern images are separated into R, G and B color components by the software. The B color images filtered by a low-pass filter are used to calculate the fringe order. Consequently, the 3D shape of a high temperature object is obtained by the unwrapping phase and the calibration parameter matrixes of the DLP projector and 3-CCD camera. The experimental results show that the unwrapping phase is completely corrected with the filtering method by removing the high frequency noise from the first harmonic of the B color images. The measurement system can complete the measurement in a few seconds with a relative error of less than 1 : 1000.

  17. FMRI Reveals a Dissociation between Grasping and Perceiving the Size of Real 3D Objects

    PubMed Central

    Cavina-Pratesi, Cristiana; Goodale, Melvyn A.; Culham, Jody C.

    2007-01-01

    Background Almost 15 years after its formulation, evidence for the neuro-functional dissociation between a dorsal action stream and a ventral perception stream in the human cerebral cortex is still based largely on neuropsychological case studies. To date, there is no unequivocal evidence for separate visual computations of object features for performance of goal-directed actions versus perceptual tasks in the neurologically intact human brain. We used functional magnetic resonance imaging to test explicitly whether or not brain areas mediating size computation for grasping are distinct from those mediating size computation for perception. Methodology/Principal Findings Subjects were presented with the same real graspable 3D objects and were required to perform a number of different tasks: grasping, reaching, size discrimination, pattern discrimination or passive viewing. As in prior studies, the anterior intraparietal area (AIP) in the dorsal stream was more active during grasping, when object size was relevant for planning the grasp, than during reaching, when object properties were irrelevant for movement planning (grasping>reaching). Activity in AIP showed no modulation, however, when size was computed in the context of a purely perceptual task (size = pattern discrimination). Conversely, the lateral occipital (LO) cortex in the ventral stream was modulated when size was computed for perception (size>pattern discrimination) but not for action (grasping = reaching). Conclusions/Significance While areas in both the dorsal and ventral streams responded to the simple presentation of 3D objects (passive viewing), these areas were differentially activated depending on whether the task was grasping or perceptual discrimination, respectively. The demonstration of dual coding of an object for the purposes of action on the one hand and perception on the other in the same healthy brains offers a substantial contribution to the current debate about the nature of

  18. High resolution 3D insider detection and tracking.

    SciTech Connect

    Nelson, Cynthia Lee

    2003-09-01

    Vulnerability analysis studies show that one of the worst threats against a facility is that of an active insider during an emergency evacuation. When a criticality or other emergency alarm occurs, employees immediately proceed along evacuation routes to designated areas. Procedures are then implemented to account for all material, classified parts, etc. The 3-Dimensional Video Motion Detection (3DVMD) technology could be used to detect and track possible insider activities during alarm situations, as just described, as well as during normal operating conditions. The 3DVMD technology uses multiple cameras to create 3-dimensional detection volumes or zones. Movement throughout detection zones is tracked and high-level information, such as the number of people and their direction of motion, is extracted. In the described alarm scenario, deviances of evacuation procedures taken by an individual could be immediately detected and relayed to a central alarm station. The insider could be tracked and any protected items removed from the area could be flagged. The 3DVMD technology could also be used to monitor such items as machines that are used to build classified parts. During an alarm, detections could be made if items were removed from the machine. Overall, the use of 3DVMD technology during emergency evacuations would help to prevent the loss of classified items and would speed recovery from emergency situations. Further security could also be added by analyzing tracked behavior (motion) as it corresponds to predicted behavior, e.g., behavior corresponding with the execution of required procedures. This information would be valuable for detecting a possible insider not only during emergency situations, but also during times of normal operation.

  19. Detecting method of subjects' 3D positions and experimental advanced camera control system

    NASA Astrophysics Data System (ADS)

    Kato, Daiichiro; Abe, Kazuo; Ishikawa, Akio; Yamada, Mitsuho; Suzuki, Takahito; Kuwashima, Shigesumi

    1997-04-01

    Steady progress is being made in the development of an intelligent robot camera capable of automatically shooting pictures with a powerful sense of reality or tracking objects whose shooting requires advanced techniques. Currently, only experienced broadcasting cameramen can provide these pictures.TO develop an intelligent robot camera with these abilities, we need to clearly understand how a broadcasting cameraman assesses his shooting situation and how his camera is moved during shooting. We use a real- time analyzer to study a cameraman's work and his gaze movements at studios and during sports broadcasts. This time, we have developed a detecting method of subjects' 3D positions and an experimental camera control system to help us further understand the movements required for an intelligent robot camera. The features are as follows: (1) Two sensor cameras shoot a moving subject and detect colors, producing its 3D coordinates. (2) Capable of driving a camera based on camera movement data obtained by a real-time analyzer. 'Moving shoot' is the name we have given to the object position detection technology on which this system is based. We used it in a soccer game, producing computer graphics showing how players moved. These results will also be reported.

  20. Detecting falls with 3D range camera in ambient assisted living applications: a preliminary study.

    PubMed

    Leone, Alessandro; Diraco, Giovanni; Siciliano, Pietro

    2011-07-01

    In recent years several world-wide ambient assisted living (AAL) programs have been activated in order to improve the quality of life of older people, and to strengthen the industrial base through the use of information and communication technologies. An important issue is extending the time that older people can live in their home environment, by increasing their autonomy and helping them to carry out activities of daily living (ADLs). Research in the automatic detection of falls has received a lot of attention, with the object of enhancing safety, emergency response and independence of the elderly, at the same time comparing the social and economic costs related to fall accidents. In this work, an algorithmic framework to detect falls by using a 3D time-of-flight vision technology is presented. The proposed system presented complementary working requirements with respect to traditional worn and non-worn fall-detection devices. The vision system used a state-of-the-art 3D range camera for elderly movement measurement and detection of critical events, such as falls. The depth images provided by the active sensor allowed reliable segmentation and tracking of elderly movements, by using well-established imaging methods. Moreover, the range camera provided 3D metric information in all illumination conditions (even night vision), allowing the overcoming of some typical limitations of passive vision (shadows, camouflage, occlusions, brightness fluctuations, perspective ambiguity). A self-calibration algorithm guarantees different setup mountings of the range camera by non-technical users. A large dataset of simulated fall events and ADLs in real dwellings was collected and the proposed fall-detection system demonstrated high performance in terms of sensitivity and specificity.

  1. Perception of physical stability and center of mass of 3-D objects

    PubMed Central

    Cholewiak, Steven A.; Fleming, Roland W.; Singh, Manish

    2015-01-01

    Humans can judge from vision alone whether an object is physically stable or not. Such judgments allow observers to predict the physical behavior of objects, and hence to guide their motor actions. We investigated the visual estimation of physical stability of 3-D objects (shown in stereoscopically viewed rendered scenes) and how it relates to visual estimates of their center of mass (COM). In Experiment 1, observers viewed an object near the edge of a table and adjusted its tilt to the perceived critical angle, i.e., the tilt angle at which the object was seen as equally likely to fall or return to its upright stable position. In Experiment 2, observers visually localized the COM of the same set of objects. In both experiments, observers' settings were compared to physical predictions based on the objects' geometry. In both tasks, deviations from physical predictions were, on average, relatively small. More detailed analyses of individual observers' settings in the two tasks, however, revealed mutual inconsistencies between observers' critical-angle and COM settings. The results suggest that observers did not use their COM estimates in a physically correct manner when making visual judgments of physical stability. PMID:25761331

  2. Perception of physical stability and center of mass of 3-D objects.

    PubMed

    Cholewiak, Steven A; Fleming, Roland W; Singh, Manish

    2015-02-10

    Humans can judge from vision alone whether an object is physically stable or not. Such judgments allow observers to predict the physical behavior of objects, and hence to guide their motor actions. We investigated the visual estimation of physical stability of 3-D objects (shown in stereoscopically viewed rendered scenes) and how it relates to visual estimates of their center of mass (COM). In Experiment 1, observers viewed an object near the edge of a table and adjusted its tilt to the perceived critical angle, i.e., the tilt angle at which the object was seen as equally likely to fall or return to its upright stable position. In Experiment 2, observers visually localized the COM of the same set of objects. In both experiments, observers' settings were compared to physical predictions based on the objects' geometry. In both tasks, deviations from physical predictions were, on average, relatively small. More detailed analyses of individual observers' settings in the two tasks, however, revealed mutual inconsistencies between observers' critical-angle and COM settings. The results suggest that observers did not use their COM estimates in a physically correct manner when making visual judgments of physical stability.

  3. Fruit bruise detection based on 3D meshes and machine learning technologies

    NASA Astrophysics Data System (ADS)

    Hu, Zilong; Tang, Jinshan; Zhang, Ping

    2016-05-01

    This paper studies bruise detection in apples using 3-D imaging. Bruise detection based on 3-D imaging overcomes many limitations of bruise detection based on 2-D imaging, such as low accuracy, sensitive to light condition, and so on. In this paper, apple bruise detection is divided into two parts: feature extraction and classification. For feature extraction, we use a framework that can directly extract local binary patterns from mesh data. For classification, we studies support vector machine. Bruise detection using 3-D imaging is compared with bruise detection using 2-D imaging. 10-fold cross validation is used to evaluate the performance of the two systems. Experimental results show that bruise detection using 3-D imaging can achieve better classification accuracy than bruise detection based on 2-D imaging.

  4. 3D Imaging with a Single-Aperture 3-mm Objective Lens: Concept, Fabrication and Test

    NASA Technical Reports Server (NTRS)

    Korniski, Ron; Bae, Sam Y.; Shearn, Mike; Manohara, Harish; Shahinian, Hrayr

    2011-01-01

    There are many advantages to minimally invasive surgery (MIS). An endoscope is the optical system of choice by the surgeon for MIS. The smaller the incision or opening made to perform the surgery, the smaller the optical system needed. For minimally invasive neurological and skull base surgeries the openings are typically 10-mm in diameter (dime sized) or less. The largest outside diameter (OD) endoscope used is 4mm. A significant drawback to endoscopic MIS is that it only provides a monocular view of the surgical site thereby lacking depth information for the surgeon. A stereo view would provide the surgeon instantaneous depth information of the surroundings within the field of view, a significant advantage especially during brain surgery. Providing 3D imaging in an endoscopic objective lens system presents significant challenges because of the tight packaging constraints. This paper presents a promising new technique for endoscopic 3D imaging that uses a single lens system with complementary multi-bandpass filters (CMBFs), and describes the proof-of-concept demonstrations performed to date validating the technique. These demonstrations of the technique have utilized many commercial off-the-shelf (COTS) components including the ones used in the endoscope objective.

  5. An optimal sensing strategy for recognition and localization of 3-D natural quadric objects

    NASA Technical Reports Server (NTRS)

    Lee, Sukhan; Hahn, Hernsoo

    1991-01-01

    An optimal sensing strategy for an optical proximity sensor system engaged in the recognition and localization of 3-D natural quadric objects is presented. The optimal sensing strategy consists of the selection of an optimal beam orientation and the determination of an optimal probing plane that compose an optimal data collection operation known as an optimal probing. The decision of an optimal probing is based on the measure of discrimination power of a cluster of surfaces on a multiple interpretation image (MII), where the measure of discrimination power is defined in terms of a utility function computing the expected number of interpretations that can be pruned out by a probing. An object representation suitable for active sensing based on a surface description vector (SDV) distribution graph and hierarchical tables is presented. Experimental results are shown.

  6. Real-scale 3D models of the scoliotic spine from biplanar radiography without calibration objects.

    PubMed

    Moura, Daniel C; Barbosa, Jorge G

    2014-10-01

    This paper presents a new method for modelling the spines of subjects and making accurate 3D measurements using standard radiologic systems without requiring calibration objects. The method makes use of the focal distance and statistical models for estimating the geometrical parameters of the system. A dataset of 32 subjects was used to assess this method. The results show small errors for the main clinical indices, such as an RMS error of 0.49° for the Cobb angle, 0.50° for kyphosis, 0.38° for lordosis, and 2.62mm for the spinal length. This method is the first to achieve this level of accuracy without requiring the use of calibration objects when acquiring radiographs. We conclude that the proposed method allows for the evaluation of scoliosis with a much simpler setup than currently available methods. PMID:24908193

  7. 3D-FFT for Signature Detection in LWIR Images

    SciTech Connect

    Medvick, Patricia A.; Lind, Michael A.; Mackey, Patrick S.; Nuffer, Lisa L.; Foote, Harlan P.

    2007-11-20

    Improvements in analysis detection exploitation are possible by applying whitened matched filtering within the Fourier domain to hyperspectral data cubes. We describe an implementation of a Three Dimensional Fast Fourier Transform Whitened Matched Filter (3DFFTMF) approach and, using several example sets of Long Wave Infra Red (LWIR) data cubes, compare the results with those from standard Whitened Matched Filter (WMF) techniques. Since the variability in shape of gaseous plumes precludes the use of spatial conformation in the matched filtering, the 3DFFTMF results were similar to those of two other WMF methods. Including a spatial low-pass filter within the Fourier space can improve signal to noise ratios and therefore improve detection limit by facilitating the mitigation of high frequency clutter. The improvement only occurs if the low-pass filter diameter is smaller than the plume diameter.

  8. Efficient 3D modeling of buildings using a priori geometric object information

    NASA Astrophysics Data System (ADS)

    Van den Heuvel, Frank A.; Vosselman, George

    1997-07-01

    The subject of this paper is the research that aims at efficiency improvement of acquisition of 3D building models from digital images for Computer Aided Architectural Design (CAAD). The results do not only apply to CAAD, but to all applications where polyhedral objects are involved. The research is concentrated on the integration of a priori geometric object information in the modeling process. Parallelism and perpendicularity are examples of the a priori information to be used. This information leads to geometric constraints in the mathematical model. This model can be formulated using condition equations with observations only. The advantage is that the adjustment does not include object parameters and the geometric constraints can be incorporated in the model sequentially. As with the use of observation equations statistical testing can be applied to verify the constraints. For the initial values of orientation parameters of the images we use a direct solution based on a priori object information as well. For this method only two sets of (coplanar) parallel lines in object space are required. The paper concentrates on the mathematical model with image lines as the main type of observations. Advantages as well as disadvantages of a mathematical model with only condition equations are discussed. The parametrization of the object model plays a major role in this discussion.

  9. Active learning in the lecture theatre using 3D printed objects.

    PubMed

    Smith, David P

    2016-01-01

    The ability to conceptualize 3D shapes is central to understanding biological processes. The concept that the structure of a biological molecule leads to function is a core principle of the biochemical field. Visualisation of biological molecules often involves vocal explanations or the use of two dimensional slides and video presentations. A deeper understanding of these molecules can however be obtained by the handling of objects. 3D printed biological molecules can be used as active learning tools to stimulate engagement in large group lectures. These models can be used to build upon initial core knowledge which can be delivered in either a flipped form or a more didactic manner. Within the teaching session the students are able to learn by handling, rotating and viewing the objects to gain an appreciation, for example, of an enzyme's active site or the difference between the major and minor groove of DNA. Models and other artefacts can be handled in small groups within a lecture theatre and act as a focal point to generate conversation. Through the approach presented here core knowledge is first established and then supplemented with high level problem solving through a "Think-Pair-Share" cooperative learning strategy. The teaching delivery was adjusted based around experiential learning activities by moving the object from mental cognition and into the physical environment. This approach led to students being able to better visualise biological molecules and a positive engagement in the lecture. The use of objects in teaching allows the lecturer to create interactive sessions that both challenge and enable the student. PMID:27366318

  10. Active learning in the lecture theatre using 3D printed objects

    PubMed Central

    Smith, David P.

    2016-01-01

    The ability to conceptualize 3D shapes is central to understanding biological processes. The concept that the structure of a biological molecule leads to function is a core principle of the biochemical field. Visualisation of biological molecules often involves vocal explanations or the use of two dimensional slides and video presentations. A deeper understanding of these molecules can however be obtained by the handling of objects. 3D printed biological molecules can be used as active learning tools to stimulate engagement in large group lectures. These models can be used to build upon initial core knowledge which can be delivered in either a flipped form or a more didactic manner. Within the teaching session the students are able to learn by handling, rotating and viewing the objects to gain an appreciation, for example, of an enzyme’s active site or the difference between the major and minor groove of DNA. Models and other artefacts can be handled in small groups within a lecture theatre and act as a focal point to generate conversation. Through the approach presented here core knowledge is first established and then supplemented with high level problem solving through a "Think-Pair-Share" cooperative learning strategy. The teaching delivery was adjusted based around experiential learning activities by moving the object from mental cognition and into the physical environment. This approach led to students being able to better visualise biological molecules and a positive engagement in the lecture. The use of objects in teaching allows the lecturer to create interactive sessions that both challenge and enable the student. PMID:27366318

  11. Digital breast tomosynthesis: computerized detection of microcalcifications in reconstructed breast volume using a 3D approach

    NASA Astrophysics Data System (ADS)

    Chan, Heang-Ping; Sahiner, Berkman; Wei, Jun; Hadjiiski, Lubomir M.; Zhou, Chuan; Helvie, Mark A.

    2010-03-01

    We are developing a computer-aided detection (CAD) system for clustered microcalcifications in digital breast tomosynthesis (DBT). In this preliminary study, we investigated the approach of detecting microcalcifications in the tomosynthesized volume. The DBT volume is first enhanced by 3D multi-scale filtering and analysis of the eigenvalues of Hessian matrices with a calcification response function and signal-to-noise ratio enhancement filtering. Potential signal sites are identified in the enhanced volume and local analysis is performed to further characterize each object. A 3D dynamic clustering procedure is designed to locate potential clusters using hierarchical criteria. We collected a pilot data set of two-view DBT mammograms of 39 breasts containing microcalcification clusters (17 malignant, 22 benign) with IRB approval. A total of 74 clusters were identified by an experienced radiologist in the 78 DBT views. Our prototype CAD system achieved view-based sensitivity of 90% and 80% at an average FP rate of 7.3 and 2.0 clusters per volume, respectively. At the same levels of case-based sensitivity, the FP rates were 3.6 and 1.3 clusters per volume, respectively. For the subset of malignant clusters, the view-based detection sensitivity was 94% and 82% at an average FP rate of 6.0 and 1.5 FP clusters per volume, respectively. At the same levels of case-based sensitivity, the FP rates were 1.2 and 0.9 clusters per volume, respectively. This study demonstrated that computerized microcalcification detection in 3D is a promising approach to the development of a CAD system for DBT. Study is underway to further improve the computer-vision methods and to optimize the processing parameters using a larger data set.

  12. Eccentricity in Images of Circular and Spherical Targets and its Impact to 3D Object Reconstruction

    NASA Astrophysics Data System (ADS)

    Luhmann, T.

    2014-06-01

    This paper discusses a feature of projective geometry which causes eccentricity in the image measurement of circular and spherical targets. While it is commonly known that flat circular targets can have a significant displacement of the elliptical image centre with respect to the true imaged circle centre, it can also be shown that the a similar effect exists for spherical targets. Both types of targets are imaged with an elliptical contour. As a result, if measurement methods based on ellipses are used to detect the target (e.g. best-fit ellipses), the calculated ellipse centre does not correspond to the desired target centre in 3D space. This paper firstly discusses the use and measurement of circular and spherical targets. It then describes the geometrical projection model in order to demonstrate the eccentricity in image space. Based on numerical simulations, the eccentricity in the image is further quantified and investigated. Finally, the resulting effect in 3D space is estimated for stereo and multi-image intersections. It can be stated that the eccentricity is larger than usually assumed, and must be compensated for high-accuracy applications. Spherical targets do not show better results than circular targets. The paper is an updated version of Luhmann (2014) new experimental investigations on the effect of length measurement errors.

  13. A Novel 3D Building Damage Detection Method Using Multiple Overlapping UAV Images

    NASA Astrophysics Data System (ADS)

    Sui, H.; Tu, J.; Song, Z.; Chen, G.; Li, Q.

    2014-09-01

    In this paper, a novel approach is presented that applies multiple overlapping UAV imagesto building damage detection. Traditional building damage detection method focus on 2D changes detection (i.e., those only in image appearance), whereas the 2D information delivered by the images is often not sufficient and accurate when dealing with building damage detection. Therefore the detection of building damage in 3D feature of scenes is desired. The key idea of 3D building damage detection is the 3D Change Detection using 3D point cloud obtained from aerial images through Structure from motion (SFM) techniques. The approach of building damage detection discussed in this paper not only uses the height changes of 3D feature of scene but also utilizes the image's shape and texture feature. Therefore, this method fully combines the 2D and 3D information of the real world to detect the building damage. The results, tested through field study, demonstrate that this method is feasible and effective in building damage detection. It has also shown that the proposed method is easily applicable and suited well for rapid damage assessment after natural disasters.

  14. Automatic detection of karstic sinkholes in seismic 3D images using circular Hough transform

    NASA Astrophysics Data System (ADS)

    Heydari Parchkoohi, Mostafa; Keshavarz Farajkhah, Nasser; Salimi Delshad, Meysam

    2015-10-01

    More than 30% of hydrocarbon reservoirs are reported in carbonates that mostly include evidence of fractures and karstification. Generally, the detection of karstic sinkholes prognosticate good quality hydrocarbon reservoirs where looser sediments fill the holes penetrating hard limestone and the overburden pressure on infill sediments is mostly tolerated by their sturdier surrounding structure. They are also useful for the detection of erosional surfaces in seismic stratigraphic studies and imply possible relative sea level fall at the time of establishment. Karstic sinkholes are identified straightforwardly by using seismic geometric attributes (e.g. coherency, curvature) in which lateral variations are much more emphasized with respect to the original 3D seismic image. Then, seismic interpreters rely on their visual skills and experience in detecting roughly round objects in seismic attribute maps. In this paper, we introduce an image processing workflow to enhance selective edges in seismic attribute volumes stemming from karstic sinkholes and finally locate them in a high quality 3D seismic image by using circular Hough transform. Afterwards, we present a case study from an on-shore oilfield in southwest Iran, in which the proposed algorithm is applied and karstic sinkholes are traced.

  15. Interferometric synthetic aperture radar detection and estimation based 3D image reconstruction

    NASA Astrophysics Data System (ADS)

    Austin, Christian D.; Moses, Randolph L.

    2006-05-01

    This paper explores three-dimensional (3D) interferometric synthetic aperture radar (IFSAR) image reconstruction when multiple scattering centers and noise are present in a radar resolution cell. We introduce an IFSAR scattering model that accounts for both multiple scattering centers and noise. The problem of 3D image reconstruction is then posed as a multiple hypothesis detection and estimation problem; resolution cells containing a single scattering center are detected and the 3D location of these cells' pixels are estimated; all other pixels are rejected from the image. Detection and estimation statistics are derived using the multiple scattering center IFSAR model. A 3D image reconstruction algorithm using these statistics is then presented, and its performance is evaluated for a 3D reconstruction of a backhoe from noisy IFSAR data.

  16. Towards fully automatic object detection and segmentation

    NASA Astrophysics Data System (ADS)

    Schramm, Hauke; Ecabert, Olivier; Peters, Jochen; Philomin, Vasanth; Weese, Juergen

    2006-03-01

    An automatic procedure for detecting and segmenting anatomical objects in 3-D images is necessary for achieving a high level of automation in many medical applications. Since today's segmentation techniques typically rely on user input for initialization, they do not allow for a fully automatic workflow. In this work, the generalized Hough transform is used for detecting anatomical objects with well defined shape in 3-D medical images. This well-known technique has frequently been used for object detection in 2-D images and is known to be robust and reliable. However, its computational and memory requirements are generally huge, especially in case of considering 3-D images and various free transformation parameters. Our approach limits the complexity of the generalized Hough transform to a reasonable amount by (1) using object prior knowledge during the preprocessing in order to suppress unlikely regions in the image, (2) restricting the flexibility of the applied transformation to only scaling and translation, and (3) using a simple shape model which does not cover any inter-individual shape variability. Despite these limitations, the approach is demonstrated to allow for a coarse 3-D delineation of the femur, vertebra and heart in a number of experiments. Additionally it is shown that the quality of the object localization is in nearly all cases sufficient to initialize a successful segmentation using shape constrained deformable models.

  17. Robust acoustic object detection

    NASA Astrophysics Data System (ADS)

    Amit, Yali; Koloydenko, Alexey; Niyogi, Partha

    2005-10-01

    We consider a novel approach to the problem of detecting phonological objects like phonemes, syllables, or words, directly from the speech signal. We begin by defining local features in the time-frequency plane with built in robustness to intensity variations and time warping. Global templates of phonological objects correspond to the coincidence in time and frequency of patterns of the local features. These global templates are constructed by using the statistics of the local features in a principled way. The templates have clear phonetic interpretability, are easily adaptable, have built in invariances, and display considerable robustness in the face of additive noise and clutter from competing speakers. We provide a detailed evaluation of the performance of some diphone detectors and a word detector based on this approach. We also perform some phonetic classification experiments based on the edge-based features suggested here.

  18. Automatic 3D pulmonary nodule detection in CT images: A survey.

    PubMed

    Valente, Igor Rafael S; Cortez, Paulo César; Neto, Edson Cavalcanti; Soares, José Marques; de Albuquerque, Victor Hugo C; Tavares, João Manuel R S

    2016-02-01

    This work presents a systematic review of techniques for the 3D automatic detection of pulmonary nodules in computerized-tomography (CT) images. Its main goals are to analyze the latest technology being used for the development of computational diagnostic tools to assist in the acquisition, storage and, mainly, processing and analysis of the biomedical data. Also, this work identifies the progress made, so far, evaluates the challenges to be overcome and provides an analysis of future prospects. As far as the authors know, this is the first time that a review is devoted exclusively to automated 3D techniques for the detection of pulmonary nodules from lung CT images, which makes this work of noteworthy value. The research covered the published works in the Web of Science, PubMed, Science Direct and IEEEXplore up to December 2014. Each work found that referred to automated 3D segmentation of the lungs was individually analyzed to identify its objective, methodology and results. Based on the analysis of the selected works, several studies were seen to be useful for the construction of medical diagnostic aid tools. However, there are certain aspects that still require attention such as increasing algorithm sensitivity, reducing the number of false positives, improving and optimizing the algorithm detection of different kinds of nodules with different sizes and shapes and, finally, the ability to integrate with the Electronic Medical Record Systems and Picture Archiving and Communication Systems. Based on this analysis, we can say that further research is needed to develop current techniques and that new algorithms are needed to overcome the identified drawbacks. PMID:26652979

  19. Aging preserves the ability to perceive 3D object shape from static but not deforming boundary contours.

    PubMed

    Norman, J Farley; Bartholomew, Ashley N; Burton, Cory L

    2008-09-01

    A single experiment investigated how younger (aged 18-32 years) and older (aged 62-82 years) observers perceive 3D object shape from deforming and static boundary contours. On any given trial, observers were shown two smoothly-curved objects, similar to water-smoothed granite rocks, and were required to judge whether they possessed the "same" or "different" shape. The objects presented during the "different" trials produced differently-shaped boundary contours. The objects presented during the "same" trials also produced different boundary contours, because one of the objects was always rotated in depth relative to the other by 5, 25, or 45 degrees. Each observer participated in 12 experimental conditions formed by the combination of 2 motion types (deforming vs. static boundary contours), 2 surface types (objects depicted as silhouettes or with texture and Lambertian shading), and 3 angular offsets (5, 25, and 45 degrees). When there was no motion (static silhouettes or stationary objects presented with shading and texture), the older observers performed as well as the younger observers. In the moving object conditions with shading and texture, the older observers' performance was facilitated by the motion, but the amount of this facilitation was reduced relative to that exhibited by the younger observers. In contrast, the older observers obtained no benefit in performance at all from the deforming (i.e., moving) silhouettes. The reduced ability of older observers to perceive 3D shape from motion is probably due to a low-level deterioration in the ability to detect and discriminate motion itself.

  20. Performance analysis of different surface reconstruction algorithms for 3D reconstruction of outdoor objects from their digital images.

    PubMed

    Maiti, Abhik; Chakravarty, Debashish

    2016-01-01

    3D reconstruction of geo-objects from their digital images is a time-efficient and convenient way of studying the structural features of the object being modelled. This paper presents a 3D reconstruction methodology which can be used to generate photo-realistic 3D watertight surface of different irregular shaped objects, from digital image sequences of the objects. The 3D reconstruction approach described here is robust, simplistic and can be readily used in reconstructing watertight 3D surface of any object from its digital image sequence. Here, digital images of different objects are used to build sparse, followed by dense 3D point clouds of the objects. These image-obtained point clouds are then used for generation of photo-realistic 3D surfaces, using different surface reconstruction algorithms such as Poisson reconstruction and Ball-pivoting algorithm. Different control parameters of these algorithms are identified, which affect the quality and computation time of the reconstructed 3D surface. The effects of these control parameters in generation of 3D surface from point clouds of different density are studied. It is shown that the reconstructed surface quality of Poisson reconstruction depends on Samples per node (SN) significantly, greater SN values resulting in better quality surfaces. Also, the quality of the 3D surface generated using Ball-Pivoting algorithm is found to be highly depend upon Clustering radius and Angle threshold values. The results obtained from this study give the readers of the article a valuable insight into the effects of different control parameters on determining the reconstructed surface quality. PMID:27386376

  1. Performance analysis of different surface reconstruction algorithms for 3D reconstruction of outdoor objects from their digital images.

    PubMed

    Maiti, Abhik; Chakravarty, Debashish

    2016-01-01

    3D reconstruction of geo-objects from their digital images is a time-efficient and convenient way of studying the structural features of the object being modelled. This paper presents a 3D reconstruction methodology which can be used to generate photo-realistic 3D watertight surface of different irregular shaped objects, from digital image sequences of the objects. The 3D reconstruction approach described here is robust, simplistic and can be readily used in reconstructing watertight 3D surface of any object from its digital image sequence. Here, digital images of different objects are used to build sparse, followed by dense 3D point clouds of the objects. These image-obtained point clouds are then used for generation of photo-realistic 3D surfaces, using different surface reconstruction algorithms such as Poisson reconstruction and Ball-pivoting algorithm. Different control parameters of these algorithms are identified, which affect the quality and computation time of the reconstructed 3D surface. The effects of these control parameters in generation of 3D surface from point clouds of different density are studied. It is shown that the reconstructed surface quality of Poisson reconstruction depends on Samples per node (SN) significantly, greater SN values resulting in better quality surfaces. Also, the quality of the 3D surface generated using Ball-Pivoting algorithm is found to be highly depend upon Clustering radius and Angle threshold values. The results obtained from this study give the readers of the article a valuable insight into the effects of different control parameters on determining the reconstructed surface quality.

  2. 3D change detection in staggered voxels model for robotic sensing and navigation

    NASA Astrophysics Data System (ADS)

    Liu, Ruixu; Hampshire, Brandon; Asari, Vijayan K.

    2016-05-01

    3D scene change detection is a challenging problem in robotic sensing and navigation. There are several unpredictable aspects in performing scene change detection. A change detection method which can support various applications in varying environmental conditions is proposed. Point cloud models are acquired from a RGB-D sensor, which provides the required color and depth information. Change detection is performed on robot view point cloud model. A bilateral filter smooths the surface and fills the holes as well as keeps the edge details on depth image. Registration of the point cloud model is implemented by using Random Sample Consensus (RANSAC) algorithm. It uses surface normal as the previous stage for the ground and wall estimate. After preprocessing the data, we create a point voxel model which defines voxel as surface or free space. Then we create a color model which defines each voxel that has a color by the mean of all points' color value in this voxel. The preliminary change detection is detected by XOR subtract on the point voxel model. Next, the eight neighbors for this center voxel are defined. If they are neither all `changed' voxels nor all `no changed' voxels, a histogram of location and hue channel color is estimated. The experimental evaluations performed to evaluate the capability of our algorithm show promising results for novel change detection that indicate all the changing objects with very limited false alarm rate.

  3. A neural-network appearance-based 3-D object recognition using independent component analysis.

    PubMed

    Sahambi, H S; Khorasani, K

    2003-01-01

    This paper presents results on appearance-based three-dimensional (3-D) object recognition (3DOR) accomplished by utilizing a neural-network architecture developed based on independent component analysis (ICA). ICA has already been applied for face recognition in the literature with encouraging results. In this paper, we are exploring the possibility of utilizing the redundant information in the visual data to enhance the view based object recognition. The underlying premise here is that since ICA uses high-order statistics, it should in principle outperform principle component analysis (PCA), which does not utilize statistics higher than two, in the recognition task. Two databases of images captured by a CCD camera are used. It is demonstrated that ICA did perform better than PCA in one of the databases, but interestingly its performance was no better than PCA in the case of the second database. Thus, suggesting that the use of ICA may not necessarily always give better results than PCA, and that the application of ICA is highly data dependent. Various factors affecting the differences in the recognition performance using both methods are also discussed. PMID:18237997

  4. 3D Visual Data-Driven Spatiotemporal Deformations for Non-Rigid Object Grasping Using Robot Hands.

    PubMed

    Mateo, Carlos M; Gil, Pablo; Torres, Fernando

    2016-05-05

    Sensing techniques are important for solving problems of uncertainty inherent to intelligent grasping tasks. The main goal here is to present a visual sensing system based on range imaging technology for robot manipulation of non-rigid objects. Our proposal provides a suitable visual perception system of complex grasping tasks to support a robot controller when other sensor systems, such as tactile and force, are not able to obtain useful data relevant to the grasping manipulation task. In particular, a new visual approach based on RGBD data was implemented to help a robot controller carry out intelligent manipulation tasks with flexible objects. The proposed method supervises the interaction between the grasped object and the robot hand in order to avoid poor contact between the fingertips and an object when there is neither force nor pressure data. This new approach is also used to measure changes to the shape of an object's surfaces and so allows us to find deformations caused by inappropriate pressure being applied by the hand's fingers. Test was carried out for grasping tasks involving several flexible household objects with a multi-fingered robot hand working in real time. Our approach generates pulses from the deformation detection method and sends an event message to the robot controller when surface deformation is detected. In comparison with other methods, the obtained results reveal that our visual pipeline does not use deformations models of objects and materials, as well as the approach works well both planar and 3D household objects in real time. In addition, our method does not depend on the pose of the robot hand because the location of the reference system is computed from a recognition process of a pattern located place at the robot forearm. The presented experiments demonstrate that the proposed method accomplishes a good monitoring of grasping task with several objects and different grasping configurations in indoor environments.

  5. Software for Building Models of 3D Objects via the Internet

    NASA Technical Reports Server (NTRS)

    Schramer, Tim; Jensen, Jeff

    2003-01-01

    The Virtual EDF Builder (where EDF signifies Electronic Development Fixture) is a computer program that facilitates the use of the Internet for building and displaying digital models of three-dimensional (3D) objects that ordinarily comprise assemblies of solid models created previously by use of computer-aided-design (CAD) programs. The Virtual EDF Builder resides on a Unix-based server computer. It is used in conjunction with a commercially available Web-based plug-in viewer program that runs on a client computer. The Virtual EDF Builder acts as a translator between the viewer program and a database stored on the server. The translation function includes the provision of uniform resource locator (URL) links to other Web-based computer systems and databases. The Virtual EDF builder can be used in two ways: (1) If the client computer is Unix-based, then it can assemble a model locally; the computational load is transferred from the server to the client computer. (2) Alternatively, the server can be made to build the model, in which case the server bears the computational load and the results are downloaded to the client computer or workstation upon completion.

  6. 3D lidar imaging for detecting and understanding plant responses and canopy structure.

    PubMed

    Omasa, Kenji; Hosoi, Fumiki; Konishi, Atsumi

    2007-01-01

    Understanding and diagnosing plant responses to stress will benefit greatly from three-dimensional (3D) measurement and analysis of plant properties because plant responses are strongly related to their 3D structures. Light detection and ranging (lidar) has recently emerged as a powerful tool for direct 3D measurement of plant structure. Here the use of 3D lidar imaging to estimate plant properties such as canopy height, canopy structure, carbon stock, and species is demonstrated, and plant growth and shape responses are assessed by reviewing the development of lidar systems and their applications from the leaf level to canopy remote sensing. In addition, the recent creation of accurate 3D lidar images combined with natural colour, chlorophyll fluorescence, photochemical reflectance index, and leaf temperature images is demonstrated, thereby providing information on responses of pigments, photosynthesis, transpiration, stomatal opening, and shape to environmental stresses; these data can be integrated with 3D images of the plants using computer graphics techniques. Future lidar applications that provide more accurate dynamic estimation of various plant properties should improve our understanding of plant responses to stress and of interactions between plants and their environment. Moreover, combining 3D lidar with other passive and active imaging techniques will potentially improve the accuracy of airborne and satellite remote sensing, and make it possible to analyse 3D information on ecophysiological responses and levels of various substances in agricultural and ecological applications and in observations of the global biosphere. PMID:17030540

  7. 3D Visual Data-Driven Spatiotemporal Deformations for Non-Rigid Object Grasping Using Robot Hands

    PubMed Central

    Mateo, Carlos M.; Gil, Pablo; Torres, Fernando

    2016-01-01

    Sensing techniques are important for solving problems of uncertainty inherent to intelligent grasping tasks. The main goal here is to present a visual sensing system based on range imaging technology for robot manipulation of non-rigid objects. Our proposal provides a suitable visual perception system of complex grasping tasks to support a robot controller when other sensor systems, such as tactile and force, are not able to obtain useful data relevant to the grasping manipulation task. In particular, a new visual approach based on RGBD data was implemented to help a robot controller carry out intelligent manipulation tasks with flexible objects. The proposed method supervises the interaction between the grasped object and the robot hand in order to avoid poor contact between the fingertips and an object when there is neither force nor pressure data. This new approach is also used to measure changes to the shape of an object’s surfaces and so allows us to find deformations caused by inappropriate pressure being applied by the hand’s fingers. Test was carried out for grasping tasks involving several flexible household objects with a multi-fingered robot hand working in real time. Our approach generates pulses from the deformation detection method and sends an event message to the robot controller when surface deformation is detected. In comparison with other methods, the obtained results reveal that our visual pipeline does not use deformations models of objects and materials, as well as the approach works well both planar and 3D household objects in real time. In addition, our method does not depend on the pose of the robot hand because the location of the reference system is computed from a recognition process of a pattern located place at the robot forearm. The presented experiments demonstrate that the proposed method accomplishes a good monitoring of grasping task with several objects and different grasping configurations in indoor environments. PMID

  8. Regularization design in penalized maximum-likelihood image reconstruction for lesion detection in 3D PET

    NASA Astrophysics Data System (ADS)

    Yang, Li; Zhou, Jian; Ferrero, Andrea; Badawi, Ramsey D.; Qi, Jinyi

    2014-01-01

    Detecting cancerous lesions is a major clinical application in emission tomography. In previous work, we have studied penalized maximum-likelihood (PML) image reconstruction for the detection task and proposed a method to design a shift-invariant quadratic penalty function to maximize detectability of a lesion at a known location in a two dimensional image. Here we extend the regularization design to maximize detectability of lesions at unknown locations in fully 3D PET. We used a multiview channelized Hotelling observer (mvCHO) to assess the lesion detectability in 3D images to mimic the condition where a human observer examines three orthogonal views of a 3D image for lesion detection. We derived simplified theoretical expressions that allow fast prediction of the detectability of a 3D lesion. The theoretical results were used to design the regularization in PML reconstruction to improve lesion detectability. We conducted computer-based Monte Carlo simulations to compare the optimized penalty with the conventional penalty for detecting lesions of various sizes. Only true coincidence events were simulated. Lesion detectability was also assessed by two human observers, whose performances agree well with that of the mvCHO. Both the numerical observer and human observer results showed a statistically significant improvement in lesion detection by using the proposed penalty function compared to using the conventional penalty function.

  9. A multi-objective optimization framework to model 3D river and landscape evolution processes

    NASA Astrophysics Data System (ADS)

    Bizzi, Simone; Castelletti, Andrea; Cominola, Andrea; Mason, Emanuele; Paik, Kyungrock

    2013-04-01

    Water and sediment interactions shape hillslopes, regulate soil erosion and sedimentation, and organize river networks. Landscape evolution and river organization occur at various spatial and temporal scale and the understanding and modelling of them is highly complex. The idea of a least action principle governing river networks evolution has been proposed many times as a simpler approach among the ones existing in the literature. These theories assume that river networks, as observed in nature, self-organize and act on soil transportation in order to satisfy a particular "optimality" criterion. Accordingly, river and landscape weathering can be simulated by solving an optimization problem, where the choice of the criterion to be optimized becomes the initial assumption. The comparison between natural river networks and optimized ones verifies the correctness of this initial assumption. Yet, various criteria have been proposed in literature and there is no consensus on which is better able to explain river network features observed in nature like network branching and river bed profile: each one is able to reproduce some river features through simplified modelling of the natural processes, but it fails to characterize the whole complexity (3D and its dynamic) of the natural processes. Some of the criteria formulated in the literature partly conflict: the reason is that their formulation rely on mathematical and theoretical simplifications of the natural system that are suitable for specific spatial and temporal scale but fails to represent the whole processes characterizing landscape evolution. In an attempt to address some of these scientific questions, we tested the suitability of using a multi-objective optimization framework to describe river and landscape evolution in a 3D spatial domain. A synthetic landscape is used to this purpose. Multiple, alternative river network evolutions, corresponding to as many tradeoffs between the different and partly

  10. Ionized Outflows in 3-D Insights from Herbig-Haro Objects and Applications to Nearby AGN

    NASA Technical Reports Server (NTRS)

    Cecil, Gerald

    1999-01-01

    HST shows that the gas distributions of these objects are complex and clump at the limit of resolution. HST spectra have lumpy emission-line profiles, indicating unresolved sub-structure. The advantages of 3D over slits on gas so distributed are: robust flux estimates of various dynamical systems projected along lines of sight, sensitivity to fainter spectral lines that are physical diagnostics (reddening-gas density, T, excitation mechanisms, abundances), and improved prospects for recovery of unobserved dimensions of phase-space. These advantages al- low more confident modeling for more profound inquiry into underlying dynamics. The main complication is the effort required to link multi- frequency datasets that optimally track the energy flow through various phases of the ISM. This tedium has limited the number of objects that have been thoroughly analyzed to the a priori most spectacular systems. For HHO'S, proper-motions constrain the ambient B-field, shock velocity, gas abundances, mass-loss rates, source duty-cycle, and tie-ins with molecular flows. If the shock speed, hence ionization fraction, is indeed small then the ionized gas is a significant part of the flow energetics. For AGN'S, nuclear beaming is a source of ionization ambiguity. Establishing the energetics of the outflow is critical to determining how the accretion disk loses its energy. CXO will provide new constraints (especially spectral) on AGN outflows, and STIS UV-spectroscopy is also constraining cloud properties (although limited by extinction). HHO's show some of the things that we will find around AGN'S. I illustrate these points with results from ground-based and HST programs being pursued with collaborators.

  11. Laser Transfer of Metals and Metal Alloys for Digital Microfabrication of 3D Objects.

    PubMed

    Zenou, Michael; Sa'ar, Amir; Kotler, Zvi

    2015-09-01

    3D copper logos printed on epoxy glass laminates are demonstrated. The structures are printed using laser transfer of molten metal microdroplets. The example in the image shows letters of 50 µm width, with each letter being taller than the last, from a height of 40 µm ('s') to 190 µm ('l'). The scanning microscopy image is taken at a tilt, and the topographic image was taken using interferometric 3D microscopy, to show the effective control of this technique. PMID:25966320

  12. True-3D accentuating of grids and streets in urban topographic maps enhances human object location memory.

    PubMed

    Edler, Dennis; Bestgen, Anne-Kathrin; Kuchinke, Lars; Dickmann, Frank

    2015-01-01

    Cognitive representations of learned map information are subject to systematic distortion errors. Map elements that divide a map surface into regions, such as content-related linear symbols (e.g. streets, rivers, railway systems) or additional artificial layers (coordinate grids), provide an orientation pattern that can help users to reduce distortions in their mental representations. In recent years, the television industry has started to establish True-3D (autostereoscopic) displays as mass media. These modern displays make it possible to watch dynamic and static images including depth illusions without additional devices, such as 3D glasses. In these images, visual details can be distributed over different positions along the depth axis. Some empirical studies of vision research provided first evidence that 3D stereoscopic content attracts higher attention and is processed faster. So far, the impact of True-3D accentuating has not yet been explored concerning spatial memory tasks and cartography. This paper reports the results of two empirical studies that focus on investigations whether True-3D accentuating of artificial, regular overlaying line features (i.e. grids) and content-related, irregular line features (i.e. highways and main streets) in official urban topographic maps (scale 1/10,000) further improves human object location memory performance. The memory performance is measured as both the percentage of correctly recalled object locations (hit rate) and the mean distances of correctly recalled objects (spatial accuracy). It is shown that the True-3D accentuating of grids (depth offset: 5 cm) significantly enhances the spatial accuracy of recalled map object locations, whereas the True-3D emphasis of streets significantly improves the hit rate of recalled map object locations. These results show the potential of True-3D displays for an improvement of the cognitive representation of learned cartographic information.

  13. Error analysis and system implementation for structured light stereo vision 3D geometric detection in large scale condition

    NASA Astrophysics Data System (ADS)

    Qi, Li; Zhang, Xuping; Wang, Jiaqi; Zhang, Yixin; Wang, Shun; Zhu, Fan

    2012-11-01

    Stereo vision based 3D metrology technique is an effective approach for relatively large scale object's 3D geometric detection. In this paper, we present a specified image capture system, which implements LVDS interface embedded CMOS sensor and CAN bus to ensure synchronous trigger and exposure. We made an error analysis for structured light vision measurement in large scale condition, based on which we built and tested the system prototype both indoor and outfield. The result shows that the system is very suitable for large scale metrology applications.

  14. The 3D Hough Transform for plane detection in point clouds: A review and a new accumulator design

    NASA Astrophysics Data System (ADS)

    Borrmann, Dorit; Elseberg, Jan; Lingemann, Kai; Nüchter, Andreas

    2011-03-01

    The Hough Transform is a well-known method for detecting parameterized objects. It is the de facto standard for detecting lines and circles in 2-dimensional data sets. For 3D it has attained little attention so far. Even for the 2D case high computational costs have lead to the development of numerous variations for the Hough Transform. In this article we evaluate different variants of the Hough Transform with respect to their applicability to detect planes in 3D point clouds reliably. Apart from computational costs, the main problem is the representation of the accumulator. Usual implementations favor geometrical objects with certain parameters due to uneven sampling of the parameter space. We present a novel approach to design the accumulator focusing on achieving the same size for each cell and compare it to existing designs. [Figure not available: see fulltext.

  15. Affective SSVEP BCI to effectively control 3D objects by using a prism array-based display

    NASA Astrophysics Data System (ADS)

    Mun, Sungchul; Park, Min-Chul

    2014-06-01

    3D objects with depth information can provide many benefits to users in education, surgery, and interactions. In particular, many studies have been done to enhance sense of reality in 3D interaction. Viewing and controlling stereoscopic 3D objects with crossed or uncrossed disparities, however, can cause visual fatigue due to the vergenceaccommodation conflict generally accepted in 3D research fields. In order to avoid the vergence-accommodation mismatch and provide a strong sense of presence to users, we apply a prism array-based display to presenting 3D objects. Emotional pictures were used as visual stimuli in control panels to increase information transfer rate and reduce false positives in controlling 3D objects. Involuntarily motivated selective attention by affective mechanism can enhance steady-state visually evoked potential (SSVEP) amplitude and lead to increased interaction efficiency. More attentional resources are allocated to affective pictures with high valence and arousal levels than to normal visual stimuli such as white-and-black oscillating squares and checkerboards. Among representative BCI control components (i.e., eventrelated potentials (ERP), event-related (de)synchronization (ERD/ERS), and SSVEP), SSVEP-based BCI was chosen in the following reasons. It shows high information transfer rates and takes a few minutes for users to control BCI system while few electrodes are required for obtaining reliable brainwave signals enough to capture users' intention. The proposed BCI methods are expected to enhance sense of reality in 3D space without causing critical visual fatigue to occur. In addition, people who are very susceptible to (auto) stereoscopic 3D may be able to use the affective BCI.

  16. Discovery of Small Molecules for Fluorescent Detection of Complement Activation Product C3d.

    PubMed

    Gorham, Ronald D; Nuñez, Vicente; Lin, Jung-Hsin; Rooijakkers, Suzan H M; Vullev, Valentine I; Morikis, Dimitrios

    2015-12-24

    Complement activation plays a major role in many acute and chronic inflammatory conditions. C3d, a terminal product of complement activation, remains covalently attached to cells and is an excellent biomarker of complement-mediated inflammation. We employed a virtual high-throughput screening protocol to identify molecules with predicted binding to complement C3d and with intrinsic fluorescence properties to enable detection. Pharmacophore models were developed based on known C3d-ligand interactions and information from computational analysis of structural and molecular dynamics data. Iterative pharmacophore-based virtual screening was performed to identify druglike molecules with physicochemical similarity to the natural C3d ligand CR2. Hits from the pharmacophore screens were docked to C3d and ranked based on predicted binding free energies. Top-ranked molecules were selected for experimental validation of binding affinity to C3d, using microscale thermophoresis, and for their suitability to become molecular imaging agents, using fluorescence spectroscopy. This work serves as a foundation for identifying additional fluorescent molecules with high-affinity for C3d that will subsequently be explored as noninvasive in vivo diagnostics of complement-mediated inflammation, for spatiotemporal monitoring of disease progression, and for targeting therapeutics to sites of inflammation.

  17. Discovery of Small Molecules for Fluorescent Detection of Complement Activation Product C3d.

    PubMed

    Gorham, Ronald D; Nuñez, Vicente; Lin, Jung-Hsin; Rooijakkers, Suzan H M; Vullev, Valentine I; Morikis, Dimitrios

    2015-12-24

    Complement activation plays a major role in many acute and chronic inflammatory conditions. C3d, a terminal product of complement activation, remains covalently attached to cells and is an excellent biomarker of complement-mediated inflammation. We employed a virtual high-throughput screening protocol to identify molecules with predicted binding to complement C3d and with intrinsic fluorescence properties to enable detection. Pharmacophore models were developed based on known C3d-ligand interactions and information from computational analysis of structural and molecular dynamics data. Iterative pharmacophore-based virtual screening was performed to identify druglike molecules with physicochemical similarity to the natural C3d ligand CR2. Hits from the pharmacophore screens were docked to C3d and ranked based on predicted binding free energies. Top-ranked molecules were selected for experimental validation of binding affinity to C3d, using microscale thermophoresis, and for their suitability to become molecular imaging agents, using fluorescence spectroscopy. This work serves as a foundation for identifying additional fluorescent molecules with high-affinity for C3d that will subsequently be explored as noninvasive in vivo diagnostics of complement-mediated inflammation, for spatiotemporal monitoring of disease progression, and for targeting therapeutics to sites of inflammation. PMID:26613117

  18. Seeing Objects as Faces Enhances Object Detection.

    PubMed

    Takahashi, Kohske; Watanabe, Katsumi

    2015-10-01

    The face is a special visual stimulus. Both bottom-up processes for low-level facial features and top-down modulation by face expectations contribute to the advantages of face perception. However, it is hard to dissociate the top-down factors from the bottom-up processes, since facial stimuli mandatorily lead to face awareness. In the present study, using the face pareidolia phenomenon, we demonstrated that face awareness, namely seeing an object as a face, enhances object detection performance. In face pareidolia, some people see a visual stimulus, for example, three dots arranged in V shape, as a face, while others do not. This phenomenon allows us to investigate the effect of face awareness leaving the stimulus per se unchanged. Participants were asked to detect a face target or a triangle target. While target per se was identical between the two tasks, the detection sensitivity was higher when the participants recognized the target as a face. This was the case irrespective of the stimulus eccentricity or the vertical orientation of the stimulus. These results demonstrate that seeing an object as a face facilitates object detection via top-down modulation. The advantages of face perception are, therefore, at least partly, due to face awareness.

  19. Seeing Objects as Faces Enhances Object Detection

    PubMed Central

    Watanabe, Katsumi

    2015-01-01

    The face is a special visual stimulus. Both bottom-up processes for low-level facial features and top-down modulation by face expectations contribute to the advantages of face perception. However, it is hard to dissociate the top-down factors from the bottom-up processes, since facial stimuli mandatorily lead to face awareness. In the present study, using the face pareidolia phenomenon, we demonstrated that face awareness, namely seeing an object as a face, enhances object detection performance. In face pareidolia, some people see a visual stimulus, for example, three dots arranged in V shape, as a face, while others do not. This phenomenon allows us to investigate the effect of face awareness leaving the stimulus per se unchanged. Participants were asked to detect a face target or a triangle target. While target per se was identical between the two tasks, the detection sensitivity was higher when the participants recognized the target as a face. This was the case irrespective of the stimulus eccentricity or the vertical orientation of the stimulus. These results demonstrate that seeing an object as a face facilitates object detection via top-down modulation. The advantages of face perception are, therefore, at least partly, due to face awareness. PMID:27648219

  20. Seeing Objects as Faces Enhances Object Detection

    PubMed Central

    Watanabe, Katsumi

    2015-01-01

    The face is a special visual stimulus. Both bottom-up processes for low-level facial features and top-down modulation by face expectations contribute to the advantages of face perception. However, it is hard to dissociate the top-down factors from the bottom-up processes, since facial stimuli mandatorily lead to face awareness. In the present study, using the face pareidolia phenomenon, we demonstrated that face awareness, namely seeing an object as a face, enhances object detection performance. In face pareidolia, some people see a visual stimulus, for example, three dots arranged in V shape, as a face, while others do not. This phenomenon allows us to investigate the effect of face awareness leaving the stimulus per se unchanged. Participants were asked to detect a face target or a triangle target. While target per se was identical between the two tasks, the detection sensitivity was higher when the participants recognized the target as a face. This was the case irrespective of the stimulus eccentricity or the vertical orientation of the stimulus. These results demonstrate that seeing an object as a face facilitates object detection via top-down modulation. The advantages of face perception are, therefore, at least partly, due to face awareness.

  1. Seeing Objects as Faces Enhances Object Detection.

    PubMed

    Takahashi, Kohske; Watanabe, Katsumi

    2015-10-01

    The face is a special visual stimulus. Both bottom-up processes for low-level facial features and top-down modulation by face expectations contribute to the advantages of face perception. However, it is hard to dissociate the top-down factors from the bottom-up processes, since facial stimuli mandatorily lead to face awareness. In the present study, using the face pareidolia phenomenon, we demonstrated that face awareness, namely seeing an object as a face, enhances object detection performance. In face pareidolia, some people see a visual stimulus, for example, three dots arranged in V shape, as a face, while others do not. This phenomenon allows us to investigate the effect of face awareness leaving the stimulus per se unchanged. Participants were asked to detect a face target or a triangle target. While target per se was identical between the two tasks, the detection sensitivity was higher when the participants recognized the target as a face. This was the case irrespective of the stimulus eccentricity or the vertical orientation of the stimulus. These results demonstrate that seeing an object as a face facilitates object detection via top-down modulation. The advantages of face perception are, therefore, at least partly, due to face awareness. PMID:27648219

  2. Lung nodule detection using 3D convolutional neural networks trained on weakly labeled data

    NASA Astrophysics Data System (ADS)

    Anirudh, Rushil; Thiagarajan, Jayaraman J.; Bremer, Timo; Kim, Hyojin

    2016-03-01

    Early detection of lung nodules is currently the one of the most effective ways to predict and treat lung cancer. As a result, the past decade has seen a lot of focus on computer aided diagnosis (CAD) of lung nodules, whose goal is to efficiently detect, segment lung nodules and classify them as being benign or malignant. Effective detection of such nodules remains a challenge due to their arbitrariness in shape, size and texture. In this paper, we propose to employ 3D convolutional neural networks (CNN) to learn highly discriminative features for nodule detection in lieu of hand-engineered ones such as geometric shape or texture. While 3D CNNs are promising tools to model the spatio-temporal statistics of data, they are limited by their need for detailed 3D labels, which can be prohibitively expensive when compared obtaining 2D labels. Existing CAD methods rely on obtaining detailed labels for lung nodules, to train models, which is also unrealistic and time consuming. To alleviate this challenge, we propose a solution wherein the expert needs to provide only a point label, i.e., the central pixel of of the nodule, and its largest expected size. We use unsupervised segmentation to grow out a 3D region, which is used to train the CNN. Using experiments on the SPIE-LUNGx dataset, we show that the network trained using these weak labels can produce reasonably low false positive rates with a high sensitivity, even in the absence of accurate 3D labels.

  3. Real-time visualization of 3-D dynamic microscopic objects using optical diffraction tomography.

    PubMed

    Kim, Kyoohyun; Kim, Kyung Sang; Park, Hyunjoo; Ye, Jong Chul; Park, Yongkeun

    2013-12-30

    3-D refractive index (RI) distribution is an intrinsic bio-marker for the chemical and structural information about biological cells. Here we develop an optical diffraction tomography technique for the real-time reconstruction of 3-D RI distribution, employing sparse angle illumination and a graphic processing unit (GPU) implementation. The execution time for the tomographic reconstruction is 0.21 s for 96(3) voxels, which is 17 times faster than that of a conventional approach. We demonstrated the real-time visualization capability with imaging the dynamics of Brownian motion of an anisotropic colloidal dimer and the dynamic shape change in a red blood cell upon shear flow.

  4. Visualizing 3D Objects from 2D Cross Sectional Images Displayed "In-Situ" versus "Ex-Situ"

    ERIC Educational Resources Information Center

    Wu, Bing; Klatzky, Roberta L.; Stetten, George

    2010-01-01

    The present research investigates how mental visualization of a 3D object from 2D cross sectional images is influenced by displacing the images from the source object, as is customary in medical imaging. Three experiments were conducted to assess people's ability to integrate spatial information over a series of cross sectional images in order to…

  5. Breast mass detection using slice conspicuity in 3D reconstructed digital breast volumes

    NASA Astrophysics Data System (ADS)

    Kim, Seong Tae; Kim, Dae Hoe; Ro, Yong Man

    2014-09-01

    In digital breast tomosynthesis, the three dimensional (3D) reconstructed volumes only provide quasi-3D structure information with limited resolution along the depth direction due to insufficient sampling in depth direction and the limited angular range. The limitation could seriously hamper the conventional 3D image analysis techniques for detecting masses because the limited number of projection views causes blurring in the out-of-focus planes. In this paper, we propose a novel mass detection approach using slice conspicuity in the 3D reconstructed digital breast volumes to overcome the above limitation. First, to overcome the limited resolution along the depth direction, we detect regions of interest (ROIs) on each reconstructed slice and separately utilize the depth directional information to combine the ROIs effectively. Furthermore, we measure the blurriness of each slice for resolving the degradation of performance caused by the blur in the out-of-focus plane. Finally, mass features are extracted from the selected in focus slices and analyzed by a support vector machine classifier to reduce the false positives. Comparative experiments have been conducted on a clinical data set. Experimental results demonstrate that the proposed approach outperforms the conventional 3D approach by achieving a high sensitivity with a small number of false positives.

  6. Extraction of "best fit circles" on 3D meshes based on discrete curvatures: application to impact craters detection

    NASA Astrophysics Data System (ADS)

    Beguet, Florian; Bali, Sarah; Christoff, Nicole; Jorda, Laurent; Viseur, Sophie; Bouley, Sylvain; Manolova, Agata; Mari, Jean-Luc

    2016-04-01

    Impact craters is a typical feature observed at the surface of most bodies in the solar system: terrestrial planets, their satellites, asteroids and even possibly cometary nuclei exhibit impact craters. Their spatial density yields the estimation of the age of the surface, a key parameter required for subsequent geological studies. With the development of interplanetary missions, a large number of solar system objects have been mapped at a high spatial resolution, emphasizing the need for new automatic methods of crater detection and counting. In this work, we present such a method using a new approach based on the analysis of reconstructed 3D meshes instead of 2D images. The robust extraction of feature areas on surface objects embedded in 3D, like circular shapes, is a challenging problem. Classical approaches generally rely on image processing and template matching on a 2D flat projection of the 3D object (for instance a high-resolution picture). In this paper, we propose a full 3D method that mainly relies on curvature analysis. Mean and Gaussian curvatures are estimated on the surface. They are used to label vertices that belong to concave parts corresponding to specific pits on the surface. Centers are located in the targeted surface regions, corresponding to potential crater features. Then "best fit circles" are extracted, based on the rims of the circular shapes. They consist in closed lines exclusively composed of edges of the initial mesh. This approach has been applied to the detection of craters on the asteroid Vesta. Keywords: geometric modeling, 3D meshes, shape recognition, mesh processing, discrete curvatures, asteroids, crater detection, geology, geomorphology.

  7. 3D ultrasound volume stitching using phase symmetry and harris corner detection for orthopaedic applications

    NASA Astrophysics Data System (ADS)

    Dalvi, Rupin; Hacihaliloglu, Ilker; Abugharbieh, Rafeef

    2010-03-01

    Stitching of volumes obtained from three dimensional (3D) ultrasound (US) scanners improves visualization of anatomy in many clinical applications. Fast but accurate volume registration remains the key challenge in this area.We propose a volume stitching method based on efficient registration of 3D US volumes obtained from a tracked US probe. Since the volumes, after adjusting for probe motion, are coarsely registered, we obtain salient correspondence points in the central slices of these volumes. This is done by first removing artifacts in the US slices using intensity invariant local phase image processing and then applying the Harris Corner detection algorithm. Fast sub-volume registration on a small neighborhood around the points then gives fast, accurate 3D registration parameters. The method has been tested on 3D US scans of phantom and real human radius and pelvis bones and a phantom human fetus. The method has also been compared to volumetric registration, as well as feature based registration using 3D-SIFT. Quantitative results show average post-registration error of 0.33mm which is comparable to volumetric registration accuracy (0.31mm) and much better than 3D-SIFT based registration which failed to register the volumes. The proposed method was also much faster than volumetric registration (~4.5 seconds versus 83 seconds).

  8. A new approach for salt dome detection using a 3D multidirectional edge detector

    NASA Astrophysics Data System (ADS)

    Asjad, Amin; Mohamed, Deriche

    2015-09-01

    Accurate salt dome detection from 3D seismic data is crucial to different seismic data analysis applications. We present a new edge based approach for salt dome detection in migrated 3D seismic data. The proposed algorithm overcomes the drawbacks of existing edge-based techniques which only consider edges in the x (crossline) and y (inline) directions in 2D data and the x (crossline), y (inline), and z (time) directions in 3D data. The algorithm works by combining 3D gradient maps computed along diagonal directions and those computed in x, y, and z directions to accurately detect the boundaries of salt regions. The combination of x, y, and z directions and diagonal edges ensures that the proposed algorithm works well even if the dips along the salt boundary are represented only by weak reflectors. Contrary to other edge and texture based salt dome detection techniques, the proposed algorithm is independent of the amplitude variations in seismic data. We tested the proposed algorithm on the publicly available Netherlands offshore F3 block. The results suggest that the proposed algorithm can detect salt bodies with high accuracy than existing gradient based and texture-based techniques when used separately. More importantly, the proposed approach is shown to be computationally efficient allowing for real time implementation and deployment.

  9. An optical system for detecting 3D high-speed oscillation of a single ultrasound microbubble

    PubMed Central

    Liu, Yuan; Yuan, Baohong

    2013-01-01

    As contrast agents, microbubbles have been playing significant roles in ultrasound imaging. Investigation of microbubble oscillation is crucial for microbubble characterization and detection. Unfortunately, 3-dimensional (3D) observation of microbubble oscillation is challenging and costly because of the bubble size—a few microns in diameter—and the high-speed dynamics under MHz ultrasound pressure waves. In this study, a cost-efficient optical confocal microscopic system combined with a gated and intensified charge-coupled device (ICCD) camera were developed to detect 3D microbubble oscillation. The capability of imaging microbubble high-speed oscillation with much lower costs than with an ultra-fast framing or streak camera system was demonstrated. In addition, microbubble oscillations along both lateral (x and y) and axial (z) directions were demonstrated. Accordingly, this system is an excellent alternative for 3D investigation of microbubble high-speed oscillation, especially when budgets are limited. PMID:24049677

  10. An optical system for detecting 3D high-speed oscillation of a single ultrasound microbubble.

    PubMed

    Liu, Yuan; Yuan, Baohong

    2013-01-01

    As contrast agents, microbubbles have been playing significant roles in ultrasound imaging. Investigation of microbubble oscillation is crucial for microbubble characterization and detection. Unfortunately, 3-dimensional (3D) observation of microbubble oscillation is challenging and costly because of the bubble size-a few microns in diameter-and the high-speed dynamics under MHz ultrasound pressure waves. In this study, a cost-efficient optical confocal microscopic system combined with a gated and intensified charge-coupled device (ICCD) camera were developed to detect 3D microbubble oscillation. The capability of imaging microbubble high-speed oscillation with much lower costs than with an ultra-fast framing or streak camera system was demonstrated. In addition, microbubble oscillations along both lateral (x and y) and axial (z) directions were demonstrated. Accordingly, this system is an excellent alternative for 3D investigation of microbubble high-speed oscillation, especially when budgets are limited. PMID:24049677

  11. A swaying object detection algorithm

    NASA Astrophysics Data System (ADS)

    Wang, Shidong; Rong, Jianzhong; Zhou, Dechuang; Wang, Jian

    2013-07-01

    Moving object detection is a most important preliminary step in video analysis. Some moving objects such as spitting steam, fire and smoke have unique motion feature whose lower position keep basically unchanged and the upper position move back and forth. Based on this unique motion feature, a swaying object detection algorithm is presented in this paper. Firstly, fuzzy integral was adopted to integrate color features for extracting moving objects from video frames. Secondly, a swaying identification algorithm based on centroid calculation was used to distinguish the swaying object from other moving objects. Experiments show that the proposed method is effective to detect swaying object.

  12. Detection of the aortic intimal tears by using 3D digital topology

    NASA Astrophysics Data System (ADS)

    Lohou, Christophe; Miguel, Bruno

    2011-03-01

    Aortic dissection is a real problem of public health, it is a medical emergency and may quickly lead to death. Aortic dissection is caused by aortal tissue perforation because of blood pressure. It consists of tears (or holes of the intimal tissue) inside lumens. These tears are difficult to detect because they do not correspond to a filled organ to segment; they are usually visually retrieved by radiologists by examining gray level variation on successive image slices, but it remains a very difficult and error-prone task. Our purpose is to detect these intimal tears to help cardiac surgeons in making diagnosis. It would be useful either during a preoperative phase (visualization and location of tears, endoprothesis sizing); or during a peroperative phase (a registration of tears on angiographic images would lead to a more accuracy of surgeon's gestures and thus would enhance care of patient). At this aim, we use Aktouf et al.'s holes filling algorithm proposed in the field of digital topology. This algorithm permits the filling of holes of a 3D binary object by using topological notions - the holes are precisely the intimal tears for our aortic dissection images, after a first preprocessing step. As far as we know, this is the first time that such a proposal is made, even if it is a crucial data for cardiac surgeons. Our study is a preliminary and innovative work; our results are nevertheless considered satisfactory. This approach would also gain to be known to specialists of other diseases.

  13. Spherical blurred shape model for 3-D object and pose recognition: quantitative analysis and HCI applications in smart environments.

    PubMed

    Lopes, Oscar; Reyes, Miguel; Escalera, Sergio; Gonzàlez, Jordi

    2014-12-01

    The use of depth maps is of increasing interest after the advent of cheap multisensor devices based on structured light, such as Kinect. In this context, there is a strong need of powerful 3-D shape descriptors able to generate rich object representations. Although several 3-D descriptors have been already proposed in the literature, the research of discriminative and computationally efficient descriptors is still an open issue. In this paper, we propose a novel point cloud descriptor called spherical blurred shape model (SBSM) that successfully encodes the structure density and local variabilities of an object based on shape voxel distances and a neighborhood propagation strategy. The proposed SBSM is proven to be rotation and scale invariant, robust to noise and occlusions, highly discriminative for multiple categories of complex objects like the human hand, and computationally efficient since the SBSM complexity is linear to the number of object voxels. Experimental evaluation in public depth multiclass object data, 3-D facial expressions data, and a novel hand poses data sets show significant performance improvements in relation to state-of-the-art approaches. Moreover, the effectiveness of the proposal is also proved for object spotting in 3-D scenes and for real-time automatic hand pose recognition in human computer interaction scenarios. PMID:25415944

  14. Detection of complement activation using monoclonal antibodies against C3d

    PubMed Central

    Thurman, Joshua M.; Kulik, Liudmila; Orth, Heather; Wong, Maria; Renner, Brandon; Sargsyan, Siranush A.; Mitchell, Lynne M.; Hourcade, Dennis E.; Hannan, Jonathan P.; Kovacs, James M.; Coughlin, Beth; Woodell, Alex S.; Pickering, Matthew C.; Rohrer, Bärbel; Holers, V. Michael

    2013-01-01

    During complement activation the C3 protein is cleaved, and C3 activation fragments are covalently fixed to tissues. Tissue-bound C3 fragments are a durable biomarker of tissue inflammation, and these fragments have been exploited as addressable binding ligands for targeted therapeutics and diagnostic agents. We have generated cross-reactive murine monoclonal antibodies against human and mouse C3d, the final C3 degradation fragment generated during complement activation. We developed 3 monoclonal antibodies (3d8b, 3d9a, and 3d29) that preferentially bind to the iC3b, C3dg, and C3d fragments in solution, but do not bind to intact C3 or C3b. The same 3 clones also bind to tissue-bound C3 activation fragments when injected systemically. Using mouse models of renal and ocular disease, we confirmed that, following systemic injection, the antibodies accumulated at sites of C3 fragment deposition within the glomerulus, the renal tubulointerstitium, and the posterior pole of the eye. To detect antibodies bound within the eye, we used optical imaging and observed accumulation of the antibodies within retinal lesions in a model of choroidal neovascularization (CNV). Our results demonstrate that imaging methods that use these antibodies may provide a sensitive means of detecting and monitoring complement activation–associated tissue inflammation. PMID:23619360

  15. 360 degree realistic 3D image display and image processing from real objects

    NASA Astrophysics Data System (ADS)

    Luo, Xin; Chen, Yue; Huang, Yong; Tan, Xiaodi; Horimai, Hideyoshi

    2016-09-01

    A 360-degree realistic 3D image display system based on direct light scanning method, so-called Holo-Table has been introduced in this paper. High-density directional continuous 3D motion images can be displayed easily with only one spatial light modulator. Using the holographic screen as the beam deflector, 360-degree full horizontal viewing angle was achieved. As an accompany part of the system, CMOS camera based image acquisition platform was built to feed the display engine, which can take a full 360-degree continuous imaging of the sample at the center. Customized image processing techniques such as scaling, rotation, format transformation were also developed and embedded into the system control software platform. In the end several samples were imaged to demonstrate the capability of our system.

  16. Parallel contact detection algorithm for transient solid dynamics simulations using PRONTO3D

    SciTech Connect

    Attaway, S.W.; Hendrickson, B.A.; Plimpton, S.J.

    1996-09-01

    An efficient, scalable, parallel algorithm for treating material surface contacts in solid mechanics finite element programs has been implemented in a modular way for MIMD parallel computers. The serial contact detection algorithm that was developed previously for the transient dynamics finite element code PRONTO3D has been extended for use in parallel computation by devising a dynamic (adaptive) processor load balancing scheme.

  17. Simulated and Real Sheet-of-Light 3D Object Scanning Using a-Si:H Thin Film PSD Arrays

    PubMed Central

    Contreras, Javier; Tornero, Josep; Ferreira, Isabel; Martins, Rodrigo; Gomes, Luis; Fortunato, Elvira

    2015-01-01

    A MATLAB/SIMULINK software simulation model (structure and component blocks) has been constructed in order to view and analyze the potential of the PSD (Position Sensitive Detector) array concept technology before it is further expanded or developed. This simulation allows changing most of its parameters, such as the number of elements in the PSD array, the direction of vision, the viewing/scanning angle, the object rotation, translation, sample/scan/simulation time, etc. In addition, results show for the first time the possibility of scanning an object in 3D when using an a-Si:H thin film 128 PSD array sensor and hardware/software system. Moreover, this sensor technology is able to perform these scans and render 3D objects at high speeds and high resolutions when using a sheet-of-light laser within a triangulation platform. As shown by the simulation, a substantial enhancement in 3D object profile image quality and realism can be achieved by increasing the number of elements of the PSD array sensor as well as by achieving an optimal position response from the sensor since clearly the definition of the 3D object profile depends on the correct and accurate position response of each detector as well as on the size of the PSD array. PMID:26633403

  18. Decoupling Object Detection and Categorization

    ERIC Educational Resources Information Center

    Mack, Michael L.; Palmeri, Thomas J.

    2010-01-01

    We investigated whether there exists a behavioral dependency between object detection and categorization. Previous work (Grill-Spector & Kanwisher, 2005) suggests that object detection and basic-level categorization may be the very same perceptual mechanism: As objects are parsed from the background they are categorized at the basic level. In the…

  19. A comparative analysis between active and passive techniques for underwater 3D reconstruction of close-range objects.

    PubMed

    Bianco, Gianfranco; Gallo, Alessandro; Bruno, Fabio; Muzzupappa, Maurizio

    2013-01-01

    In some application fields, such as underwater archaeology or marine biology, there is the need to collect three-dimensional, close-range data from objects that cannot be removed from their site. In particular, 3D imaging techniques are widely employed for close-range acquisitions in underwater environment. In this work we have compared in water two 3D imaging techniques based on active and passive approaches, respectively, and whole-field acquisition. The comparison is performed under poor visibility conditions, produced in the laboratory by suspending different quantities of clay in a water tank. For a fair comparison, a stereo configuration has been adopted for both the techniques, using the same setup, working distance, calibration, and objects. At the moment, the proposed setup is not suitable for real world applications, but it allowed us to conduct a preliminary analysis on the performances of the two techniques and to understand their capability to acquire 3D points in presence of turbidity. The performances have been evaluated in terms of accuracy and density of the acquired 3D points. Our results can be used as a reference for further comparisons in the analysis of other 3D techniques and algorithms. PMID:23966193

  20. A comparative analysis between active and passive techniques for underwater 3D reconstruction of close-range objects.

    PubMed

    Bianco, Gianfranco; Gallo, Alessandro; Bruno, Fabio; Muzzupappa, Maurizio

    2013-08-20

    In some application fields, such as underwater archaeology or marine biology, there is the need to collect three-dimensional, close-range data from objects that cannot be removed from their site. In particular, 3D imaging techniques are widely employed for close-range acquisitions in underwater environment. In this work we have compared in water two 3D imaging techniques based on active and passive approaches, respectively, and whole-field acquisition. The comparison is performed under poor visibility conditions, produced in the laboratory by suspending different quantities of clay in a water tank. For a fair comparison, a stereo configuration has been adopted for both the techniques, using the same setup, working distance, calibration, and objects. At the moment, the proposed setup is not suitable for real world applications, but it allowed us to conduct a preliminary analysis on the performances of the two techniques and to understand their capability to acquire 3D points in presence of turbidity. The performances have been evaluated in terms of accuracy and density of the acquired 3D points. Our results can be used as a reference for further comparisons in the analysis of other 3D techniques and algorithms.

  1. A Comparative Analysis between Active and Passive Techniques for Underwater 3D Reconstruction of Close-Range Objects

    PubMed Central

    Bianco, Gianfranco; Gallo, Alessandro; Bruno, Fabio; Muzzupappa, Maurizio

    2013-01-01

    In some application fields, such as underwater archaeology or marine biology, there is the need to collect three-dimensional, close-range data from objects that cannot be removed from their site. In particular, 3D imaging techniques are widely employed for close-range acquisitions in underwater environment. In this work we have compared in water two 3D imaging techniques based on active and passive approaches, respectively, and whole-field acquisition. The comparison is performed under poor visibility conditions, produced in the laboratory by suspending different quantities of clay in a water tank. For a fair comparison, a stereo configuration has been adopted for both the techniques, using the same setup, working distance, calibration, and objects. At the moment, the proposed setup is not suitable for real world applications, but it allowed us to conduct a preliminary analysis on the performances of the two techniques and to understand their capability to acquire 3D points in presence of turbidity. The performances have been evaluated in terms of accuracy and density of the acquired 3D points. Our results can be used as a reference for further comparisons in the analysis of other 3D techniques and algorithms. PMID:23966193

  2. High sensitivity plasmonic biosensor based on nanoimprinted quasi 3D nanosquares for cell detection

    NASA Astrophysics Data System (ADS)

    Zhu, Shuyan; Li, Hualin; Yang, Mengsu; Pang, Stella W.

    2016-07-01

    Quasi three-dimensional (3D) plasmonic nanostructures consisting of Au nanosquares on top of SU-8 nanopillars and Au nanoholes on the bottom were developed and fabricated using nanoimprint lithography with simultaneous thermal and UV exposure. These 3D plasmonic nanostructures were used to detect cell concentration of lung cancer A549 cells, retinal pigment epithelial (RPE) cells, and breast cancer MCF-7 cells. Nanoimprint technology has the advantage of producing high uniformity plasmonic nanostructures for such biosensors. Multiple resonance modes were observed in these quasi 3D plasmonic nanostructures. The hybrid coupling of localized surface plasmon resonances and Fabry–Perot cavity modes in the quasi 3D nanostructures resulted in high sensitivity of 496 nm/refractive index unit. The plasmonic resonance peak wavelength and sensitivity could be tuned by varying the Au thickness. Resonance peak shifts for different cells at the same concentration were distinct due to their different cell area and confluency. The cell concentration detection limit covered a large range of 5 × 102 to 1 × 107 cells ml‑1 with these new plasmonic nanostructures. They also provide a large resonance peak shift of 51 nm for as little as 0.08 cells mm‑2 of RPE cells for high sensitivity cell detection.

  3. High sensitivity plasmonic biosensor based on nanoimprinted quasi 3D nanosquares for cell detection

    NASA Astrophysics Data System (ADS)

    Zhu, Shuyan; Li, Hualin; Yang, Mengsu; Pang, Stella W.

    2016-07-01

    Quasi three-dimensional (3D) plasmonic nanostructures consisting of Au nanosquares on top of SU-8 nanopillars and Au nanoholes on the bottom were developed and fabricated using nanoimprint lithography with simultaneous thermal and UV exposure. These 3D plasmonic nanostructures were used to detect cell concentration of lung cancer A549 cells, retinal pigment epithelial (RPE) cells, and breast cancer MCF-7 cells. Nanoimprint technology has the advantage of producing high uniformity plasmonic nanostructures for such biosensors. Multiple resonance modes were observed in these quasi 3D plasmonic nanostructures. The hybrid coupling of localized surface plasmon resonances and Fabry-Perot cavity modes in the quasi 3D nanostructures resulted in high sensitivity of 496 nm/refractive index unit. The plasmonic resonance peak wavelength and sensitivity could be tuned by varying the Au thickness. Resonance peak shifts for different cells at the same concentration were distinct due to their different cell area and confluency. The cell concentration detection limit covered a large range of 5 × 102 to 1 × 107 cells ml-1 with these new plasmonic nanostructures. They also provide a large resonance peak shift of 51 nm for as little as 0.08 cells mm-2 of RPE cells for high sensitivity cell detection.

  4. Development of 3D interactive visual objects using the Scripps Institution of Oceanography's Visualization Center

    NASA Astrophysics Data System (ADS)

    Kilb, D.; Reif, C.; Peach, C.; Keen, C. S.; Smith, B.; Mellors, R. J.

    2003-12-01

    Within the last year scientists and educators at the Scripps Institution of Oceanography (SIO), the Birch Aquarium at Scripps and San Diego State University have collaborated with education specialists to develop 3D interactive graphic teaching modules for use in the classroom and in teacher workshops at the SIO Visualization center (http://siovizcenter.ucsd.edu). The unique aspect of the SIO Visualization center is that the center is designed around a 120 degree curved Panoram floor-to-ceiling screen (8'6" by 28'4") that immerses viewers in a virtual environment. The center is powered by an SGI 3400 Onyx computer that is more powerful, by an order of magnitude in both speed and memory, than typical base systems currently used for education and outreach presentations. This technology allows us to display multiple 3D data layers (e.g., seismicity, high resolution topography, seismic reflectivity, draped interferometric synthetic aperture radar (InSAR) images, etc.) simultaneously, render them in 3D stereo, and take a virtual flight through the data as dictated on the spot by the user. This system can also render snapshots, images and movies that are too big for other systems, and then export smaller size end-products to more commonly used computer systems. Since early 2002, we have explored various ways to provide informal education and outreach focusing on current research presented directly by the researchers doing the work. The Center currently provides a centerpiece for instruction on southern California seismology for K-12 students and teachers for various Scripps education endeavors. Future plans are in place to use the Visualization Center at Scripps for extended K-12 and college educational programs. In particular, we will be identifying K-12 curriculum needs, assisting with teacher education, developing assessments of our programs and products, producing web-accessible teaching modules and facilitating the development of appropriate teaching tools to be

  5. 3D graphene foams decorated by CuO nanoflowers for ultrasensitive ascorbic acid detection.

    PubMed

    Ma, Ye; Zhao, Minggang; Cai, Bin; Wang, Wei; Ye, Zhizhen; Huang, Jingyun

    2014-09-15

    When the in vitro research works of biosensing begin to mimic in vivo conditions, some certain three-dimensional (3D) structures of biosensors are needed to accommodate biomolecules, bacteria or even cells to resemble the in vivo 3D environment. To meet this end, a novel method of synthesizing CuO nanoflowers on the 3D graphene foam (GF) was first demonstrated. The 3DGF/CuO nanoflowers composite was used as a monolithic free-standing 3D biosensor for electrochemical detection of ascorbic acid (AA). The 3D conductive structure of the GF is favorable for current collection, mass transport and loading bioactive chemicals. And CuO nanoflowers further increase the active surface area and catalyze the redox of AA. Thus, all these features endows 3DGF/CuO composite with outstanding biosensing properties such as an ultrahigh sensitivity of 2.06 mA mM(-1) cm(-2) to AA at 3 s response time.

  6. Objective Assessment and Design Improvement of a Staring, Sparse Transducer Array by the Spatial Crosstalk Matrix for 3D Photoacoustic Tomography

    PubMed Central

    Kosik, Ivan; Raess, Avery

    2015-01-01

    Accurate reconstruction of 3D photoacoustic (PA) images requires detection of photoacoustic signals from many angles. Several groups have adopted staring ultrasound arrays, but assessment of array performance has been limited. We previously reported on a method to calibrate a 3D PA tomography (PAT) staring array system and analyze system performance using singular value decomposition (SVD). The developed SVD metric, however, was impractical for large system matrices, which are typical of 3D PAT problems. The present study consisted of two main objectives. The first objective aimed to introduce the crosstalk matrix concept to the field of PAT for system design. Figures-of-merit utilized in this study were root mean square error, peak signal-to-noise ratio, mean absolute error, and a three dimensional structural similarity index, which were derived between the normalized spatial crosstalk matrix and the identity matrix. The applicability of this approach for 3D PAT was validated by observing the response of the figures-of-merit in relation to well-understood PAT sampling characteristics (i.e. spatial and temporal sampling rate). The second objective aimed to utilize the figures-of-merit to characterize and improve the performance of a near-spherical staring array design. Transducer arrangement, array radius, and array angular coverage were the design parameters examined. We observed that the performance of a 129-element staring transducer array for 3D PAT could be improved by selection of optimal values of the design parameters. The results suggested that this formulation could be used to objectively characterize 3D PAT system performance and would enable the development of efficient strategies for system design optimization. PMID:25875177

  7. Evaluation of iterative sparse object reconstruction from few projections for 3-D rotational coronary angiography.

    PubMed

    Hansis, Eberhard; Schäfer, Dirk; Dössel, Olaf; Grass, Michael

    2008-11-01

    A 3-D reconstruction of the coronary arteries offers great advantages in the diagnosis and treatment of cardiovascular disease, compared to 2-D X-ray angiograms. Besides improved roadmapping, quantitative vessel analysis is possible. Due to the heart's motion, rotational coronary angiography typically provides only 5-10 projections for the reconstruction of each cardiac phase, which leads to a strongly undersampled reconstruction problem. Such an ill-posed problem can be approached with regularized iterative methods. The coronary arteries cover only a small fraction of the reconstruction volume. Therefore, the minimization of the mbiL(1) norm of the reconstructed image, favoring spatially sparse images, is a suitable regularization. Additional problems are overlaid background structures and projection truncation, which can be alleviated by background reduction using a morphological top-hat filter. This paper quantitatively evaluates image reconstruction based on these ideas on software phantom data, in terms of reconstructed absorption coefficients and vessel radii. Results for different algorithms and different input data sets are compared. First results for electrocardiogram-gated reconstruction from clinical catheter-based rotational X-ray coronary angiography are presented. Excellent 3-D image quality can be achieved. PMID:18955171

  8. Tailoring bulk mechanical properties of 3D printed objects of polylactic acid varying internal micro-architecture

    NASA Astrophysics Data System (ADS)

    Malinauskas, Mangirdas; Skliutas, Edvinas; Jonušauskas, Linas; Mizeras, Deividas; Šešok, Andžela; Piskarskas, Algis

    2015-05-01

    Herein we present 3D Printing (3DP) fabrication of structures having internal microarchitecture and characterization of their mechanical properties. Depending on the material, geometry and fill factor, the manufactured objects mechanical performance can be tailored from "hard" to "soft." In this work we employ low-cost fused filament fabrication 3D printer enabling point-by-point structuring of poly(lactic acid) (PLA) with~̴400 µm feature spatial resolution. The chosen architectures are defined as woodpiles (BCC, FCC and 60 deg rotating). The period is chosen to be of 1200 µm corresponding to 800 µm pores. The produced objects structural quality is characterized using scanning electron microscope, their mechanical properties such as flexural modulus, elastic modulus and stiffness are evaluated by measured experimentally using universal TIRAtest2300 machine. Within the limitation of the carried out study we show that the mechanical properties of 3D printed objects can be tuned at least 3 times by only changing the woodpile geometry arrangement, yet keeping the same filling factor and periodicity of the logs. Additionally, we demonstrate custom 3D printed µ-fluidic elements which can serve as cheap, biocompatible and environmentally biodegradable platforms for integrated Lab-On-Chip (LOC) devices.

  9. Simultaneous high-speed 3D flame front detection and tomographic PIV

    NASA Astrophysics Data System (ADS)

    Ebi, Dominik; Clemens, Noel T.

    2016-03-01

    A technique capable of detecting the instantaneous, time-resolved, 3D flame topography is successfully demonstrated in a lean-premixed swirl flame undergoing flashback. A simultaneous measurement of the volumetric velocity field is possible without the need for additional hardware. Droplets which vaporize in the preheat zone of the flame serve as the marker for the flame front. The droplets are illuminated with a laser and imaged from four different views followed by a tomographic reconstruction to obtain the volumetric particle field. Void regions in the reconstructed particle field, which correspond to regions of burnt gas, are detected with a series of image processing steps. The interface separating the void region from regions filled with particles is defined as the flame surface. The velocity field in the unburnt gas is measured using tomographic PIV. The resulting data include the simultaneous 3D flame front and 3D volumetric velocity field at 5 kHz. The technique is applied to a lean-premixed (ϕ  =  0.8), swirling methane-air flame and validated against simultaneously acquired planar measurements. The mean error associated with the reconstructed 3D flame topography is about 0.4 mm, which is smaller than the flame thickness under the studied conditions. The mean error associated with the volumetric velocity field is about 0.2 m s-1.

  10. 3D GeoWall Analysis System for Shuttle External Tank Foreign Object Debris Events

    NASA Technical Reports Server (NTRS)

    Brown, Richard; Navard, Andrew; Spruce, Joseph

    2010-01-01

    An analytical, advanced imaging method has been developed for the initial monitoring and identification of foam debris and similar anomalies that occur post-launch in reference to the space shuttle s external tank (ET). Remote sensing technologies have been used to perform image enhancement and analysis on high-resolution, true-color images collected with the DCS 760 Kodak digital camera located in the right umbilical well of the space shuttle. Improvements to the camera, using filters, have added sharpness/definition to the image sets; however, image review/analysis of the ET has been limited by the fact that the images acquired by umbilical cameras during launch are two-dimensional, and are usually nonreferenceable between frames due to rotation translation of the ET as it falls away from the space shuttle. Use of stereo pairs of these images can enable strong visual indicators that can immediately portray depth perception of damaged areas or movement of fragments between frames is not perceivable in two-dimensional images. A stereoscopic image visualization system has been developed to allow 3D depth perception of stereo-aligned image pairs taken from in-flight umbilical and handheld digital shuttle cameras. This new system has been developed to augment and optimize existing 2D monitoring capabilities. Using this system, candidate sequential image pairs are identified for transformation into stereo viewing pairs. Image orientation is corrected using control points (similar points) between frames to place the two images in proper X-Y viewing perspective. The images are then imported into the WallView stereo viewing software package. The collected control points are used to generate a transformation equation that is used to re-project one image and effectively co-register it to the other image. The co-registered, oriented image pairs are imported into a WallView image set and are used as a 3D stereo analysis slide show. Multiple sequential image pairs can be used

  11. Objective Assessment of shoulder mobility with a new 3D gyroscope - a validation study

    PubMed Central

    2011-01-01

    Background Assessment of shoulder mobility is essential for clinical follow-up of shoulder treatment. Only a few high sophisticated instruments for objective measurements of shoulder mobility are available. The interobserver dependency of conventional goniometer measurements is high. In the 1990s an isokinetic measuring system of BIODEX Inc. was introduced, which is a very complex but valid instrument. Since 2008 a new user-friendly system called DynaPort MiniMod TriGyro ShoulderTest-System (DP) is available. Aim of this study is the validation of this measuring instrument using the BIODEX-System. Methods The BIODEX is a computerized robotic dynamometer used for isokinetic testing and training of athletes. Because of its size the system needs to be installed in a separated room. The DP is a small, light-weighted three-dimensional gyroscope that is fixed on the distal upper patient arm, recording abduction, flexion and rotation. For direct comparison we fixed the DP on the lever arm of the BIODEX. The accuracy of measurement was determined at different positions, angles and distances from the centre of rotation (COR) as well as different velocities in a radius between 0° - 180° in steps of 20°. All measurements were repeated 10 times. As satisfactory accuracy a difference between both systems below 5° was defined. The statistical analysis was performed with a linear regression model. Results The evaluation shows very high accuracy of measurements. The maximum average deviation is below 2.1°. For a small range of motion the DP is slightly underestimating comparing the BIODEX, whereas for higher angles increasing positive differences are observed. The distance to the COR as well as the position of the DP on the lever arm have no significant influence. Concerning different motion speeds significant but not relevant influence is detected. Unfortunately device related effects are observed, leading to differences between repeated measurements with any two different

  12. Road Signs Detection and Recognition Utilizing Images and 3d Point Cloud Acquired by Mobile Mapping System

    NASA Astrophysics Data System (ADS)

    Li, Y. H.; Shinohara, T.; Satoh, T.; Tachibana, K.

    2016-06-01

    High-definition and highly accurate road maps are necessary for the realization of automated driving, and road signs are among the most important element in the road map. Therefore, a technique is necessary which can acquire information about all kinds of road signs automatically and efficiently. Due to the continuous technical advancement of Mobile Mapping System (MMS), it has become possible to acquire large number of images and 3d point cloud efficiently with highly precise position information. In this paper, we present an automatic road sign detection and recognition approach utilizing both images and 3D point cloud acquired by MMS. The proposed approach consists of three stages: 1) detection of road signs from images based on their color and shape features using object based image analysis method, 2) filtering out of over detected candidates utilizing size and position information estimated from 3D point cloud, region of candidates and camera information, and 3) road sign recognition using template matching method after shape normalization. The effectiveness of proposed approach was evaluated by testing dataset, acquired from more than 180 km of different types of roads in Japan. The results show a very high success in detection and recognition of road signs, even under the challenging conditions such as discoloration, deformation and in spite of partial occlusions.

  13. Detection and 3D reconstruction of traffic signs from multiple view color images

    NASA Astrophysics Data System (ADS)

    Soheilian, Bahman; Paparoditis, Nicolas; Vallet, Bruno

    2013-03-01

    3D reconstruction of traffic signs is of great interest in many applications such as image-based localization and navigation. In order to reflect the reality, the reconstruction process should meet both accuracy and precision. In order to reach such a valid reconstruction from calibrated multi-view images, accurate and precise extraction of signs in every individual view is a must. This paper presents first an automatic pipeline for identifying and extracting the silhouette of signs in every individual image. Then, a multi-view constrained 3D reconstruction algorithm provides an optimum 3D silhouette for the detected signs. The first step called detection, tackles with a color-based segmentation to generate ROIs (Region of Interests) in image. The shape of every ROI is estimated by fitting an ellipse, a quadrilateral or a triangle to edge points. A ROI is rejected if none of the three shapes can be fitted sufficiently precisely. Thanks to the estimated shape the remained candidates ROIs are rectified to remove the perspective distortion and then matched with a set of reference signs using textural information. Poor matches are rejected and the types of remained ones are identified. The output of the detection algorithm is a set of identified road signs whose silhouette in image plane is represented by and ellipse, a quadrilateral or a triangle. The 3D reconstruction process is based on a hypothesis generation and verification. Hypotheses are generated by a stereo matching approach taking into account epipolar geometry and also the similarity of the categories. The hypotheses that are plausibly correspond to the same 3D road sign are identified and grouped during this process. Finally, all the hypotheses of the same group are merged to generate a unique 3D road sign by a multi-view algorithm integrating a priori knowledges about 3D shape of road signs as constraints. The algorithm is assessed on real and synthetic images and reached and average accuracy of 3.5cm for

  14. Ultrarapid Detection of Pathogenic Bacteria Using a 3D Immunomagnetic Flow Assay

    PubMed Central

    Lee, Wonjae; Kwon, Donghoon; Chung, Boram; Jung, Gyoo Yeol; Au, Anthony; Folch, Albert; Jeon, Sangmin

    2015-01-01

    We developed a novel 3D immunomagnetic flow assay for the rapid detection of pathogenic bacteria in a large-volume food sample. Antibody-functionalized magnetic nanoparticle clusters (AbMNCs) were magnetically immobilized on the surfaces of a 3D-printed cylindrical microchannel. The injection of a Salmonella-spiked sample solution into the microchannel produced instant binding between the AbMNCs and the Salmonella bacteria due to their efficient collisions. Nearly perfect capture of the AbMNCs and AbMNCs-Salmonella complexes was achieved under a high flow rate by stacking permanent magnets with spacers inside the cylindrical separator to maximize the magnetic force. The concentration of the bacteria in solution was determined using ATP luminescence measurements. The detection limit was better than 10 cfu/mL, and the overall assay time, including the binding, rinsing, and detection steps for a 10 mL sample took less than 3 min. To our knowledge, the 3D immunomagnetic flow assay described here provides the fastest high-sensitivity, high-capacity method for the detection of pathogenic bacteria. PMID:24856003

  15. Ultrarapid detection of pathogenic bacteria using a 3D immunomagnetic flow assay.

    PubMed

    Lee, Wonjae; Kwon, Donghoon; Chung, Boram; Jung, Gyoo Yeol; Au, Anthony; Folch, Albert; Jeon, Sangmin

    2014-07-01

    We developed a novel 3D immunomagnetic flow assay for the rapid detection of pathogenic bacteria in a large-volume food sample. Antibody-functionalized magnetic nanoparticle clusters (AbMNCs) were magnetically immobilized on the surfaces of a 3D-printed cylindrical microchannel. The injection of a Salmonella-spiked sample solution into the microchannel produced instant binding between the AbMNCs and the Salmonella bacteria due to their efficient collisions. Nearly perfect capture of the AbMNCs and AbMNCs-Salmonella complexes was achieved under a high flow rate by stacking permanent magnets with spacers inside the cylindrical separator to maximize the magnetic force. The concentration of the bacteria in solution was determined using ATP luminescence measurements. The detection limit was better than 10 cfu/mL, and the overall assay time, including the binding, rinsing, and detection steps for a 10 mL sample took less than 3 min. To our knowledge, the 3D immunomagnetic flow assay described here provides the fastest high-sensitivity, high-capacity method for the detection of pathogenic bacteria.

  16. 3D-printed and CNC milled flow-cells for chemiluminescence detection.

    PubMed

    Spilstead, Kara B; Learey, Jessica J; Doeven, Egan H; Barbante, Gregory J; Mohr, Stephan; Barnett, Neil W; Terry, Jessica M; Hall, Robynne M; Francis, Paul S

    2014-08-01

    Herein we explore modern fabrication techniques for the development of chemiluminescence detection flow-cells with features not attainable using the traditional coiled tubing approach. This includes the first 3D-printed chemiluminescence flow-cells, and a milled flow-cell designed to split the analyte stream into two separate detection zones within the same polymer chip. The flow-cells are compared to conventional detection systems using flow injection analysis (FIA) and high performance liquid chromatography (HPLC), with the fast chemiluminescence reactions of an acidic potassium permanganate reagent with morphine and a series of adrenergic phenolic amines. PMID:24881540

  17. Decoupling object detection and categorization.

    PubMed

    Mack, Michael L; Palmeri, Thomas J

    2010-10-01

    We investigated whether there exists a behavioral dependency between object detection and categorization. Previous work (Grill-Spector & Kanwisher, 2005) suggests that object detection and basic-level categorization may be the very same perceptual mechanism: As objects are parsed from the background they are categorized at the basic level. In the current study, we decouple object detection from categorization by manipulating the between-category contrast of the categorization decision. With a superordinate-level contrast with people as one of the target categories (e.g., cars vs. people), which replicates Grill-Spector and Kanwisher, we found that success at object detection depended on success at basic-level categorization and vice versa. But with a basic-level contrast (e.g., cars vs. boats) or superordinate-level contrast without people as a target category (e.g., dog vs. boat), success at object detection did not depend on success at basic-level categorization. Successful object detection could occur without successful basic-level categorization. Object detection and basic-level categorization do not seem to occur within the same early stage of visual processing.

  18. Detection of micromechanical deformation under rigid body displacement using twin-pulsed 3D digital holography

    NASA Astrophysics Data System (ADS)

    Perez-Lopez, Carlos; Hernandez-Montes, Maria del Socorro; Mendoza-Santoyo, Fernando

    2005-02-01

    Twin-pulsed digital holography in its 3D set up is used to recover exclusively the micro-mechanical deformation of an object. The test object is allowed to have rigid body movements such as rotation and translation, with the result that the fringe patterns contain information of the latter and the object deformation, a feature that may significantly modify the interpretation of the results. Experimental results from a flat metal plate subject to micro stress and a displacement in the x-z plane are presented to demonstrate that using this optical method it is possible to recover exclusively the contribution of the micro stress.

  19. Detecting and estimating errors in 3D restoration methods using analog models.

    NASA Astrophysics Data System (ADS)

    José Ramón, Ma; Pueyo, Emilio L.; Briz, José Luis

    2015-04-01

    Some geological scenarios may be important for a number of socio-economic reasons, such as water or energy resources, but the available underground information is often limited, scarce and heterogeneous. A truly 3D reconstruction, which is still necessary during the decision-making process, may have important social and economic implications. For this reason, restoration methods were developed. By honoring some geometric or mechanical laws, they help build a reliable image of the subsurface. Pioneer methods were firstly applied in 2D (balanced and restored cross-sections) during the sixties and seventies. Later on, and due to the improvements of computational capabilities, they were extended to 3D. Currently, there are some academic and commercial restoration solutions; Unfold by the Université de Grenoble, Move by Midland Valley Exploration, Kine3D (on gOcad code) by Paradigm, Dynel3D by igeoss-Schlumberger. We have developed our own restoration method, Pmag3Drest (IGME-Universidad de Zaragoza), which is designed to tackle complex geometrical scenarios using paleomagnetic vectors as a pseudo-3D indicator of deformation. However, all these methods have limitations based on the assumptions they need to establish. For this reason, detecting and estimating uncertainty in 3D restoration methods is of key importance to trust the reconstructions. Checking the reliability and the internal consistency of every method, as well as to compare the results among restoration tools, is a critical issue never tackled so far because of the impossibility to test out the results in Nature. To overcome this problem we have developed a technique using analog models. We built complex geometric models inspired in real cases of superposed and/or conical folding at laboratory scale. The stratigraphic volumes were modeled using EVA sheets (ethylene vinyl acetate). Their rheology (tensile and tear strength, elongation, density etc) and thickness can be chosen among a large number of values

  20. Accurate Automatic Detection of Densely Distributed Cell Nuclei in 3D Space

    PubMed Central

    Tokunaga, Terumasa; Kanamori, Manami; Teramoto, Takayuki; Jang, Moon Sun; Kuge, Sayuri; Ishihara, Takeshi; Yoshida, Ryo; Iino, Yuichi

    2016-01-01

    To measure the activity of neurons using whole-brain activity imaging, precise detection of each neuron or its nucleus is required. In the head region of the nematode C. elegans, the neuronal cell bodies are distributed densely in three-dimensional (3D) space. However, no existing computational methods of image analysis can separate them with sufficient accuracy. Here we propose a highly accurate segmentation method based on the curvatures of the iso-intensity surfaces. To obtain accurate positions of nuclei, we also developed a new procedure for least squares fitting with a Gaussian mixture model. Combining these methods enables accurate detection of densely distributed cell nuclei in a 3D space. The proposed method was implemented as a graphical user interface program that allows visualization and correction of the results of automatic detection. Additionally, the proposed method was applied to time-lapse 3D calcium imaging data, and most of the nuclei in the images were successfully tracked and measured. PMID:27271939

  1. Accurate Automatic Detection of Densely Distributed Cell Nuclei in 3D Space.

    PubMed

    Toyoshima, Yu; Tokunaga, Terumasa; Hirose, Osamu; Kanamori, Manami; Teramoto, Takayuki; Jang, Moon Sun; Kuge, Sayuri; Ishihara, Takeshi; Yoshida, Ryo; Iino, Yuichi

    2016-06-01

    To measure the activity of neurons using whole-brain activity imaging, precise detection of each neuron or its nucleus is required. In the head region of the nematode C. elegans, the neuronal cell bodies are distributed densely in three-dimensional (3D) space. However, no existing computational methods of image analysis can separate them with sufficient accuracy. Here we propose a highly accurate segmentation method based on the curvatures of the iso-intensity surfaces. To obtain accurate positions of nuclei, we also developed a new procedure for least squares fitting with a Gaussian mixture model. Combining these methods enables accurate detection of densely distributed cell nuclei in a 3D space. The proposed method was implemented as a graphical user interface program that allows visualization and correction of the results of automatic detection. Additionally, the proposed method was applied to time-lapse 3D calcium imaging data, and most of the nuclei in the images were successfully tracked and measured. PMID:27271939

  2. 3D model-based detection and tracking for space autonomous and uncooperative rendezvous

    NASA Astrophysics Data System (ADS)

    Shang, Yang; Zhang, Yueqiang; Liu, Haibo

    2015-10-01

    In order to fully navigate using a vision sensor, a 3D edge model based detection and tracking technique was developed. Firstly, we proposed a target detection strategy over a sequence of several images from the 3D model to initialize the tracking. The overall purpose of such approach is to robustly match each image with the model views of the target. Thus we designed a line segment detection and matching method based on the multi-scale space technology. Experiments on real images showed that our method is highly robust under various image changes. Secondly, we proposed a method based on 3D particle filter (PF) coupled with M-estimation to track and estimate the pose of the target efficiently. In the proposed approach, a similarity observation model was designed according to a new distance function of line segments. Then, based on the tracking results of PF, the pose was optimized using M-estimation. Experiments indicated that the proposed method can effectively track and accurately estimate the pose of freely moving target in unconstrained environment.

  3. Multi-resolution Gabor wavelet feature extraction for needle detection in 3D ultrasound

    NASA Astrophysics Data System (ADS)

    Pourtaherian, Arash; Zinger, Svitlana; Mihajlovic, Nenad; de With, Peter H. N.; Huang, Jinfeng; Ng, Gary C.; Korsten, Hendrikus H. M.

    2015-12-01

    Ultrasound imaging is employed for needle guidance in various minimally invasive procedures such as biopsy guidance, regional anesthesia and brachytherapy. Unfortunately, a needle guidance using 2D ultrasound is very challenging, due to a poor needle visibility and a limited field of view. Nowadays, 3D ultrasound systems are available and more widely used. Consequently, with an appropriate 3D image-based needle detection technique, needle guidance and interventions may significantly be improved and simplified. In this paper, we present a multi-resolution Gabor transformation for an automated and reliable extraction of the needle-like structures in a 3D ultrasound volume. We study and identify the best combination of the Gabor wavelet frequencies. High precision in detecting the needle voxels leads to a robust and accurate localization of the needle for the intervention support. Evaluation in several ex-vivo cases shows that the multi-resolution analysis significantly improves the precision of the needle voxel detection from 0.23 to 0.32 at a high recall rate of 0.75 (gain 40%), where a better robustness and confidence were confirmed in the practical experiments.

  4. Accurate Automatic Detection of Densely Distributed Cell Nuclei in 3D Space.

    PubMed

    Toyoshima, Yu; Tokunaga, Terumasa; Hirose, Osamu; Kanamori, Manami; Teramoto, Takayuki; Jang, Moon Sun; Kuge, Sayuri; Ishihara, Takeshi; Yoshida, Ryo; Iino, Yuichi

    2016-06-01

    To measure the activity of neurons using whole-brain activity imaging, precise detection of each neuron or its nucleus is required. In the head region of the nematode C. elegans, the neuronal cell bodies are distributed densely in three-dimensional (3D) space. However, no existing computational methods of image analysis can separate them with sufficient accuracy. Here we propose a highly accurate segmentation method based on the curvatures of the iso-intensity surfaces. To obtain accurate positions of nuclei, we also developed a new procedure for least squares fitting with a Gaussian mixture model. Combining these methods enables accurate detection of densely distributed cell nuclei in a 3D space. The proposed method was implemented as a graphical user interface program that allows visualization and correction of the results of automatic detection. Additionally, the proposed method was applied to time-lapse 3D calcium imaging data, and most of the nuclei in the images were successfully tracked and measured.

  5. A fast 3-D object recognition algorithm for the vision system of a special-purpose dexterous manipulator

    NASA Technical Reports Server (NTRS)

    Hung, Stephen H. Y.

    1989-01-01

    A fast 3-D object recognition algorithm that can be used as a quick-look subsystem to the vision system for the Special-Purpose Dexterous Manipulator (SPDM) is described. Global features that can be easily computed from range data are used to characterize the images of a viewer-centered model of an object. This algorithm will speed up the processing by eliminating the low level processing whenever possible. It may identify the object, reject a set of bad data in the early stage, or create a better environment for a more powerful algorithm to carry the work further.

  6. Robust 3D object localization and pose estimation for random bin picking with the 3DMaMa algorithm

    NASA Astrophysics Data System (ADS)

    Skotheim, Øystein; Thielemann, Jens T.; Berge, Asbjørn; Sommerfelt, Arne

    2010-02-01

    Enabling robots to automatically locate and pick up randomly placed and oriented objects from a bin is an important challenge in factory automation, replacing tedious and heavy manual labor. A system should be able to recognize and locate objects with a predefined shape and estimate the position with the precision necessary for a gripping robot to pick it up. We describe a system that consists of a structured light instrument for capturing 3D data and a robust approach for object location and pose estimation. The method does not depend on segmentation of range images, but instead searches through pairs of 2D manifolds to localize candidates for object match. This leads to an algorithm that is not very sensitive to scene complexity or the number of objects in the scene. Furthermore, the strategy for candidate search is easily reconfigurable to arbitrary objects. Experiments reported in this paper show the utility of the method on a general random bin picking problem, in this paper exemplified by localization of car parts with random position and orientation. Full pose estimation is done in less than 380 ms per image. We believe that the method is applicable for a wide range of industrial automation problems where precise localization of 3D objects in a scene is needed.

  7. Recognition of 3-D symmetric objects from range images in automated assembly tasks

    NASA Technical Reports Server (NTRS)

    Alvertos, Nicolas; Dcunha, Ivan

    1990-01-01

    A new technique is presented for the three dimensional recognition of symmetric objects from range images. Beginning from the implicit representation of quadrics, a set of ten coefficients is determined for symmetric objects like spheres, cones, cylinders, ellipsoids, and parallelepipeds. Instead of using these ten coefficients trying to fit them to smooth surfaces (patches) based on the traditional way of determining curvatures, a new approach based on two dimensional geometry is used. For each symmetric object, a unique set of two dimensional curves is obtained from the various angles at which the object is intersected with a plane. Using the same ten coefficients obtained earlier and based on the discriminant method, each of these curves is classified as a parabola, circle, ellipse, or hyperbola. Each symmetric object is found to possess a unique set of these two dimensional curves whereby it can be differentiated from the others. It is shown that instead of using the three dimensional discriminant which involves evaluation of the rank of its matrix, it is sufficient to use the two dimensional discriminant which only requires three arithmetic operations.

  8. Low-Cost Impact Detection and Location for Automated Inspections of 3D Metallic Based Structures

    PubMed Central

    Morón, Carlos; Portilla, Marina P.; Somolinos, José A.; Morales, Rafael

    2015-01-01

    This paper describes a new low-cost means to detect and locate mechanical impacts (collisions) on a 3D metal-based structure. We employ the simple and reasonably hypothesis that the use of a homogeneous material will allow certain details of the impact to be automatically determined by measuring the time delays of acoustic wave propagation throughout the 3D structure. The location of strategic piezoelectric sensors on the structure and an electronic-computerized system has allowed us to determine the instant and position at which the impact is produced. The proposed automatic system allows us to fully integrate impact point detection and the task of inspecting the point or zone at which this impact occurs. What is more, the proposed method can be easily integrated into a robot-based inspection system capable of moving over 3D metallic structures, thus avoiding (or minimizing) the need for direct human intervention. Experimental results are provided to show the effectiveness of the proposed approach. PMID:26029951

  9. Multiscale segmentation method for small inclusion detection in 3D industrial computed tomography

    NASA Astrophysics Data System (ADS)

    Zauner, G.; Harrer, B.; Angermaier, D.; Reiter, M.; Kastner, J.

    2007-06-01

    In this paper a new segmentation method for highly precise inclusion detection in 3D X-ray computed tomography (CT), based on multiresolution denoising methods, is presented. The aim of this work is the automatic 3D-segmentation of small graphite inclusions in cast iron samples. Industrial X-ray computed tomography of metallic samples often suffers from imaging artifacts (e.g. cupping effects) which result in unwanted background image structures, making automated segmentation a difficult task. Additionally, small spatial structures (inclusions and voids) are generally difficult to detect e.g. by standard region based methods like watershed segmentation. Finally, image noise (assuming a Poisson noise characteristic) and the large amount of 3D data have to be considered to obtain good results. The approach presented is based on image subtraction of two different representations of the image under consideration. The first image represents the low spatial frequency content derived by means of wavelet filtering based on the 'a trous' algorithm (i.e. the 'background' content) assuming standard Gaussian noise. The second image is derived by applying a multiresolution denoising scheme based on 'platelet'-filtering, which can produce highly accurate intensity and density estimates assuming Poisson noise. It is shown that the resulting arithmetic difference between these two images can give highly accurate segmentation results with respect to finding small spatial structures in heavily cluttered background structures. Experimental results of industrial CT measurements are presented showing the practicability and reliability of this approach for the proposed task.

  10. Research into a Single-aperture Light Field Camera System to Obtain Passive Ground-based 3D Imagery of LEO Objects

    NASA Astrophysics Data System (ADS)

    Bechis, K.; Pitruzzello, A.

    2014-09-01

    This presentation describes our ongoing research into using a ground-based light field camera to obtain passive, single-aperture 3D imagery of LEO objects. Light field cameras are an emerging and rapidly evolving technology for passive 3D imaging with a single optical sensor. The cameras use an array of lenslets placed in front of the camera focal plane, which provides angle of arrival information for light rays originating from across the target, allowing range to target and 3D image to be obtained from a single image using monocular optics. The technology, which has been commercially available for less than four years, has the potential to replace dual-sensor systems such as stereo cameras, dual radar-optical systems, and optical-LIDAR fused systems, thus reducing size, weight, cost, and complexity. We have developed a prototype system for passive ranging and 3D imaging using a commercial light field camera and custom light field image processing algorithms. Our light field camera system has been demonstrated for ground-target surveillance and threat detection applications, and this paper presents results of our research thus far into applying this technology to the 3D imaging of LEO objects. The prototype 3D imaging camera system developed by Northrop Grumman uses a Raytrix R5 C2GigE light field camera connected to a Windows computer with an nVidia graphics processing unit (GPU). The system has a frame rate of 30 Hz, and a software control interface allows for automated camera triggering and light field image acquisition to disk. Custom image processing software then performs the following steps: (1) image refocusing, (2) change detection, (3) range finding, and (4) 3D reconstruction. In Step (1), a series of 2D images are generated from each light field image; the 2D images can be refocused at up to 100 different depths. Currently, steps (1) through (3) are automated, while step (4) requires some user interaction. A key requirement for light field camera

  11. PLANETARY NEBULAE DETECTED IN THE SPITZER SPACE TELESCOPE GLIMPSE 3D LEGACY SURVEY

    SciTech Connect

    Zhang Yong; Hsia, Chih-Hao; Kwok, Sun E-mail: xiazh@hku.hk

    2012-01-20

    We used the data from the Spitzer Legacy Infrared Mid-Plane Survey Extraordinaire (GLIMPSE) to investigate the mid-infrared (MIR) properties of planetary nebulae (PNs) and PN candidates. In previous studies of GLIMPSE I and II data, we have shown that these MIR data are very useful in distinguishing PNs from other emission-line objects. In the present paper, we focus on the PNs in the field of the GLIMPSE 3D survey, which has a more extensive latitude coverage. We found a total of 90 Macquarie-AAO-Strasbourg (MASH) and MASH II PNs and 101 known PNs to have visible MIR counterparts in the GLIMPSE 3D survey area. The images and photometry of these PNs are presented. Combining the derived IRAC photometry at 3.6, 4.5, 5.8, and 8.0 {mu}m with the existing photometric measurements from other infrared catalogs, we are able to construct spectral energy distributions (SEDs) of these PNs. Among the most notable objects in this survey is the PN M1-41, whose GLIMPSE 3D image reveals a large bipolar structure of more than 3 arcmin in extent.

  12. Microwave and camera sensor fusion for the shape extraction of metallic 3D space objects

    NASA Technical Reports Server (NTRS)

    Shaw, Scott W.; Defigueiredo, Rui J. P.; Krishen, Kumar

    1989-01-01

    The vacuum of space presents special problems for optical image sensors. Metallic objects in this environment can produce intense specular reflections and deep shadows. By combining the polarized RCS with an incomplete camera image, it has become possible to better determine the shape of some simple three-dimensional objects. The radar data are used in an iterative procedure that generates successive approximations to the target shape by minimizing the error between computed scattering cross-sections and the observed radar returns. Favorable results have been obtained for simulations and experiments reconstructing plates, ellipsoids, and arbitrary surfaces.

  13. Robust volumetric change detection using mutual information with 3D fractals

    NASA Astrophysics Data System (ADS)

    Rahmes, Mark; Akbari, Morris; Henning, Ronda; Pokorny, John

    2014-06-01

    We discuss a robust method for quantifying change of multi-temporal remote sensing point data in the presence of affine registration errors. Three dimensional image processing algorithms can be used to extract and model an electronic module, consisting of a self-contained assembly of electronic components and circuitry, using an ultrasound scanning sensor. Mutual information (MI) is an effective measure of change. We propose a multi-resolution 3D fractal algorithm which is a novel extension to MI or regional mutual information (RMI). Our method is called fractal mutual information (FMI). This extension efficiently takes neighborhood fractal patterns of corresponding voxels (3D pixels) into account. The goal of this system is to quantify the change in a module due to tampering and provide a method for quantitative and qualitative change detection and analysis.

  14. Gray-level transformation and Canny edge detection for 3D seismic discontinuity enhancement

    NASA Astrophysics Data System (ADS)

    Di, Haibin; Gao, Dengliang

    2014-11-01

    In a 3D seismic survey, detecting seismic discontinuities is vital to robust structural and stratigraphic analysis in the subsurface. Previous methods have difficulty highlighting subtle discontinuities from seismic data in cases where the local amplitude variation is of non-zero mean. This study proposes implementing a gray-level transformation and the Canny edge detector for improved imaging of discontinuities. Specifically, the new process transforms seismic signals to be of zero mean and helps amplify subtle discontinuities, leading to an enhanced visualization for structural and stratigraphic details. Applications to various 3D seismic datasets demonstrate that the new algorithm helps better define channels, faults, and fractures than the traditional similarity, amplitude gradient, and semblance attributes.

  15. Robust Curb Detection with Fusion of 3D-Lidar and Camera Data

    PubMed Central

    Tan, Jun; Li, Jian; An, Xiangjing; He, Hangen

    2014-01-01

    Curb detection is an essential component of Autonomous Land Vehicles (ALV), especially important for safe driving in urban environments. In this paper, we propose a fusion-based curb detection method through exploiting 3D-Lidar and camera data. More specifically, we first fuse the sparse 3D-Lidar points and high-resolution camera images together to recover a dense depth image of the captured scene. Based on the recovered dense depth image, we propose a filter-based method to estimate the normal direction within the image. Then, by using the multi-scale normal patterns based on the curb's geometric property, curb point features fitting the patterns are detected in the normal image row by row. After that, we construct a Markov Chain to model the consistency of curb points which utilizes the continuous property of the curb, and thus the optimal curb path which links the curb points together can be efficiently estimated by dynamic programming. Finally, we perform post-processing operations to filter the outliers, parameterize the curbs and give the confidence scores on the detected curbs. Extensive evaluations clearly show that our proposed method can detect curbs with strong robustness at real-time speed for both static and dynamic scenes. PMID:24854364

  16. Robust curb detection with fusion of 3D-Lidar and camera data.

    PubMed

    Tan, Jun; Li, Jian; An, Xiangjing; He, Hangen

    2014-05-21

    Curb detection is an essential component of Autonomous Land Vehicles (ALV), especially important for safe driving in urban environments. In this paper, we propose a fusion-based curb detection method through exploiting 3D-Lidar and camera data. More specifically, we first fuse the sparse 3D-Lidar points and high-resolution camera images together to recover a dense depth image of the captured scene. Based on the recovered dense depth image, we propose a filter-based method to estimate the normal direction within the image. Then, by using the multi-scale normal patterns based on the curb's geometric property, curb point features fitting the patterns are detected in the normal image row by row. After that, we construct a Markov Chain to model the consistency of curb points which utilizes the continuous property of the curb, and thus the optimal curb path which links the curb points together can be efficiently estimated by dynamic programming. Finally, we perform post-processing operations to filter the outliers, parameterize the curbs and give the confidence scores on the detected curbs. Extensive evaluations clearly show that our proposed method can detect curbs with strong robustness at real-time speed for both static and dynamic scenes.

  17. Robust curb detection with fusion of 3D-Lidar and camera data.

    PubMed

    Tan, Jun; Li, Jian; An, Xiangjing; He, Hangen

    2014-01-01

    Curb detection is an essential component of Autonomous Land Vehicles (ALV), especially important for safe driving in urban environments. In this paper, we propose a fusion-based curb detection method through exploiting 3D-Lidar and camera data. More specifically, we first fuse the sparse 3D-Lidar points and high-resolution camera images together to recover a dense depth image of the captured scene. Based on the recovered dense depth image, we propose a filter-based method to estimate the normal direction within the image. Then, by using the multi-scale normal patterns based on the curb's geometric property, curb point features fitting the patterns are detected in the normal image row by row. After that, we construct a Markov Chain to model the consistency of curb points which utilizes the continuous property of the curb, and thus the optimal curb path which links the curb points together can be efficiently estimated by dynamic programming. Finally, we perform post-processing operations to filter the outliers, parameterize the curbs and give the confidence scores on the detected curbs. Extensive evaluations clearly show that our proposed method can detect curbs with strong robustness at real-time speed for both static and dynamic scenes. PMID:24854364

  18. Nonthreshold-based event detection for 3d environment monitoring in sensor networks

    SciTech Connect

    Li, M.; Liu, Y.H.; Chen, L.

    2008-12-15

    Event detection is a crucial task for wireless sensor network applications, especially environment monitoring. Existing approaches for event detection are mainly based on some predefined threshold values and, thus, are often inaccurate and incapable of capturing complex events. For example, in coal mine monitoring scenarios, gas leakage or water osmosis can hardly be described by the overrun of specified attribute thresholds but some complex pattern in the full-scale view of the environmental data. To address this issue, we propose a nonthreshold-based approach for the real 3D sensor monitoring environment. We employ energy-efficient methods to collect a time series of data maps from the sensor network and detect complex events through matching the gathered data to spatiotemporal data patterns. Finally, we conduct trace-driven simulations to prove the efficacy and efficiency of this approach on detecting events of complex phenomena from real-life records.

  19. Surface classification and detection of latent fingerprints based on 3D surface texture parameters

    NASA Astrophysics Data System (ADS)

    Gruhn, Stefan; Fischer, Robert; Vielhauer, Claus

    2012-06-01

    In the field of latent fingerprint detection in crime scene forensics the classification of surfaces has importance. A new method for the scientific analysis of image based information for forensic science was investigated in the last years. Our image acquisition based on a sensor using Chromatic White Light (CWL) with a lateral resolution up to 2 μm. The used FRT-MicroProf 200 CWL 600 measurement device is able to capture high-resolution intensity and topography images in an optical and contact-less way. In prior work, we have suggested to use 2D surface texture parameters to classify various materials, which was a novel approach in the field of criminalistic forensic using knowledge from surface appearance and a chromatic white light sensor. A meaningful and useful classification of different crime scene specific surfaces is not existent. In this work, we want to extend such considerations by the usage of fourteen 3D surface parameters, called 'Birmingham 14'. In our experiment we define these surface texture parameters and use them to classify ten different materials in this test set-up and create specific material classes. Further it is shown in first experiments, that some surface texture parameters are sensitive to separate fingerprints from carrier surfaces. So far, the use of surface roughness is mainly known within the framework of material quality control. The analysis and classification of the captured 3D-topography images from crime scenes is important for the adaptive preprocessing depending on the surface texture. The adaptive preprocessing in dependency of surface classification is necessary for precise detection because of the wide variety of surface textures. We perform a preliminary study in usage of these 3D surface texture parameters as feature for the fingerprint detection. In combination with a reference sample we show that surface texture parameters can be an indication for a fingerprint and can be a feature in latent fingerprint detection.

  20. Calibration and 3D reconstruction of underwater objects with non-single-view projection model by structured light stereo imaging.

    PubMed

    Wang, Yexin; Negahdaripour, Shahriar; Aykin, Murat D

    2016-08-20

    Establishing the projection model of imaging systems is critical in 3D reconstruction of object shapes from multiple 2D views. When deployed underwater, these are enclosed in waterproof housings with transparent glass ports that generate nonlinear refractions of optical rays at interfaces, leading to invalidation of the commonly assumed single-viewpoint (SVP) model. In this paper, we propose a non-SVP ray tracing model for the calibration of a projector-camera system, employed for 3D reconstruction based on the structured light paradigm. The projector utilizes dot patterns, having established that the contrast loss is less severe than for traditional stripe patterns in highly turbid waters. Experimental results are presented to assess the achieved calibrating accuracy. PMID:27556973

  1. In-hand dexterous manipulation of piecewise-smooth 3-D objects

    SciTech Connect

    Rus, D.

    1999-04-01

    The author presents an algorithm called finger tracking for in-hand manipulation of three-dimensional objects with independent robot fingers. She describes and analyzes the differential control for finger tracking and extends it to on-line continuous control for a set of cooperating robot fingers. She shows experimental data from a simulation. Finally, she discusses global control issues for finger tracking, and computes lower bounds for reorientation by finger tracking. The algorithm is computationally efficient, exact, and takes into consideration the full dynamics of the system.

  2. A new algorithm for evaluating 3D curvature and curvature gradient for improved fracture detection

    NASA Astrophysics Data System (ADS)

    Di, Haibin; Gao, Dengliang

    2014-09-01

    In 3D seismic interpretation, both curvature and curvature gradient are useful seismic attributes for structure characterization and fault detection in the subsurface. However, the existing algorithms are computationally intensive and limited by the lateral resolution for steeply-dipping formations. This study presents new and robust volume-based algorithms that evaluate both curvature and curvature gradient attributes more accurately and effectively. The algorithms first instantaneously fit a local surface to seismic data and then compute attributes using the spatial derivatives of the built surface. Specifically, the curvature algorithm constructs a quadratic surface by using a rectangle 9-node grid cell, whereas the curvature gradient algorithm builds a cubic surface by using a diamond 13-node grid cell. A dip-steering approach based on 3D complex seismic trace analysis is implemented to enhance the accuracy of surface construction and to reduce computational time. Applications to two 3D seismic surveys demonstrate the accuracy and efficiency of the new curvature and curvature gradient algorithms for characterizing faults and fractures in fractured reservoirs.

  3. Detection of cerebral aneurysms in MRA, CTA and 3D-RA data sets

    NASA Astrophysics Data System (ADS)

    Hentschke, Clemens M.; Beuing, Oliver; Nickl, Rosa; Tönnies, Klaus D.

    2012-03-01

    We propose a system to automatically detect cerebral aneurysms in 3D X-ray rotational angiography images (3D-RA), magnetic resonance angiography images (MRA) and computed tomography angiography images (CTA). After image normalization, initial candidates are found by applying a blob-enhancing filter on the data sets. Clusters are computed by a modified k-means algorithm. A post-processing step reduces the false positive (FP) rate on the basis of computed features. This is implemented as a rule-based system that is adapted according to the modality. In MRA, clusters are excluded that are not neighbored to a vessel. As a final step, FP are further reduced by applying a threshold classification on a feature. Our method was tested on 93 angiographic data sets containing aneurysm and non-aneurysm cases. We achieved 95 % sensitivity with an average rate of 2.6 FP per data set (FP/DS) in case of 3D-RA, 89 % sensitivity at 6.6 FP/DS for MRA and 95 % sensitivity at 37.6 FP/DS with CTA, respectively. We showed that our post-processing approach eliminates FP in MRA with only a slight decrease of sensitivity. In contrast to other approaches, our algorithm does not require a vessel segmentation and does not require training of distributional properties.

  4. Intrinsic spatial shift of local focus metric curves in digital inline holography for accurate 3D morphology measurement of irregular micro-objects

    NASA Astrophysics Data System (ADS)

    Wu, Yingchun; Wu, Xuecheng; Lebrun, Denis; Brunel, Marc; Coëtmellec, Sébastien; Lesouhaitier, Olivier; Chen, Jia; Gréhan, Gérard

    2016-09-01

    A theoretical model of digital inline holography system reveals that the local focus metric curves (FMCs) of different parts of an irregular micro-object present spatial shift in the depth direction which is resulted from the depth shift. Thus, the 3D morphology of an irregular micro-object can be accurately measured using the cross correlation of the local FMCs. This method retrieves the 3D depth information directly, avoiding the uncertainty inherited from the depth position determination. Typical 3D morphology measurements, including the 3D boundary lines of tilted carbon fibers and irregular coal particles, and the 3D swimming gesture of a live Caenorhabdities elegans, are presented.

  5. Acoustic Detection of Buried Objects

    NASA Astrophysics Data System (ADS)

    Ivansson, S.; Jacobsen, N.; Levonen, M.; Nilsson, B.; Moren, P.

    2001-12-01

    The capability to detect objects buried in the sea bottom is important for many reasons. For example bottom mines as well as dumped chemical munitions can be expected to have been buried by the sedimentation. Standard sub-bottom profilers that are routinely used for mapping sediment structures do not have good enough resolutions to detect small buried objects. Parametric sonar, with a much smaller lobe, is much more appropriate. In the report, we show results from measurements with a parametric sonar, mounted on a ROV (remotely operated vehicle). The measurements were made in the archipelago of Stockholm with a test object buried in clay. Two techniques were used to improve the detection capability, image processing and FARIM analysis. Concerning image processing, median filtering turns out to provide the best results. Isolated noisy pings are effectively suppressed in this way. FARIM analysis can be used to estimate roughness and impedance of the bottom. Our experiments show that a buried object can often be detected by an anomaly in the impedance estimate. Among three tested center frequencies for the emitted pulse, 5, 10 and 20 kHz, the highest frequency (20 kHz) turns out to provide the best detection capability. This is true for the image processing results as well as for the FARIM results. We have tried bistatic techniques to characterize a detected buried object. Sound pulses are emitted towards the object from one direction and the scattered energy is studied at another direction. We show computational results from a recently developed numerical model. The scattered field turns out to be very sensitive to the properties of the object.

  6. Automatic nipple detection on 3D images of an automated breast ultrasound system (ABUS)

    NASA Astrophysics Data System (ADS)

    Javanshir Moghaddam, Mandana; Tan, Tao; Karssemeijer, Nico; Platel, Bram

    2014-03-01

    Recent studies have demonstrated that applying Automated Breast Ultrasound in addition to mammography in women with dense breasts can lead to additional detection of small, early stage breast cancers which are occult in corresponding mammograms. In this paper, we proposed a fully automatic method for detecting the nipple location in 3D ultrasound breast images acquired from Automated Breast Ultrasound Systems. The nipple location is a valuable landmark to report the position of possible abnormalities in a breast or to guide image registration. To detect the nipple location, all images were normalized. Subsequently, features have been extracted in a multi scale approach and classification experiments were performed using a gentle boost classifier to identify the nipple location. The method was applied on a dataset of 100 patients with 294 different 3D ultrasound views from Siemens and U-systems acquisition systems. Our database is a representative sample of cases obtained in clinical practice by four medical centers. The automatic method could accurately locate the nipple in 90% of AP (Anterior-Posterior) views and in 79% of the other views.

  7. Automated kidney detection for 3D ultrasound using scan line searching

    NASA Astrophysics Data System (ADS)

    Noll, Matthias; Nadolny, Anne; Wesarg, Stefan

    2016-04-01

    Ultrasound (U/S) is a fast and non-expensive imaging modality that is used for the examination of various anatomical structures, e.g. the kidneys. One important task for automatic organ tracking or computer-aided diagnosis is the identification of the organ region. During this process the exact information about the transducer location and orientation is usually unavailable. This renders the implementation of such automatic methods exceedingly challenging. In this work we like to introduce a new automatic method for the detection of the kidney in 3D U/S images. This novel technique analyses the U/S image data along virtual scan lines. Here, characteristic texture changes when entering and leaving the symmetric tissue regions of the renal cortex are searched for. A subsequent feature accumulation along a second scan direction produces a 2D heat map of renal cortex candidates, from which the kidney location is extracted in two steps. First, the strongest candidate as well as its counterpart are extracted by heat map intensity ranking and renal cortex size analysis. This process exploits the heat map gap caused by the renal pelvis region. Substituting the renal pelvis detection with this combined cortex tissue feature increases the detection robustness. In contrast to model based methods that generate characteristic pattern matches, our method is simpler and therefore faster. An evaluation performed on 61 3D U/S data sets showed, that in 55 cases showing none or minor shadowing the kidney location could be correctly identified.

  8. Electrochemical detection of lung cancer specific microRNAs using 3D DNA origami nanostructures.

    PubMed

    Liu, Shuopeng; Su, Wenqiong; Li, Zonglin; Ding, Xianting

    2015-09-15

    Recent reports have indicated that aberrant expression of microRNAs is highly correlated with occurrence of lung cancer. Therefore, highly sensitive detection of lung cancer specific microRNAs provides an attractive approach in lung cancer early diagnostics. Herein, we designed 3D DNA origami structure that enables electrochemical detection of lung cancer related microRNAs. The 3D DNA origami structure is constituted of a ferrocene-tagged DNA of stem-loop structure combined with a thiolated tetrahedron DNA nanostructure at the bottom. The top portion hybridized with the lung cancer correlated microRNA, while the bottom portion was self-assembled on gold disk electrode surface, which was modified with gold nanoparticles (Au NPs) and blocked with mercaptoethanol (MCH). The preparation process and the performance of the proposed electrochemical genosensor were characterized by scanning electron microscopy (SEM), atomic force microscopy (AFM), cyclic voltammetry (CV) and differential pulse voltammetry (DPV). Under the optimal conditions, the developed genosensor had a detection limit of 10 pM and a good linearity with microRNA concentration ranging from 100 pM to 1 µM, which showed a great potential in highly sensitive clinical cancer diagnosis application.

  9. Calculations of Arctic ozone chemistry using objectively analyzed data in a 3-D CTM

    NASA Technical Reports Server (NTRS)

    Kaminski, J. W.; Mcconnell, J. C.; Sandilands, J. W.

    1994-01-01

    A three-dimensional chemical transport model (CTM) (Kaminski, 1992) has been used to study the evolution of the Arctic ozone during the winter of 1992. The continuity equation has been solved using a spectral method with Rhomboidal 15 (R15) truncation and leap-frog time stepping. Six-hourly meteorological fields from the Canadian Meteorological Center global objective analysis routines run at T79 were degraded to the model resolution. In addition, they were interpolated to the model time grid and were used to drive the model from the surface to 10 mb. In the model, processing of Cl(x) occurred over Arctic latitudes but some of the initial products were still present by mid-January. Also, the large amounts of ClO formed in the model in early January were converted to ClNO3. The results suggest that the model resolution may be insufficient to resolve the details of the Arctic transport during this time period. In particular, the wind field does not move the ClO(x) 'cloud' to the south over Europe as seen in the MLS measurements.

  10. Objective assessment, repeatability, and agreement of shoulder ROM with a 3D gyroscope

    PubMed Central

    2013-01-01

    Background Assessment of shoulder mobility is essential for diagnosis and clinical follow-up of shoulder diseases. Only a few highly sophisticated instruments for objective measurements of shoulder mobility are available. The recently introduced DynaPort MiniMod TriGyro ShoulderTest-System (DP) was validated earlier in laboratory trials. We aimed to assess the precision (repeatability) and agreement of this instrument in human subjects, as compared to the conventional goniometer. Methods The DP is a small, light-weight, three-dimensional gyroscope that can be fixed on the distal upper arm, recording shoulder abduction, flexion, and rotation. Twenty-one subjects (42 shoulders) were included for analysis. Two subsequent assessments of the same subject with a 30-minute delay in testing of each shoulder were performed with the DP in two directions (flexion and abduction), and simultaneously correlated with the measurements of a conventional goniometer. All assessments were performed by one observer. Repeatability for each method was determined and compared as the statistical variance between two repeated measurements. Agreement was illustrated by Bland-Altman-Plots with 95% limits of agreement. Statistical analysis was performed with a linear mixed regression model. Variance for repeated measurements by the same method was also estimated and compared with the likelihood-ratio test. Results Evaluation of abduction showed significantly better repeatability for the DP compared to the conventional goniometer (error variance: DP = 0.89, goniometer = 8.58, p = 0.025). No significant differences were found for flexion (DP = 1.52, goniometer = 5.94, p = 0.09). Agreement assessment was performed for flexion for mean differences of 0.27° with 95% limit of agreement ranging from −7.97° to 8.51°. For abduction, the mean differences were 1.19° with a 95% limit of agreement ranging from −9.07° to 11.46°. Conclusion In summary, DP demonstrated a high precision even higher

  11. Segmentation of complex objects with non-spherical topologies from volumetric medical images using 3D livewire

    NASA Astrophysics Data System (ADS)

    Poon, Kelvin; Hamarneh, Ghassan; Abugharbieh, Rafeef

    2007-03-01

    Segmentation of 3D data is one of the most challenging tasks in medical image analysis. While reliable automatic methods are typically preferred, their success is often hindered by poor image quality and significant variations in anatomy. Recent years have thus seen an increasing interest in the development of semi-automated segmentation methods that combine computational tools with intuitive, minimal user interaction. In an earlier work, we introduced a highly-automated technique for medical image segmentation, where a 3D extension of the traditional 2D Livewire was proposed. In this paper, we present an enhanced and more powerful 3D Livewire-based segmentation approach with new features designed to primarily enable the handling of complex object topologies that are common in biological structures. The point ordering algorithm we proposed earlier, which automatically pairs up seedpoints in 3D, is improved in this work such that multiple sets of points are allowed to simultaneously exist. Point sets can now be automatically merged and split to accommodate for the presence of concavities, protrusions, and non-spherical topologies. The robustness of the method is further improved by extending the 'turtle algorithm', presented earlier, by using a turtle-path pruning step. Tests on both synthetic and real medical images demonstrate the efficiency, reproducibility, accuracy, and robustness of the proposed approach. Among the examples illustrated is the segmentation of the left and right ventricles from a T1-weighted MRI scan, where an average task time reduction of 84.7% was achieved when compared to a user performing 2D Livewire segmentation on every slice.

  12. Detection of a concealed object

    DOEpatents

    Keller, Paul E [Richland, WA; Hall, Thomas E [Kennewick, WA; McMakin, Douglas L [Richland, WA

    2010-11-16

    Disclosed are systems, methods, devices, and apparatus to determine if a clothed individual is carrying a suspicious, concealed object. This determination includes establishing data corresponding to an image of the individual through interrogation with electromagnetic radiation in the 200 MHz to 1 THz range. In one form, image data corresponding to intensity of reflected radiation and differential depth of the reflecting surface is received and processed to detect the suspicious, concealed object.

  13. Detection of a concealed object

    DOEpatents

    Keller, Paul E.; Hall, Thomas E.; McMakin, Douglas L.

    2008-04-29

    Disclosed are systems, methods, devices, and apparatus to determine if a clothed individual is carrying a suspicious, concealed object. This determination includes establishing data corresponding to an image of the individual through interrogation with electromagnetic radiation in the 200 MHz to 1 THz range. In one form, image data corresponding to intensity of reflected radiation and differential depth of the reflecting surface is received and processed to detect the suspicious, concealed object.

  14. INTERSTELLAR DETECTION OF c-C{sub 3}D{sub 2}

    SciTech Connect

    Spezzano, S.; Bruenken, S.; Schilke, P.; Schlemmer, S.; Caselli, P.; Menten, K. M.; McCarthy, M. C.; Bizzocchi, L.; Trevino-Morales, S. P.; Aikawa, Y.

    2013-06-01

    We report the first interstellar detection of c-C{sub 3}D{sub 2}. Doubly deuterated cyclopropenylidene, a carbene, has been detected toward the starless cores TMC-1C and L1544 using the IRAM 30 m telescope. The J{sub K{sub a,K{sub c}}} = 3{sub 0,3}-2{sub 1,2}, 3{sub 1,3}-2{sub 0,2}, and 2{sub 2,1}-1{sub 1,0} transitions of this species have been observed at 3 mm in both sources. The expected 1:2 intensity ratio has been found in the 3{sub 0,3}-2{sub 1,2} and 3{sub 1,3}-2{sub 0,2} lines, belonging to the para and ortho species, respectively. We also observed lines of the main species, c-C{sub 3}H{sub 2}, singly deuterated c-C{sub 3}HD, and the species with one {sup 13}C off of the principal axis of the molecule, c-H{sup 13}CC{sub 2}H. The lines of c-C{sub 3}D{sub 2} have been observed with high signal-to-noise ratio, better than 7.5{sigma} in TMC-1C and 9{sigma} in L1544. The abundance of doubly deuterated cyclopropenylidene with respect to the normal species is found to be 0.4%-0.8% in TMC-1C and 1.2%-2.1% in L1544. The deuteration of this small hydrocarbon ring is analyzed with a comprehensive gas-grain model, the first including doubly deuterated species. The observed abundances of c-C{sub 3}D{sub 2} can be explained solely by gas-phase processes, supporting the idea that c-C{sub 3}H{sub 2} is a good indicator of gas-phase deuteration.

  15. Reference Frames and 3-D Shape Perception of Pictured Objects: On Verticality and Viewpoint-From-Above

    PubMed Central

    van Doorn, Andrea J.; Wagemans, Johan

    2016-01-01

    Research on the influence of reference frames has generally focused on visual phenomena such as the oblique effect, the subjective visual vertical, the perceptual upright, and ambiguous figures. Another line of research concerns mental rotation studies in which participants had to discriminate between familiar or previously seen 2-D figures or pictures of 3-D objects and their rotated versions. In the present study, we disentangled the influence of the environmental and the viewer-centered reference frame, as classically done, by comparing the performances obtained in various picture and participant orientations. However, this time, the performance is the pictorial relief: the probed 3-D shape percept of the depicted object reconstructed from the local attitude settings of the participant. Comparisons between the pictorial reliefs based on different picture and participant orientations led to two major findings. First, in general, the pictorial reliefs were highly similar if the orientation of the depicted object was vertical with regard to the environmental or the viewer-centered reference frame. Second, a viewpoint-from-above interpretation could almost completely account for the shears occurring between the pictorial reliefs. More specifically, the shears could largely be considered as combinations of slants generated from the viewpoint-from-above, which was determined by the environmental as well as by the viewer-centered reference frame. PMID:27433329

  16. Spun-wrapped aligned nanofiber (SWAN) lithography for fabrication of micro/nano-structures on 3D objects.

    PubMed

    Ye, Zhou; Nain, Amrinder S; Behkam, Bahareh

    2016-07-01

    Fabrication of micro/nano-structures on irregularly shaped substrates and three-dimensional (3D) objects is of significant interest in diverse technological fields. However, it remains a formidable challenge thwarted by limited adaptability of the state-of-the-art nanolithography techniques for nanofabrication on non-planar surfaces. In this work, we introduce Spun-Wrapped Aligned Nanofiber (SWAN) lithography, a versatile, scalable, and cost-effective technique for fabrication of multiscale (nano to microscale) structures on 3D objects without restriction on substrate material and geometry. SWAN lithography combines precise deposition of polymeric nanofiber masks, in aligned single or multilayer configurations, with well-controlled solvent vapor treatment and etching processes to enable high throughput (>10(-7) m(2) s(-1)) and large-area fabrication of sub-50 nm to several micron features with high pattern fidelity. Using this technique, we demonstrate whole-surface nanopatterning of bulk and thin film surfaces of cubes, cylinders, and hyperbola-shaped objects that would be difficult, if not impossible to achieve with existing methods. We demonstrate that the fabricated feature size (b) scales with the fiber mask diameter (D) as b(1.5)∝D. This scaling law is in excellent agreement with theoretical predictions using the Johnson, Kendall, and Roberts (JKR) contact theory, thus providing a rational design framework for fabrication of systems and devices that require precisely designed multiscale features.

  17. Spun-wrapped aligned nanofiber (SWAN) lithography for fabrication of micro/nano-structures on 3D objects.

    PubMed

    Ye, Zhou; Nain, Amrinder S; Behkam, Bahareh

    2016-07-01

    Fabrication of micro/nano-structures on irregularly shaped substrates and three-dimensional (3D) objects is of significant interest in diverse technological fields. However, it remains a formidable challenge thwarted by limited adaptability of the state-of-the-art nanolithography techniques for nanofabrication on non-planar surfaces. In this work, we introduce Spun-Wrapped Aligned Nanofiber (SWAN) lithography, a versatile, scalable, and cost-effective technique for fabrication of multiscale (nano to microscale) structures on 3D objects without restriction on substrate material and geometry. SWAN lithography combines precise deposition of polymeric nanofiber masks, in aligned single or multilayer configurations, with well-controlled solvent vapor treatment and etching processes to enable high throughput (>10(-7) m(2) s(-1)) and large-area fabrication of sub-50 nm to several micron features with high pattern fidelity. Using this technique, we demonstrate whole-surface nanopatterning of bulk and thin film surfaces of cubes, cylinders, and hyperbola-shaped objects that would be difficult, if not impossible to achieve with existing methods. We demonstrate that the fabricated feature size (b) scales with the fiber mask diameter (D) as b(1.5)∝D. This scaling law is in excellent agreement with theoretical predictions using the Johnson, Kendall, and Roberts (JKR) contact theory, thus providing a rational design framework for fabrication of systems and devices that require precisely designed multiscale features. PMID:27283144

  18. Benchmarking of state-of-the-art needle detection algorithms in 3D ultrasound data volumes

    NASA Astrophysics Data System (ADS)

    Pourtaherian, Arash; Zinger, Svitlana; de With, Peter H. N.; Korsten, Hendrikus H. M.; Mihajlovic, Nenad

    2015-03-01

    Ultrasound-guided needle interventions are widely practiced in medical diagnostics and therapy, i.e. for biopsy guidance, regional anesthesia or for brachytherapy. Needle guidance using 2D ultrasound can be very challenging due to the poor needle visibility and the limited field of view. Since 3D ultrasound transducers are becoming more widely used, needle guidance can be improved and simplified with appropriate computer-aided analyses. In this paper, we compare two state-of-the-art 3D needle detection techniques: a technique based on line filtering from literature and a system employing Gabor transformation. Both algorithms utilize supervised classification to pre-select candidate needle voxels in the volume and then fit a model of the needle on the selected voxels. The major differences between the two approaches are in extracting the feature vectors for classification and selecting the criterion for fitting. We evaluate the performance of the two techniques using manually-annotated ground truth in several ex-vivo situations of different complexities, containing three different needle types with various insertion angles. This extensive evaluation provides better understanding on the limitations and advantages of each technique under different acquisition conditions, which is leading to the development of improved techniques for more reliable and accurate localization. Benchmarking results that the Gabor features are better capable of distinguishing the needle voxels in all datasets. Moreover, it is shown that the complete processing chain of the Gabor-based method outperforms the line filtering in accuracy and stability of the detection results.

  19. Parallel phase-shifting digital holography and its application to high-speed 3D imaging of dynamic object

    NASA Astrophysics Data System (ADS)

    Awatsuji, Yasuhiro; Xia, Peng; Wang, Yexin; Matoba, Osamu

    2016-03-01

    Digital holography is a technique of 3D measurement of object. The technique uses an image sensor to record the interference fringe image containing the complex amplitude of object, and numerically reconstructs the complex amplitude by computer. Parallel phase-shifting digital holography is capable of accurate 3D measurement of dynamic object. This is because this technique can reconstruct the complex amplitude of object, on which the undesired images are not superimposed, form a single hologram. The undesired images are the non-diffraction wave and the conjugate image which are associated with holography. In parallel phase-shifting digital holography, a hologram, whose phase of the reference wave is spatially and periodically shifted every other pixel, is recorded to obtain complex amplitude of object by single-shot exposure. The recorded hologram is decomposed into multiple holograms required for phase-shifting digital holography. The complex amplitude of the object is free from the undesired images is reconstructed from the multiple holograms. To validate parallel phase-shifting digital holography, a high-speed parallel phase-shifting digital holography system was constructed. The system consists of a Mach-Zehnder interferometer, a continuous-wave laser, and a high-speed polarization imaging camera. Phase motion picture of dynamic air flow sprayed from a nozzle was recorded at 180,000 frames per second (FPS) have been recorded by the system. Also phase motion picture of dynamic air induced by discharge between two electrodes has been recorded at 1,000,000 FPS, when high voltage was applied between the electrodes.

  20. Diffuse reflectance optical topography: location of inclusions in 3D and detectability limits

    PubMed Central

    Carbone, N. A.; Baez, G. R.; García, H. A.; Waks Serra, M. V.; Di Rocco, H. O.; Iriarte, D. I.; Pomarico, J. A.; Grosenick, D.; Macdonald, R.

    2014-01-01

    In the present contribution we investigate the images of CW diffusely reflected light for a point-like source, registered by a CCD camera imaging a turbid medium containing an absorbing lesion. We show that detection of μa variations (absorption anomalies) is achieved if images are normalized to background intensity. A theoretical analysis based on the diffusion approximation is presented to investigate the sensitivity and the limitations of our proposal and a novel procedure to find the location of the inclusions in 3D is given and tested. An analysis of the noise and its influence on the detection capabilities of our proposal is provided. Experimental results on phantoms are also given, supporting the proposed approach. PMID:24876999

  1. 3D Ag/ZnO hybrids for sensitive surface-enhanced Raman scattering detection

    NASA Astrophysics Data System (ADS)

    Huang, Chenyue; Xu, Chunxiang; Lu, Junfeng; Li, Zhaohui; Tian, Zhengshan

    2016-03-01

    To combine the surface plasma resonance of metal and local field enhancement in metal/semiconductor interface, Ag nanoparticles (NPs) were assembled on a ZnO nanorod array which was grown by hydrothermally on carbon fibers. The construction of dimensional (3D) Surface-Enhanced Raman Scattering (SERS) substrate is used for the sensitive detection of organic pollutants with the advantages such as facile synthesis, short detection time and low cost. The hybrid substrate was manifested a high sensitivity to phenol red at a lower concentration of 1 × 10-9 M and a higher enhancement factor of 3.18 × 109. Moreover, the ZnO nanostructures decorated with Ag NPs were demonstrated self-cleaning function under UV irradiation via photocatalytic degradation of the analytic molecules. The fabrication process of the materials and sensors, optimization of the SERS behaviors for different sized Ag NPs, the mechanism of SERS and recovery were presented with a detailed discussion.

  2. Multifocal multiphoton excitation and time correlated single photon counting detection for 3-D fluorescence lifetime imaging.

    PubMed

    Kumar, S; Dunsby, C; De Beule, P A A; Owen, D M; Anand, U; Lanigan, P M P; Benninger, R K P; Davis, D M; Neil, M A A; Anand, P; Benham, C; Naylor, A; French, P M W

    2007-10-01

    We report a multifocal multiphoton time-correlated single photon counting (TCSPC) fluorescence lifetime imaging (FLIM) microscope system that uses a 16 channel multi-anode PMT detector. Multiphoton excitation minimizes out-of-focus photobleaching, multifocal excitation reduces non-linear in-plane photobleaching effects and TCSPC electronics provide photon-efficient detection of the fluorescence decay profile. TCSPC detection is less prone to bleaching- and movement-induced artefacts compared to wide-field time-gated or frequency-domain FLIM. This microscope is therefore capable of acquiring 3-D FLIM images at significantly increased speeds compared to single beam multiphoton microscopy and we demonstrate this with live cells expressing a GFP tagged protein. We also apply this system to time-lapse FLIM of NAD(P)H autofluorescence in single live cells and report measurements on the change in the fluorescence decay profile following the application of a known metabolic inhibitor. PMID:19550524

  3. Detectability of hepatic tumors during 3D post-processed ultrafast cone-beam computed tomography

    NASA Astrophysics Data System (ADS)

    Paul, Jijo; Vogl, Thomas J.; Chacko, Annamma

    2015-10-01

    To evaluate hepatic tumor detection using ultrafast cone-beam computed tomography (UCBCT) cross-sectional and 3D post-processed image datasets. 657 patients were examined using UCBCT during hepatic transarterial chemoembolization (TACE), and data were collected retrospectively from January 2012 to September 2014. Tumor detectability, diagnostic ability, detection accuracy and sensitivity were examined for different hepatic tumors using UCBCT cross-sectional, perfusion blood volume (PBV) and UCBCT-MRI (magnetic resonance imaging) fused image datasets. Appropriate statistical tests were used to compare collected sample data. Fused image data showed the significantly higher (all P  <  0.05) diagnostic ability for hepatic tumors compared to UCBCT or PBV image data. The detectability of small hepatic tumors (<5 mm) was significantly reduced (all P  <  0.05) using UCBCT cross-sectional images compared to MRI or fused image data; however, PBV improved tumor detectability using a color display. Fused image data produced 100% tumor sensitivity due to the simultaneous availability of MRI and UCBCT information during tumor diagnosis. Fused image data produced excellent hepatic tumor sensitivity, detectability and diagnostic ability compared to other datasets assessed. Fused image data is extremely reliable and useful compared to UCBCT cross-sectional or PBV image datasets to depict hepatic tumors during TACE. Partial anatomical visualization on cross-sectional images was compensated by fused image data during tumor diagnosis.

  4. Workflows and the Role of Images for Virtual 3d Reconstruction of no Longer Extant Historic Objects

    NASA Astrophysics Data System (ADS)

    Münster, S.

    2013-07-01

    3D reconstruction technologies have gained importance as tools for the research and visualization of no longer extant historic objects during the last decade. Within such reconstruction processes, visual media assumes several important roles: as the most important sources especially for a reconstruction of no longer extant objects, as a tool for communication and cooperation within the production process, as well as for a communication and visualization of results. While there are many discourses about theoretical issues of depiction as sources and as visualization outcomes of such projects, there is no systematic research about the importance of depiction during a 3D reconstruction process and based on empirical findings. Moreover, from a methodological perspective, it would be necessary to understand which role visual media plays during the production process and how it is affected by disciplinary boundaries and challenges specific to historic topics. Research includes an analysis of published work and case studies investigating reconstruction projects. This study uses methods taken from social sciences to gain a grounded view of how production processes would take place in practice and which functions and roles images would play within them. For the investigation of these topics, a content analysis of 452 conference proceedings and journal articles related to 3D reconstruction modeling in the field of humanities has been completed. Most of the projects described in those publications dealt with data acquisition and model building for existing objects. Only a small number of projects focused on structures that no longer or never existed physically. Especially that type of project seems to be interesting for a study of the importance of pictures as sources and as tools for interdisciplinary cooperation during the production process. In the course of the examination the authors of this paper applied a qualitative content analysis for a sample of 26 previously

  5. Contextualizing Object Detection and Classification.

    PubMed

    Chen, Qiang; Song, Zheng; Dong, Jian; Huang, Zhongyang; Hua, Yang; Yan, Shuicheng

    2015-01-01

    We investigate how to iteratively and mutually boost object classification and detection performance by taking the outputs from one task as the context of the other one. While context models have been quite popular, previous works mainly concentrate on co-occurrence relationship within classes and few of them focus on contextualization from a top-down perspective, i.e. high-level task context. In this paper, our system adopts a new method for adaptive context modeling and iterative boosting. First, the contextualized support vector machine (Context-SVM) is proposed, where the context takes the role of dynamically adjusting the classification score based on the sample ambiguity, and thus the context-adaptive classifier is achieved. Then, an iterative training procedure is presented. In each step, Context-SVM, associated with the output context from one task (object classification or detection), is instantiated to boost the performance for the other task, whose augmented outputs are then further used to improve the former task by Context-SVM. The proposed solution is evaluated on the object classification and detection tasks of PASCAL Visual Object Classes Challenge (VOC) 2007, 2010 and SUN09 data sets, and achieves the state-of-the-art performance.

  6. Subjective and Objective Video Quality Assessment of 3D Synthesized Views With Texture/Depth Compression Distortion.

    PubMed

    Liu, Xiangkai; Zhang, Yun; Hu, Sudeng; Kwong, Sam; Kuo, C-C Jay; Peng, Qiang

    2015-12-01

    The quality assessment for synthesized video with texture/depth compression distortion is important for the design, optimization, and evaluation of the multi-view video plus depth (MVD)-based 3D video system. In this paper, the subjective and objective studies for synthesized view assessment are both conducted. First, a synthesized video quality database with texture/depth compression distortion is presented with subjective scores given by 56 subjects. The 140 videos are synthesized from ten MVD sequences with different texture/depth quantization combinations. Second, a full reference objective video quality assessment (VQA) method is proposed concerning about the annoying temporal flicker distortion and the change of spatio-temporal activity in the synthesized video. The proposed VQA algorithm has a good performance evaluated on the entire synthesized video quality database, and is particularly prominent on the subsets which have significant temporal flicker distortion induced by depth compression and view synthesis process. PMID:26292342

  7. 3D topographic correction of the BSR heat flow and detection of focused fluid flow

    NASA Astrophysics Data System (ADS)

    He, Tao; Li, Hong-Lin; Zou, Chang-Chun

    2014-06-01

    The bottom-simulating reflector (BSR) is a seismic indicator of the bottom of a gas hydrate stability zone. Its depth can be used to calculate the seafloor surface heat flow. The calculated BSR heat flow variations include disturbances from two important factors: (1) seafloor topography, which focuses the heat flow over regions of concave topography and defocuses it over regions of convex topography, and (2) the focused warm fluid flow within the accretionary prism coming from depths deeper than BSR. The focused fluid flow can be detected if the contribution of the topography to the BSR heat flow is removed. However, the analytical equation cannot solve the topographic effect at complex seafloor regions. We prove that 3D finite element method can model the topographic effect on the regional background heat flow with high accuracy, which can then be used to correct the topographic effect and obtain the BSR heat flow under the condition of perfectly flat topography. By comparing the corrected BSR heat flow with the regional background heat flow, focused fluid flow regions can be detected that are originally too small and cannot be detected using present-day equipment. This method was successfully applied to the midslope region of northern Cascadia subducting margin. The results suggest that the Cucumber Ridge and its neighboring area are positive heat flow anomalies, about 10%-20% higher than the background heat flow after 3D topographic correction. Moreover, the seismic imaging associated the positive heat flow anomaly areas with seabed fracture-cavity systems. This suggests flow of warm gas-carrying fluids along these high-permeability pathways, which could result in higher gas hydrate concentrations.

  8. Automatic 3D Building Detection and Modeling from Airborne LiDAR Point Clouds

    NASA Astrophysics Data System (ADS)

    Sun, Shaohui

    Urban reconstruction, with an emphasis on man-made structure modeling, is an active research area with broad impact on several potential applications. Urban reconstruction combines photogrammetry, remote sensing, computer vision, and computer graphics. Even though there is a huge volume of work that has been done, many problems still remain unsolved. Automation is one of the key focus areas in this research. In this work, a fast, completely automated method to create 3D watertight building models from airborne LiDAR (Light Detection and Ranging) point clouds is presented. The developed method analyzes the scene content and produces multi-layer rooftops, with complex rigorous boundaries and vertical walls, that connect rooftops to the ground. The graph cuts algorithm is used to separate vegetative elements from the rest of the scene content, which is based on the local analysis about the properties of the local implicit surface patch. The ground terrain and building rooftop footprints are then extracted, utilizing the developed strategy, a two-step hierarchical Euclidean clustering. The method presented here adopts a "divide-and-conquer" scheme. Once the building footprints are segmented from the terrain and vegetative areas, the whole scene is divided into individual pendent processing units which represent potential points on the rooftop. For each individual building region, significant features on the rooftop are further detected using a specifically designed region-growing algorithm with surface smoothness constraints. The principal orientation of each building rooftop feature is calculated using a minimum bounding box fitting technique, and is used to guide the refinement of shapes and boundaries of the rooftop parts. Boundaries for all of these features are refined for the purpose of producing strict description. Once the description of the rooftops is achieved, polygonal mesh models are generated by creating surface patches with outlines defined by detected

  9. Multi-frequency color-marked fringe projection profilometry for fast 3D shape measurement of complex objects.

    PubMed

    Jiang, Chao; Jia, Shuhai; Dong, Jun; Bao, Qingchen; Yang, Jia; Lian, Qin; Li, Dichen

    2015-09-21

    We propose a novel multi-frequency color-marked fringe projection profilometry approach to measure the 3D shape of objects with depth discontinuities. A digital micromirror device projector is used to project a color map consisting of a series of different-frequency color-marked fringe patterns onto the target object. We use a chromaticity curve to calculate the color change caused by the height of the object. The related algorithm to measure the height is also described in this paper. To improve the measurement accuracy, a chromaticity curve correction method is presented. This correction method greatly reduces the influence of color fluctuations and measurement error on the chromaticity curve and the calculation of the object height. The simulation and experimental results validate the utility of our method. Our method avoids the conventional phase shifting and unwrapping process, as well as the independent calculation of the object height required by existing techniques. Thus, it can be used to measure complex and dynamic objects with depth discontinuities. These advantages are particularly promising for industrial applications. PMID:26406621

  10. Colorful holographic display of 3D object based on scaled diffraction by using non-uniform fast Fourier transform

    NASA Astrophysics Data System (ADS)

    Chang, Chenliang; Xia, Jun; Lei, Wei

    2015-03-01

    We proposed a new method to calculate the color computer generated hologram of three-dimensional object in holographic display. The three-dimensional object is composed of several tilted planes which are tilted from the hologram. The diffraction from each tilted plane to the hologram plane is calculated based on the coordinate rotation in Fourier spectrum domains. We used the nonuniform fast Fourier transformation (NUFFT) to calculate the nonuniform sampled Fourier spectrum on the tilted plane after coordinate rotation. By using the NUFFT, the diffraction calculation from tilted plane to the hologram plane with variable sampling rates can be achieved, which overcomes the sampling restriction of FFT in the conventional angular spectrum based method. The holograms of red, green and blue component of the polygon-based object are calculated separately by using our NUFFT based method. Then the color hologram is synthesized by placing the red, green and blue component hologram in sequence. The chromatic aberration caused by the wavelength difference can be solved effectively by restricting the sampling rate of the object in the calculation of each wavelength component. The computer simulation shows the feasibility of our method in calculating the color hologram of polygon-based object. The 3D object can be displayed in color with adjustable size and no chromatic aberration in holographic display system, which can be considered as an important application in the colorful holographic three-dimensional display.

  11. Early detection of skin cancer via terahertz spectral profiling and 3D imaging.

    PubMed

    Rahman, Anis; Rahman, Aunik K; Rao, Babar

    2016-08-15

    Terahertz scanning reflectometry, terahertz 3D imaging and terahertz time-domain spectroscopy have been used to identify features in human skin biopsy samples diagnosed for basal cell carcinoma (BCC) and compared with healthy skin samples. It was found from the 3D images that the healthy skin samples exhibit regular cellular pattern while the BCC skin samples indicate lack of regular cell pattern. The skin is a highly layered structure organ; this is evident from the thickness profile via a scan through the thickness of the healthy skin samples, where, the reflected intensity of the terahertz beam exhibits fluctuations originating from different skin layers. Compared to the healthy skin samples, the BCC samples' profiles exhibit significantly diminished layer definition; thus indicating a lack of cellular order. In addition, terahertz time-domain spectroscopy reveals significant and quantifiable differences between the healthy and BCC skin samples. Thus, a combination of three different terahertz techniques constitutes a conclusive route for detecting the BCC condition on a cellular level compared to the healthy skin. PMID:27040943

  12. Indoor Navigation from Point Clouds: 3d Modelling and Obstacle Detection

    NASA Astrophysics Data System (ADS)

    Díaz-Vilariño, L.; Boguslawski, P.; Khoshelham, K.; Lorenzo, H.; Mahdjoubi, L.

    2016-06-01

    In the recent years, indoor modelling and navigation has become a research of interest because many stakeholders require navigation assistance in various application scenarios. The navigational assistance for blind or wheelchair people, building crisis management such as fire protection, augmented reality for gaming, tourism or training emergency assistance units are just some of the direct applications of indoor modelling and navigation. Navigational information is traditionally extracted from 2D drawings or layouts. Real state of indoors, including opening position and geometry for both windows and doors, and the presence of obstacles is commonly ignored. In this work, a real indoor-path planning methodology based on 3D point clouds is developed. The value and originality of the approach consist on considering point clouds not only for reconstructing semantically-rich 3D indoor models, but also for detecting potential obstacles in the route planning and using these for readapting the routes according to the real state of the indoor depictured by the laser scanner.

  13. 3D Seismic Flexure Analysis for Subsurface Fault Detection and Fracture Characterization

    NASA Astrophysics Data System (ADS)

    Di, Haibin; Gao, Dengliang

    2016-10-01

    Seismic flexure is a new geometric attribute with the potential of delineating subtle faults and fractures from three-dimensional (3D) seismic surveys, especially those overlooked by the popular discontinuity and curvature attributes. Although the concept of flexure and its related algorithms have been published in the literature, the attribute has not been sufficiently applied to subsurface fault detection and fracture characterization. This paper provides a comprehensive study of the flexure attribute, including its definition, computation, as well as geologic implications for evaluating the fundamental fracture properties that are essential to fracture characterization and network modeling in the subsurface, through applications to the fractured reservoir at Teapot Dome, Wyoming (USA). Specifically, flexure measures the third-order variation of the geometry of a seismic reflector and is dependent on the measuring direction in 3D space; among all possible directions, flexure is considered most useful when extracted perpendicular to the orientation of dominant deformation; and flexure offers new insights into qualitative/quantitative fracture characterization, with its magnitude indicating the intensity of faulting and fracturing, its azimuth defining the orientation of most-likely fracture trends, and its sign differentiating the sense of displacement of faults and fractures.

  14. Application for 3d Scene Understanding in Detecting Discharge of Domesticwaste Along Complex Urban Rivers

    NASA Astrophysics Data System (ADS)

    Ninsalam, Y.; Qin, R.; Rekittke, J.

    2016-06-01

    In our study we use 3D scene understanding to detect the discharge of domestic solid waste along an urban river. Solid waste found along the Ciliwung River in the neighbourhoods of Bukit Duri and Kampung Melayu may be attributed to households. This is in part due to inadequate municipal waste infrastructure and services which has caused those living along the river to rely upon it for waste disposal. However, there has been little research to understand the prevalence of household waste along the river. Our aim is to develop a methodology that deploys a low cost sensor to identify point source discharge of solid waste using image classification methods. To demonstrate this we describe the following five-step method: 1) a strip of GoPro images are captured photogrammetrically and processed for dense point cloud generation; 2) depth for each image is generated through a backward projection of the point clouds; 3) a supervised image classification method based on Random Forest classifier is applied on the view dependent red, green, blue and depth (RGB-D) data; 4) point discharge locations of solid waste can then be mapped by projecting the classified images to the 3D point clouds; 5) then the landscape elements are classified into five types, such as vegetation, human settlement, soil, water and solid waste. While this work is still ongoing, the initial results have demonstrated that it is possible to perform quantitative studies that may help reveal and estimate the amount of waste present along the river bank.

  15. SDTP: a robust method for interest point detection on 3D range images

    NASA Astrophysics Data System (ADS)

    Wang, Shandong; Gong, Lujin; Zhang, Hui; Zhang, Yongjie; Ren, Haibing; Rhee, Seon-Min; Lee, Hyong-Euk

    2013-12-01

    In fields of intelligent robots and computer vision, the capability to select a few points representing salient structures has always been focused and investigated. In this paper, we present a novel interest point detector for 3D range images, which can be used with good results in applications of surface registration and object recognition. A local shape description around each point in the range image is firstly constructed based on the distribution map of the signed distances to the tangent plane in its local support region. Using this shape description, the interest value is computed for indicating the probability of a point being the interest point. Lastly a Non-Maxima Suppression procedure is performed to select stable interest points on positions that have large surface variation in the vicinity. Our method is robust to noise, occlusion and clutter, which can be seen from the higher repeatability values compared with the state-of-the-art 3D interest point detectors in experiments. In addition, the method can be implemented easily and requires low computation time.

  16. Spun-wrapped aligned nanofiber (SWAN) lithography for fabrication of micro/nano-structures on 3D objects

    NASA Astrophysics Data System (ADS)

    Ye, Zhou; Nain, Amrinder S.; Behkam, Bahareh

    2016-06-01

    Fabrication of micro/nano-structures on irregularly shaped substrates and three-dimensional (3D) objects is of significant interest in diverse technological fields. However, it remains a formidable challenge thwarted by limited adaptability of the state-of-the-art nanolithography techniques for nanofabrication on non-planar surfaces. In this work, we introduce Spun-Wrapped Aligned Nanofiber (SWAN) lithography, a versatile, scalable, and cost-effective technique for fabrication of multiscale (nano to microscale) structures on 3D objects without restriction on substrate material and geometry. SWAN lithography combines precise deposition of polymeric nanofiber masks, in aligned single or multilayer configurations, with well-controlled solvent vapor treatment and etching processes to enable high throughput (>10-7 m2 s-1) and large-area fabrication of sub-50 nm to several micron features with high pattern fidelity. Using this technique, we demonstrate whole-surface nanopatterning of bulk and thin film surfaces of cubes, cylinders, and hyperbola-shaped objects that would be difficult, if not impossible to achieve with existing methods. We demonstrate that the fabricated feature size (b) scales with the fiber mask diameter (D) as b1.5 ~ D. This scaling law is in excellent agreement with theoretical predictions using the Johnson, Kendall, and Roberts (JKR) contact theory, thus providing a rational design framework for fabrication of systems and devices that require precisely designed multiscale features.Fabrication of micro/nano-structures on irregularly shaped substrates and three-dimensional (3D) objects is of significant interest in diverse technological fields. However, it remains a formidable challenge thwarted by limited adaptability of the state-of-the-art nanolithography techniques for nanofabrication on non-planar surfaces. In this work, we introduce Spun-Wrapped Aligned Nanofiber (SWAN) lithography, a versatile, scalable, and cost-effective technique for

  17. Development and Evaluation of Roadside/Obstacle Detection Method Using 3D Scanned Data Processing

    NASA Astrophysics Data System (ADS)

    Yamamoto, Hiroshi; Ishii, Yoshinori; Yamazaki, Katsuyuki

    In this paper, we have reported the development of a snowblower support system which can safely navigate snowblowers, even during a whiteout, with the combination of a very accurate GPS system, so called RTK-GPS, and a unique and highly accurate map of roadsides and obstacles on roads. Particularly emphasized new techniques in this paper are ways to detect accurate geographical positions of roadsides and obstacles by utilizing and analyzing 3D laser scanned data, whose data has become available in recent days. The experiment has shown that the map created by the methods and RTK-GPS can sufficiently navigate snowblowers, whereby a secure and pleasant social environment can be archived in snow areas of Japan. In addition, proposed methods are expected to be useful for other systems such as a quick development of a highly accurate road map, a safely navigation of a wheeled chair, and so on.

  18. Automatic Dent-landmark detection in 3-D CBCT dental volumes.

    PubMed

    Cheng, Erkang; Chen, Jinwu; Yang, Jie; Deng, Huiyang; Wu, Yi; Megalooikonomou, Vasileios; Gable, Bryce; Ling, Haibin

    2011-01-01

    Orthodontic craniometric landmarks provide critical information in oral and maxillofacial imaging diagnosis and treatment planning. The Dent-landmark, defined as the odontoid process of the epistropheus, is one of the key landmarks to construct the midsagittal reference plane. In this paper, we propose a learning-based approach to automatically detect the Dent-landmark in the 3D cone-beam computed tomography (CBCT) dental data. Specifically, a detector is learned using the random forest with sampled context features. Furthermore, we use spacial prior to build a constrained search space other than use the full three dimensional space. The proposed method has been evaluated on a dataset containing 73 CBCT dental volumes and yields promising results.

  19. Reverse engineering physical models employing a sensor integration between 3D stereo detection and contact digitization

    NASA Astrophysics Data System (ADS)

    Chen, Liang-Chia; Lin, Grier C. I.

    1997-12-01

    A vision-drive automatic digitization process for free-form surface reconstruction has been developed, with a coordinate measurement machine (CMM) equipped with a touch-triggered probe and a CCD camera, in reverse engineering physical models. The process integrates 3D stereo detection, data filtering, Delaunay triangulation, adaptive surface digitization into a single process of surface reconstruction. By using this innovative approach, surface reconstruction can be implemented automatically and accurately. Least-squares B- spline surface models with the controlled accuracy of digitization can be generated for further application in product design and manufacturing processes. One industrial application indicates that this approach is feasible, and the processing time required in reverse engineering process can be significantly reduced up to more than 85%.

  20. Detecting Distance between Injected Microspheres and Target Tumor via 3D Reconstruction of Tissue Sections

    SciTech Connect

    Carson, James P.; Kuprat, Andrew P.; Colby, Sean M.; Davis, Cassi A.; Basciano, Christopher; Greene, Kevin; Feo, John T.; Kennedy, Andrew

    2012-08-28

    One treatment increasing in use for solid tumors in the liver is radioembolization via the delivery of 90Y microspheres to the vascular bed within or near the location of the tumor. It is desirable as part of the treatment for the microspheres to embed preferentially in or near the tumor. This work details an approach for analyzing the deposition of microspheres with respect to the location of the tumor. The approach used is based upon thin-slice serial sectioning of the tissue sample, followed by high resolution imaging, microsphere detection, and 3-D reconstruction of the tumor surface. Distance from the microspheres to the tumor was calculated using a fast deterministic point inclusion method.

  1. Multi-hole seismic modeling in 3-D space and cross-hole seismic tomography analysis for boulder detection

    NASA Astrophysics Data System (ADS)

    Cheng, Fei; Liu, Jiangping; Wang, Jing; Zong, Yuquan; Yu, Mingyu

    2016-11-01

    A boulder stone, a common geological feature in south China, is referred to the remnant of a granite body which has been unevenly weathered. Undetected boulders could adversely impact the schedule and safety of subway construction when using tunnel boring machine (TBM) method. Therefore, boulder detection has always been a key issue demanded to be solved before the construction. Nowadays, cross-hole seismic tomography is a high resolution technique capable of boulder detection, however, the method can only solve for velocity in a 2-D slice between two wells, and the size and central position of the boulder are generally difficult to be accurately obtained. In this paper, the authors conduct a multi-hole wave field simulation and characteristic analysis of a boulder model based on the 3-D elastic wave staggered-grid finite difference theory, and also a 2-D imaging analysis based on first arrival travel time. The results indicate that (1) full wave field records could be obtained from multi-hole seismic wave simulations. Simulation results describe that the seismic wave propagation pattern in cross-hole high-velocity spherical geological bodies is more detailed and can serve as a basis for the wave field analysis. (2) When a cross-hole seismic section cuts through the boulder, the proposed method provides satisfactory cross-hole tomography results; however, when the section is closely positioned to the boulder, such high-velocity object in the 3-D space would impact on the surrounding wave field. The received diffracted wave interferes with the primary wave and in consequence the picked first arrival travel time is not derived from the profile, which results in a false appearance of high-velocity geology features. Finally, the results of 2-D analysis in 3-D modeling space are comparatively analyzed with the physical model test vis-a-vis the effect of high velocity body on the seismic tomographic measurements.

  2. Hepatic 3D spheroid models for the detection and study of compounds with cholestatic liability

    PubMed Central

    Hendriks, Delilah F. G.; Fredriksson Puigvert, Lisa; Messner, Simon; Mortiz, Wolfgang; Ingelman-Sundberg, Magnus

    2016-01-01

    Drug-induced cholestasis (DIC) is poorly understood and its preclinical prediction is mainly limited to assessing the compound’s potential to inhibit the bile salt export pump (BSEP). Here, we evaluated two 3D spheroid models, one from primary human hepatocytes (PHH) and one from HepaRG cells, for the detection of compounds with cholestatic liability. By repeatedly co-exposing both models to a set of compounds with different mechanisms of hepatotoxicity and a non-toxic concentrated bile acid (BA) mixture for 8 days we observed a selective synergistic toxicity of compounds known to cause cholestatic or mixed cholestatic/hepatocellular toxicity and the BA mixture compared to exposure to the compounds alone, a phenomenon that was more pronounced after extending the exposure time to 14 days. In contrast, no such synergism was observed after both 8 and 14 days of exposure to the BA mixture for compounds that cause non-cholestatic hepatotoxicity. Mechanisms behind the toxicity of the cholestatic compound chlorpromazine were accurately detected in both spheroid models, including intracellular BA accumulation, inhibition of ABCB11 expression and disruption of the F-actin cytoskeleton. Furthermore, the observed synergistic toxicity of chlorpromazine and BA was associated with increased oxidative stress and modulation of death receptor signalling. Combined, our results demonstrate that the hepatic spheroid models presented here can be used to detect and study compounds with cholestatic liability. PMID:27759057

  3. Single objective light-sheet microscopy for high-speed whole-cell 3D super-resolution

    DOE PAGES

    Meddens, Marjolein B. M.; Liu, Sheng; Finnegan, Patrick S.; Edwards, Thayne L.; James, Conrad D.; Lidke, Keith A.

    2016-05-01

    Here, we have developed a method for performing light-sheet microscopy with a single high numerical aperture lens by integrating reflective side walls into a microfluidic chip. These 45° side walls generate light-sheet illumination by reflecting a vertical light-sheet into the focal plane of the objective. Light-sheet illumination of cells loaded in the channels increases image quality in diffraction limited imaging via reduction of out-of-focus background light. Single molecule super-resolution is also improved by the decreased background resulting in better localization precision and decreased photo-bleaching, leading to more accepted localizations overall and higher quality images. Moreover, 2D and 3D single moleculemore » super-resolution data can be acquired faster by taking advantage of the increased illumination intensities as compared to wide field, in the focused light-sheet.« less

  4. Single objective light-sheet microscopy for high-speed whole-cell 3D super-resolution.

    PubMed

    Meddens, Marjolein B M; Liu, Sheng; Finnegan, Patrick S; Edwards, Thayne L; James, Conrad D; Lidke, Keith A

    2016-06-01

    We have developed a method for performing light-sheet microscopy with a single high numerical aperture lens by integrating reflective side walls into a microfluidic chip. These 45° side walls generate light-sheet illumination by reflecting a vertical light-sheet into the focal plane of the objective. Light-sheet illumination of cells loaded in the channels increases image quality in diffraction limited imaging via reduction of out-of-focus background light. Single molecule super-resolution is also improved by the decreased background resulting in better localization precision and decreased photo-bleaching, leading to more accepted localizations overall and higher quality images. Moreover, 2D and 3D single molecule super-resolution data can be acquired faster by taking advantage of the increased illumination intensities as compared to wide field, in the focused light-sheet.

  5. Single objective light-sheet microscopy for high-speed whole-cell 3D super-resolution

    PubMed Central

    Meddens, Marjolein B. M.; Liu, Sheng; Finnegan, Patrick S.; Edwards, Thayne L.; James, Conrad D.; Lidke, Keith A.

    2016-01-01

    We have developed a method for performing light-sheet microscopy with a single high numerical aperture lens by integrating reflective side walls into a microfluidic chip. These 45° side walls generate light-sheet illumination by reflecting a vertical light-sheet into the focal plane of the objective. Light-sheet illumination of cells loaded in the channels increases image quality in diffraction limited imaging via reduction of out-of-focus background light. Single molecule super-resolution is also improved by the decreased background resulting in better localization precision and decreased photo-bleaching, leading to more accepted localizations overall and higher quality images. Moreover, 2D and 3D single molecule super-resolution data can be acquired faster by taking advantage of the increased illumination intensities as compared to wide field, in the focused light-sheet. PMID:27375939

  6. Single objective light-sheet microscopy for high-speed whole-cell 3D super-resolution

    SciTech Connect

    Meddens, Marjolein B. M.; Liu, Sheng; Finnegan, Patrick S.; Edwards, Thayne L.; James, Conrad D.; Lidke, Keith A.

    2016-01-01

    Here, we have developed a method for performing light-sheet microscopy with a single high numerical aperture lens by integrating reflective side walls into a microfluidic chip. These 45° side walls generate light-sheet illumination by reflecting a vertical light-sheet into the focal plane of the objective. Light-sheet illumination of cells loaded in the channels increases image quality in diffraction limited imaging via reduction of out-of-focus background light. Single molecule super-resolution is also improved by the decreased background resulting in better localization precision and decreased photo-bleaching, leading to more accepted localizations overall and higher quality images. Moreover, 2D and 3D single molecule super-resolution data can be acquired faster by taking advantage of the increased illumination intensities as compared to wide field, in the focused light-sheet.

  7. Single objective light-sheet microscopy for high-speed whole-cell 3D super-resolution.

    PubMed

    Meddens, Marjolein B M; Liu, Sheng; Finnegan, Patrick S; Edwards, Thayne L; James, Conrad D; Lidke, Keith A

    2016-06-01

    We have developed a method for performing light-sheet microscopy with a single high numerical aperture lens by integrating reflective side walls into a microfluidic chip. These 45° side walls generate light-sheet illumination by reflecting a vertical light-sheet into the focal plane of the objective. Light-sheet illumination of cells loaded in the channels increases image quality in diffraction limited imaging via reduction of out-of-focus background light. Single molecule super-resolution is also improved by the decreased background resulting in better localization precision and decreased photo-bleaching, leading to more accepted localizations overall and higher quality images. Moreover, 2D and 3D single molecule super-resolution data can be acquired faster by taking advantage of the increased illumination intensities as compared to wide field, in the focused light-sheet. PMID:27375939

  8. A novel Hessian based algorithm for rat kidney glomerulus detection in 3D MRI

    NASA Astrophysics Data System (ADS)

    Zhang, Min; Wu, Teresa; Bennett, Kevin M.

    2015-03-01

    The glomeruli of the kidney perform the key role of blood filtration and the number of glomeruli in a kidney is correlated with susceptibility to chronic kidney disease and chronic cardiovascular disease. This motivates the development of new technology using magnetic resonance imaging (MRI) to measure the number of glomeruli and nephrons in vivo. However, there is currently a lack of computationally efficient techniques to perform fast, reliable and accurate counts of glomeruli in MR images due to the issues inherent in MRI, such as acquisition noise, partial volume effects (the mixture of several tissue signals in a voxel) and bias field (spatial intensity inhomogeneity). Such challenges are particularly severe because the glomeruli are very small, (in our case, a MRI image is ~16 million voxels, each glomerulus is in the size of 8~20 voxels), and the number of glomeruli is very large. To address this, we have developed an efficient Hessian based Difference of Gaussians (HDoG) detector to identify the glomeruli on 3D rat MR images. The image is first smoothed via DoG followed by the Hessian process to pre-segment and delineate the boundary of the glomerulus candidates. This then provides a basis to extract regional features used in an unsupervised clustering algorithm, completing segmentation by removing the false identifications occurred in the pre-segmentation. The experimental results show that Hessian based DoG has the potential to automatically detect glomeruli,from MRI in 3D, enabling new measurements of renal microstructure and pathology in preclinical and clinical studies.

  9. Three-dimensional object detection under arbitrary lighting conditions.

    PubMed

    Vallés, José J; García, Javier; García-Martínez, Pascuala; Arsenault, Henri H

    2006-07-20

    A novel method of 3D object recognition independent of lighting conditions is presented. The recognition model is based on a vector space representation using an orthonormal basis generated by the Lambertian reflectance functions obtained with distant light sources. Changing the lighting conditions corresponds to multiplying the elementary images by a constant factor and because of that, all possible lighting views will be elements that belong to that vector space. The recognition method proposed is based on the calculation of the angle between the vector associated with a certain illuminated 3D object and that subspace. We define the angle in terms of linear correlations to get shift and illumination-invariant detection.

  10. See-Through Imaging of Laser-Scanned 3d Cultural Heritage Objects Based on Stochastic Rendering of Large-Scale Point Clouds

    NASA Astrophysics Data System (ADS)

    Tanaka, S.; Hasegawa, K.; Okamoto, N.; Umegaki, R.; Wang, S.; Uemura, M.; Okamoto, A.; Koyamada, K.

    2016-06-01

    We propose a method for the precise 3D see-through imaging, or transparent visualization, of the large-scale and complex point clouds acquired via the laser scanning of 3D cultural heritage objects. Our method is based on a stochastic algorithm and directly uses the 3D points, which are acquired using a laser scanner, as the rendering primitives. This method achieves the correct depth feel without requiring depth sorting of the rendering primitives along the line of sight. Eliminating this need allows us to avoid long computation times when creating natural and precise 3D see-through views of laser-scanned cultural heritage objects. The opacity of each laser-scanned object is also flexibly controllable. For a laser-scanned point cloud consisting of more than 107 or 108 3D points, the pre-processing requires only a few minutes, and the rendering can be executed at interactive frame rates. Our method enables the creation of cumulative 3D see-through images of time-series laser-scanned data. It also offers the possibility of fused visualization for observing a laser-scanned object behind a transparent high-quality photographic image placed in the 3D scene. We demonstrate the effectiveness of our method by applying it to festival floats of high cultural value. These festival floats have complex outer and inner 3D structures and are suitable for see-through imaging.

  11. Label-free optical detection of cells grown in 3D silicon microstructures.

    PubMed

    Merlo, Sabina; Carpignano, Francesca; Silva, Gloria; Aredia, Francesca; Scovassi, A Ivana; Mazzini, Giuliano; Surdo, Salvatore; Barillaro, Giuseppe

    2013-08-21

    We demonstrate high aspect-ratio photonic crystals that could serve as three-dimensional (3D) microincubators for cell culture and also provide label-free optical detection of the cells. The investigated microstructures, fabricated by electrochemical micromachining of standard silicon wafers, consist of periodic arrays of silicon walls separated by narrow deeply etched air-gaps (50 μm high and 5 μm wide) and feature the typical spectral properties of photonic crystals in the wavelength range 1.0-1.7 μm: their spectral reflectivity is characterized by wavelength regions where reflectivity is high (photonic bandgaps), separated by narrow wavelength regions where reflectivity is very low. In this work, we show that the presence of cells, grown inside the gaps, strongly affects light propagation across the photonic crystal and, therefore, its spectral reflectivity. Exploiting a label-free optical detection method, based on a fiberoptic setup, we are able to probe the extension of cells adherent to the vertical silicon walls with a non-invasive direct testing. In particular, the intensity ratio at two wavelengths is the experimental parameter that can be well correlated to the cell spreading on the silicon wall inside the gaps.

  12. 3D Printed Scintillators For Use in Field Emission Detection and Other Nuclear Physics Experiments

    NASA Astrophysics Data System (ADS)

    Ficenec, Karen

    2015-10-01

    In accelerator cavities, field emission electrons - electrons that get stripped away from the cavity walls due to the high electromagnetic field necessary to accelerate the main beam - are partially accelerated and can crash into the cavity walls, adding to the heat-load of the cryogenic system. Because these field electrons emit gamma rays when bent by the electromagnetic field, a scintillator, if made to fit the cavity enclosure, can detect their presence. Eliminating the waste of subtractive manufacturing techniques and allowing for the production of unique, varied shapes, 3D printing of scintillators may allow for an efficient detection system. UV light is used to start a chemical polymerization process that links the monomers of the liquid resin together into larger, intertwined molecules, forming the solid structure. Each shape requires slightly different calibration of its optimal printing parameters, such as slice thickness and exposure time to UV light. Thus far, calibration parameters have been optimized for cylinders of 20 mm diameter, cones of 30 mm diameter and 30 mm height, rectangular prisms 30 by 40 by 10 mm, and square pyramids 20 mm across. Calibration continues on creating holes in the prints (for optical fibers), as well as shapes with overhangs. Scintill This work was supported in part by the National Science Foundation under Grant No. PHY-1405857.

  13. Computer-aided detection of lung nodules: false positive reduction using a 3D gradient field method

    NASA Astrophysics Data System (ADS)

    Ge, Zhanyu; Sahiner, Berkman; Chan, Heang-Ping; Hadjiiski, Lubomir M.; Wei, Jun; Bogot, Naama; Cascade, Philip N.; Kazerooni, Ella A.; Zhou, Chuan

    2004-05-01

    We are developing a computer-aided detection system to aid radiologists in diagnosing lung cancer in thoracic computed tomographic (CT) images. The purpose of this study was to improve the false-positive (FP) reduction stage of our algorithm by developing and incorporating a gradient field technique. This technique extracts 3D shape information from the gray-scale values within a volume of interest. The gradient field feature values are higher for spherical objects, and lower for elongated and irregularly-shaped objects. A data set of 55 thin CT scans from 40 patients was used to evaluate the usefulness of the gradient field technique. After initial nodule candidate detection and rule-based first stage FP reduction, there were 3487 FP and 65 true positive (TP) objects in our data set. Linear discriminant classifiers with and without the gradient field feature were designed for the second stage FP reduction. The accuracy of these classifiers was evaluated using the area Az under the receiver operating characteristic (ROC) curve. The Az values were 0.93 and 0.91 with and without the gradient field feature, respectively. The improvement with the gradient field feature was statistically significant (p=0.01).

  14. A New Methodology for 3D Target Detection in Automotive Radar Applications.

    PubMed

    Baselice, Fabio; Ferraioli, Giampaolo; Lukin, Sergyi; Matuozzo, Gianfranco; Pascazio, Vito; Schirinzi, Gilda

    2016-04-29

    Today there is a growing interest in automotive sensor monitoring systems. One of the main challenges is to make them an effective and valuable aid in dangerous situations, improving transportation safety. The main limitation of visual aid systems is that they do not produce accurate results in critical visibility conditions, such as in presence of rain, fog or smoke. Radar systems can greatly help in overcoming such limitations. In particular, imaging radar is gaining interest in the framework of Driver Assistance Systems (DAS). In this manuscript, a new methodology able to reconstruct the 3D imaged scene and to detect the presence of multiple targets within each line of sight is proposed. The technique is based on the use of Compressive Sensing (CS) theory and produces the estimation of multiple targets for each line of sight, their range distance and their reflectivities. Moreover, a fast approach for 2D focus based on the FFT algorithm is proposed. After the description of the proposed methodology, different simulated case studies are reported in order to evaluate the performances of the proposed approach.

  15. A New Methodology for 3D Target Detection in Automotive Radar Applications.

    PubMed

    Baselice, Fabio; Ferraioli, Giampaolo; Lukin, Sergyi; Matuozzo, Gianfranco; Pascazio, Vito; Schirinzi, Gilda

    2016-01-01

    Today there is a growing interest in automotive sensor monitoring systems. One of the main challenges is to make them an effective and valuable aid in dangerous situations, improving transportation safety. The main limitation of visual aid systems is that they do not produce accurate results in critical visibility conditions, such as in presence of rain, fog or smoke. Radar systems can greatly help in overcoming such limitations. In particular, imaging radar is gaining interest in the framework of Driver Assistance Systems (DAS). In this manuscript, a new methodology able to reconstruct the 3D imaged scene and to detect the presence of multiple targets within each line of sight is proposed. The technique is based on the use of Compressive Sensing (CS) theory and produces the estimation of multiple targets for each line of sight, their range distance and their reflectivities. Moreover, a fast approach for 2D focus based on the FFT algorithm is proposed. After the description of the proposed methodology, different simulated case studies are reported in order to evaluate the performances of the proposed approach. PMID:27136558

  16. A New Methodology for 3D Target Detection in Automotive Radar Applications

    PubMed Central

    Baselice, Fabio; Ferraioli, Giampaolo; Lukin, Sergyi; Matuozzo, Gianfranco; Pascazio, Vito; Schirinzi, Gilda

    2016-01-01

    Today there is a growing interest in automotive sensor monitoring systems. One of the main challenges is to make them an effective and valuable aid in dangerous situations, improving transportation safety. The main limitation of visual aid systems is that they do not produce accurate results in critical visibility conditions, such as in presence of rain, fog or smoke. Radar systems can greatly help in overcoming such limitations. In particular, imaging radar is gaining interest in the framework of Driver Assistance Systems (DAS). In this manuscript, a new methodology able to reconstruct the 3D imaged scene and to detect the presence of multiple targets within each line of sight is proposed. The technique is based on the use of Compressive Sensing (CS) theory and produces the estimation of multiple targets for each line of sight, their range distance and their reflectivities. Moreover, a fast approach for 2D focus based on the FFT algorithm is proposed. After the description of the proposed methodology, different simulated case studies are reported in order to evaluate the performances of the proposed approach. PMID:27136558

  17. Ultrasensitive detection of 3D cerebral microvascular network dynamics in vivo

    PubMed Central

    Pan, Yingtian; You, Jiang; Volkow, Nora D.; Park, Ki; Du, Congwu

    2014-01-01

    Despite widespread applications of multiphoton microscopy in microcirculation, its small field of view and inability to instantaneously quantify cerebral blood flow velocity (CBFv) in vascular networks limit its utility in investigating the heterogeneous responses to brain stimulations. Optical Doppler tomography (ODT) provides 3D images of CBFv networks, but it suffers poor sensitivity for measuring capillary flows. Here we report a new method, contrast-enhanced ODT with intralipid that significantly improves quantitative CBFv imaging of capillary networks by obviating the errors from long latency between flowing red blood cells (low hematocrit ~20% in capillaries). This enhanced sensitivity allowed us to measure the ultraslow microcirculation surrounding a brain tumor and the abnormal ingrowth of capillary flows in the tumor as well as in ischemia triggered by chronic cocaine in the mouse brain that could not be detected by regular ODT. It also enabled significantly enhanced sensitivity for quantifying the heterogeneous CBFv responses of vascular networks to acute cocaine. Inasmuch as intralipids are widely used for parenteral nutrition the intralipid contrast method has translational potential for clinical applications. PMID:25192654

  18. Toward automatic detection of vessel stenoses in cerebral 3D DSA volumes

    NASA Astrophysics Data System (ADS)

    Mualla, F.; Pruemmer, M.; Hahn, D.; Hornegger, J.

    2012-05-01

    Vessel diseases are a very common reason for permanent organ damage, disability and death. This fact necessitates further research for extracting meaningful and reliable medical information from the 3D DSA volumes. Murray's law states that at each branch point of a lumen-based system, the sum of the minor branch diameters each raised to the power x, is equal to the main branch diameter raised to the power x. The principle of minimum work and other factors like the vessel type, impose typical values for the junction exponent x. Therefore, deviations from these typical values may signal pathological cases. In this paper, we state the necessary and the sufficient conditions for the existence and the uniqueness of the solution for x. The second contribution is a scale- and orientation- independent set of features for stenosis classification. A support vector machine classifier was trained in the space of these features. Only one branch was misclassified in a cross validation on 23 branches. The two contributions fit into a pipeline for the automatic detection of the cerebral vessel stenoses.

  19. Multidimensional morphometric 3D MRI analyses for detecting brain abnormalities in children: impact of control population.

    PubMed

    Wilke, Marko; Rose, Douglas F; Holland, Scott K; Leach, James L

    2014-07-01

    Automated morphometric approaches are used to detect epileptogenic structural abnormalities in 3D MR images in adults, using the variance of a control population to obtain z-score maps in an individual patient. Due to the substantial changes the developing human brain undergoes, performing such analyses in children is challenging. This study investigated six features derived from high-resolution T1 datasets in four groups: normal children (1.5T or 3T data), normal clinical scans (3T data), and patients with structural brain lesions (3T data), with each n = 10. Normative control data were obtained from the NIH study on normal brain development (n = 401). We show that control group size substantially influences the captured variance, directly impacting the patient's z-scores. Interestingly, matching on gender does not seem to be beneficial, which was unexpected. Using data obtained at higher field scanners produces slightly different base rates of suprathreshold voxels, as does using clinically derived normal studies, suggesting a subtle but systematic effect of both factors. Two approaches for controlling suprathreshold voxels in a multidimensional approach (combining features and requiring a minimum cluster size) were shown to be substantial and effective in reducing this number. Finally, specific strengths and limitations of such an approach could be demonstrated in individual cases. PMID:25050423

  20. Orienting of visuo-spatial attention in complex 3D space: Search and detection

    PubMed Central

    Ogawa, Akitoshi; Macaluso, Emiliano

    2015-01-01

    The ability to detect changes in the environment is necessary for appropriate interactions with the external world. Changes in the background go more unnoticed than foreground changes, possibly because attention prioritizes processing of foreground/near stimuli. Here, we investigated the detectability of foreground and background changes within natural scenes and the influence of stereoscopic depth cues on this. Using a flicker paradigm, we alternated a pair of images that were exactly same or differed for one single element (i.e., a color change of one object in the scene). The participants were asked to find the change that occurred either in a foreground or background object, while viewing the stimuli either with binocular and monocular cues (bmC) or monocular cues only (mC). The behavioral results showed faster and more accurate detections for foreground changes and overall better performance in bmC than mC conditions. The imaging results highlighted the involvement of fronto-parietal attention controlling networks during active search and target detection. These attention networks did not show any differential effect as function of the presence/absence of the binocular cues, or the detection of foreground/background changes. By contrast, the lateral occipital cortex showed greater activation for detections in foreground compared to background, while area V3A showed a main effect of bmC vs. mC, specifically during search. These findings indicate that visual search with binocular cues does not impose any specific requirement on attention-controlling fronto-parietal networks, while the enhanced detection of front/near objects in the bmC condition reflects bottom-up sensory processes in visual cortex. Hum Brain Mapp 36:2231–2247, 2015. © 2015 The Authors Human Brain Mapping Published by Wiley Periodicals, Inc. PMID:25691253

  1. Detection of 3D tree root systems using high resolution ground penetration radar

    NASA Astrophysics Data System (ADS)

    Altdorff, D.; Honds, M.; Botschek, J.; Van Der Kruk, J.

    2014-12-01

    demonstrated approach is a promising tool for semi-linear root detection, whereas advanced 3D processing and migration is needed for more complicated root structures.

  2. A joint estimation detection of Glaucoma progression in 3D spectral domain optical coherence tomography optic nerve head images

    NASA Astrophysics Data System (ADS)

    Belghith, Akram; Bowd, Christopher; Weinreb, Robert N.; Zangwill, Linda M.

    2014-03-01

    Glaucoma is an ocular disease characterized by distinctive changes in the optic nerve head (ONH) and visual field. Glaucoma can strike without symptoms and causes blindness if it remains without treatment. Therefore, early disease detection is important so that treatment can be initiated and blindness prevented. In this context, important advances in technology for non-invasive imaging of the eye have been made providing quantitative tools to measure structural changes in ONH topography, an essential element for glaucoma detection and monitoring. 3D spectral domain optical coherence tomography (SD-OCT), an optical imaging technique, has been commonly used to discriminate glaucomatous from healthy subjects. In this paper, we present a new framework for detection of glaucoma progression using 3D SD-OCT images. In contrast to previous works that the retinal nerve fiber layer (RNFL) thickness measurement provided by commercially available spectral-domain optical coherence tomograph, we consider the whole 3D volume for change detection. To integrate a priori knowledge and in particular the spatial voxel dependency in the change detection map, we propose the use of the Markov Random Field to handle a such dependency. To accommodate the presence of false positive detection, the estimated change detection map is then used to classify a 3D SDOCT image into the "non-progressing" and "progressing" glaucoma classes, based on a fuzzy logic classifier. We compared the diagnostic performance of the proposed framework to existing methods of progression detection.

  3. Animal testing using 3D microwave tomography system for breast cancer detection.

    PubMed

    Lee, Jong Moon; Son, Sung Ho; Kim, Hyuk Je; Kim, Bo Ra; Choi, Heyng Do; Jeon, Soon Ik

    2014-01-01

    The three dimensional microwave tomography (3D MT) system of the Electronics and Telecommunications Research Institute (ETRI) comprises an antenna array, transmitting receiving module, switch matrix module and a signal processing component. This system also includes a patient interface bed as well as a 3D reconstruction algorithm. Here, we perform a comparative analysis of image reconstruction results using the assembled system and MRI results, which is used to image the breasts of dogs. Microwave imaging reconstruction results (at 1,500 MHz) obtained using the ETRI 3D MT system are presented. The system provides computationally reliable diagnosis results from the reconstructed MT Image. PMID:25160233

  4. Object-oriented philosophy in designing adaptive finite-element package for 3D elliptic deferential equations

    NASA Astrophysics Data System (ADS)

    Zhengyong, R.; Jingtian, T.; Changsheng, L.; Xiao, X.

    2007-12-01

    Although adaptive finite-element (AFE) analysis is becoming more and more focused in scientific and engineering fields, its efficient implementations are remain to be a discussed problem as its more complex procedures. In this paper, we propose a clear C++ framework implementation to show the powerful properties of Object-oriented philosophy (OOP) in designing such complex adaptive procedure. In terms of the modal functions of OOP language, the whole adaptive system is divided into several separate parts such as the mesh generation or refinement, a-posterior error estimator, adaptive strategy and the final post processing. After proper designs are locally performed on these separate modals, a connected framework of adaptive procedure is formed finally. Based on the general elliptic deferential equation, little efforts should be added in the adaptive framework to do practical simulations. To show the preferable properties of OOP adaptive designing, two numerical examples are tested. The first one is the 3D direct current resistivity problem in which the powerful framework is efficiently shown as only little divisions are added. And then, in the second induced polarization£¨IP£©exploration case, new adaptive procedure is easily added which adequately shows the strong extendibility and re-usage of OOP language. Finally we believe based on the modal framework adaptive implementation by OOP methodology, more advanced adaptive analysis system will be available in future.

  5. Europeana and 3D

    NASA Astrophysics Data System (ADS)

    Pletinckx, D.

    2011-09-01

    The current 3D hype creates a lot of interest in 3D. People go to 3D movies, but are we ready to use 3D in our homes, in our offices, in our communication? Are we ready to deliver real 3D to a general public and use interactive 3D in a meaningful way to enjoy, learn, communicate? The CARARE project is realising this for the moment in the domain of monuments and archaeology, so that real 3D of archaeological sites and European monuments will be available to the general public by 2012. There are several aspects to this endeavour. First of all is the technical aspect of flawlessly delivering 3D content over all platforms and operating systems, without installing software. We have currently a working solution in PDF, but HTML5 will probably be the future. Secondly, there is still little knowledge on how to create 3D learning objects, 3D tourist information or 3D scholarly communication. We are still in a prototype phase when it comes to integrate 3D objects in physical or virtual museums. Nevertheless, Europeana has a tremendous potential as a multi-facetted virtual museum. Finally, 3D has a large potential to act as a hub of information, linking to related 2D imagery, texts, video, sound. We describe how to create such rich, explorable 3D objects that can be used intuitively by the generic Europeana user and what metadata is needed to support the semantic linking.

  6. Object-constrained meshless deformable algorithm for high speed 3D nonrigid registration between CT and CBCT

    SciTech Connect

    Chen Ting; Kim, Sung; Goyal, Sharad; Jabbour, Salma; Zhou Jinghao; Rajagopal, Gunaretnum; Haffty, Bruce; Yue Ning

    2010-01-15

    Purpose: High-speed nonrigid registration between the planning CT and the treatment CBCT data is critical for real time image guided radiotherapy (IGRT) to improve the dose distribution and to reduce the toxicity to adjacent organs. The authors propose a new fully automatic 3D registration framework that integrates object-based global and seed constraints with the grayscale-based ''demons'' algorithm. Methods: Clinical objects were segmented on the planning CT images and were utilized as meshless deformable models during the nonrigid registration process. The meshless models reinforced a global constraint in addition to the grayscale difference between CT and CBCT in order to maintain the shape and the volume of geometrically complex 3D objects during the registration. To expedite the registration process, the framework was stratified into hierarchies, and the authors used a frequency domain formulation to diffuse the displacement between the reference and the target in each hierarchy. Also during the registration of pelvis images, they replaced the air region inside the rectum with estimated pixel values from the surrounding rectal wall and introduced an additional seed constraint to robustly track and match the seeds implanted into the prostate. The proposed registration framework and algorithm were evaluated on 15 real prostate cancer patients. For each patient, prostate gland, seminal vesicle, bladder, and rectum were first segmented by a radiation oncologist on planning CT images for radiotherapy planning purpose. The same radiation oncologist also manually delineated the tumor volumes and critical anatomical structures in the corresponding CBCT images acquired at treatment. These delineated structures on the CBCT were only used as the ground truth for the quantitative validation, while structures on the planning CT were used both as the input to the registration method and the ground truth in validation. By registering the planning CT to the CBCT, a

  7. Single cell detection using 3D magnetic rolled-up structures.

    PubMed

    Ger, Tzong-Rong; Huang, Hao-Ting; Huang, Chen-Yu; Lai, Mei-Feng

    2013-11-01

    A 3D rolled-up structure made of a SiO2 layer and a fishbone-like magnetic thin film was proposed here as a biosensor. The magnetoresistance (MR) measurement results of the sensor suggest that the presence of the stray field, which is induced by the magnetic nanoparticles, significantly increased the switching field. Comparing the performance of the 2D sensor and 3D sensor designed in this study, the response in switching field variation was 12.14% in the 2D sensor and 62.55% in the 3D sensor. The response in MR ratio variation was 4.55% in the 2D sensor and 82.32% in the 3D sensor. In addition, the design of the 3D sensor structure also helped to attract and trap a single magnetic cell due to its stronger stray field compared with the 2D structure. The 3D magnetic biosensor designed here can provide important information for future biochip research and applications.

  8. Automatic Building Damage Detection Method Using High-Resolution Remote Sensing Images and 3d GIS Model

    NASA Astrophysics Data System (ADS)

    Tu, Jihui; Sui, Haigang; Feng, Wenqing; Song, Zhina

    2016-06-01

    In this paper, a novel approach of building damaged detection is proposed using high resolution remote sensing images and 3D GIS-Model data. Traditional building damage detection method considers to detect damaged building due to earthquake, but little attention has been paid to analyze various building damaged types(e.g., trivial damaged, severely damaged and totally collapsed.) Therefore, we want to detect the different building damaged type using 2D and 3D feature of scenes because the real world we live in is a 3D space. The proposed method generalizes that the image geometric correction method firstly corrects the post-disasters remote sensing image using the 3D GIS model or RPC parameters, then detects the different building damaged types using the change of the height and area between the pre- and post-disasters and the texture feature of post-disasters. The results, evaluated on a selected study site of the Beichuan earthquake ruins, Sichuan, show that this method is feasible and effective in building damage detection. It has also shown that the proposed method is easily applicable and well suited for rapid damage assessment after natural disasters.

  9. Large-scale computer-generated absorption holograms of 3D objects: I. Theoretical background and visual concepts

    NASA Astrophysics Data System (ADS)

    Cameron, Colin D.; Payne, Douglas A.; Sheerin, David T.; Slinger, Christopher W.; Phillips, Nicholas J.; Dodd, Adrian K.

    1999-03-01

    Over many years, the subject of computer generation of holograms has been visited in various guises. Historically, the obvious restrictions imposed by computational power and computer generated hologram (CGH) fabrication techniques have placed limits on what can be taken seriously in terms of image complexity. Modern advances in computational hardware and electro-optic systems now permit both the calculation and the manufacture of CGH's of complex 3D objects which fill a significant volume of space. New methods permit the recording to be made within a reasonable timescale. In addition to advancing fixed CGH generation techniques, the motivation for the work reported here includes assessment of design algorithms, modulation strategies and image quality metrics. These results are of relevance for a novel electroholography system, currently under development at DERA Malvern. This paper describes a complete process of data generation, computation, data manipulation and recording leading to practical techniques for the creation of large area CGH's. As a support to the advances in theoretical understanding and computational methods, we describe (in Part II) a new laser plotter technique that enables, in principle, an unlimited size of pixel array to be plotted efficiently with a rigorous estimate of duration of the plot run time. The results reported here are limited to 2048 X 2048 pixels. In this example, the novel switching techniques employed on the laser plotter permit the pixel array to be printed in approximately 1 hour. However, paths towards easily raising the pixel count and its associated printing rate are presented for both the computational engine and laser plotting processes.

  10. Automatic loop closure detection using multiple cameras for 3D indoor localization

    NASA Astrophysics Data System (ADS)

    Kua, John; Corso, Nicholas; Zakhor, Avideh

    2012-03-01

    Automated 3D modeling of building interiors is useful in applications such as virtual reality and environment mapping. We have developed a human operated backpack data acquisition system equipped with a variety of sensors such as cameras, laser scanners, and orientation measurement sensors to generate 3D models of building interiors, including uneven surfaces and stairwells. An important intermediate step in any 3D modeling system, including ours, is accurate 6 degrees of freedom localization over time. In this paper, we propose two approaches to improve localization accuracy over our previously proposed methods. First, we develop an adaptive localization algorithm which takes advantage of the environment's floor planarity whenever possible. Secondly, we show that by including all the loop closures resulting from two cameras facing away from each other, it is possible to reduce localization error in scenarios where parts of the acquisition path is retraced. We experimentally characterize the performance gains due to both schemes.

  11. A computational model that recovers the 3D shape of an object from a single 2D retinal representation.

    PubMed

    Li, Yunfeng; Pizlo, Zygmunt; Steinman, Robert M

    2009-05-01

    Human beings perceive 3D shapes veridically, but the underlying mechanisms remain unknown. The problem of producing veridical shape percepts is computationally difficult because the 3D shapes have to be recovered from 2D retinal images. This paper describes a new model, based on a regularization approach, that does this very well. It uses a new simplicity principle composed of four shape constraints: viz., symmetry, planarity, maximum compactness and minimum surface. Maximum compactness and minimum surface have never been used before. The model was tested with random symmetrical polyhedra. It recovered their 3D shapes from a single randomly-chosen 2D image. Neither learning, nor depth perception, was required. The effectiveness of the maximum compactness and the minimum surface constraints were measured by how well the aspect ratio of the 3D shapes was recovered. These constraints were effective; they recovered the aspect ratio of the 3D shapes very well. Aspect ratios recovered by the model were compared to aspect ratios adjusted by four human observers. They also adjusted aspect ratios very well. In those rare cases, in which the human observers showed large errors in adjusted aspect ratios, their errors were very similar to the errors made by the model. PMID:18621410

  12. Multi-view and 3D deformable part models.

    PubMed

    Pepik, Bojan; Stark, Michael; Gehler, Peter; Schiele, Bernt

    2015-11-01

    As objects are inherently 3D, they have been modeled in 3D in the early days of computer vision. Due to the ambiguities arising from mapping 2D features to 3D models, 3D object representations have been neglected and 2D feature-based models are the predominant paradigm in object detection nowadays. While such models have achieved outstanding bounding box detection performance, they come with limited expressiveness, as they are clearly limited in their capability of reasoning about 3D shape or viewpoints. In this work, we bring the worlds of 3D and 2D object representations closer, by building an object detector which leverages the expressive power of 3D object representations while at the same time can be robustly matched to image evidence. To that end, we gradually extend the successful deformable part model [1] to include viewpoint information and part-level 3D geometry information, resulting in several different models with different level of expressiveness. We end up with a 3D object model, consisting of multiple object parts represented in 3D and a continuous appearance model. We experimentally verify that our models, while providing richer object hypotheses than the 2D object models, provide consistently better joint object localization and viewpoint estimation than the state-of-the-art multi-view and 3D object detectors on various benchmarks (KITTI [2] , 3D object classes [3] , Pascal3D+ [4] , Pascal VOC 2007 [5] , EPFL multi-view cars[6] ). PMID:26440264

  13. Increased sensitivity of 3D-Well enzyme-linked immunosorbent assay (ELISA) for infectious disease detection using 3D-printing fabrication technology.

    PubMed

    Singh, Harpal; Shimojima, Masayuki; Fukushi, Shuetsu; Le Van, An; Sugamata, Masami; Yang, Ming

    2015-01-01

    Enzyme-linked Immunosorbent Assay or ELISA -based diagnostics are considered the gold standard in the demonstration of various immunological reaction including in the measurement of antibody response to infectious diseases and to support pathogen identification with application potential in infectious disease outbreaks and individual patients' treatment and clinical care. The rapid prototyping of ELISA-based diagnostics using available 3D printing technologies provides an opportunity for a further exploration of this platform into immunodetection systems. In this study, a '3D-Well' was designed and fabricated using available 3D printing platforms to have an increased surface area of more than 4 times for protein-surface adsorption compared to those of 96-well plates. The ease and rapidity in designing-product development-feedback cycle offered through 3D printing platforms provided an opportunity for its rapid assessment, in which a chemical etching process was used to make the surface hydrophilic followed by validation through the diagnostic performance of ELISA for infectious disease without modifying current laboratory practices for ELISA. The higher sensitivity of the 3D-Well (3-folds higher) compared to the 96-well ELISA provides a potential for the expansion of this technology towards miniaturization platforms to reduce time, volume of reagents and samples needed for laboratory or field diagnosis of infectious diseases including applications in other disciplines.

  14. Increased sensitivity of 3D-Well enzyme-linked immunosorbent assay (ELISA) for infectious disease detection using 3D-printing fabrication technology.

    PubMed

    Singh, Harpal; Shimojima, Masayuki; Fukushi, Shuetsu; Le Van, An; Sugamata, Masami; Yang, Ming

    2015-01-01

    Enzyme-linked Immunosorbent Assay or ELISA -based diagnostics are considered the gold standard in the demonstration of various immunological reaction including in the measurement of antibody response to infectious diseases and to support pathogen identification with application potential in infectious disease outbreaks and individual patients' treatment and clinical care. The rapid prototyping of ELISA-based diagnostics using available 3D printing technologies provides an opportunity for a further exploration of this platform into immunodetection systems. In this study, a '3D-Well' was designed and fabricated using available 3D printing platforms to have an increased surface area of more than 4 times for protein-surface adsorption compared to those of 96-well plates. The ease and rapidity in designing-product development-feedback cycle offered through 3D printing platforms provided an opportunity for its rapid assessment, in which a chemical etching process was used to make the surface hydrophilic followed by validation through the diagnostic performance of ELISA for infectious disease without modifying current laboratory practices for ELISA. The higher sensitivity of the 3D-Well (3-folds higher) compared to the 96-well ELISA provides a potential for the expansion of this technology towards miniaturization platforms to reduce time, volume of reagents and samples needed for laboratory or field diagnosis of infectious diseases including applications in other disciplines. PMID:26406036

  15. Ultra-wide-band 3D microwave imaging scanner for the detection of concealed weapons

    NASA Astrophysics Data System (ADS)

    Rezgui, Nacer-Ddine; Andrews, David A.; Bowring, Nicholas J.

    2015-10-01

    The threat of concealed weapons, explosives and contraband in footwear, bags and suitcases has led to the development of new devices, which can be deployed for security screening. To address known deficiencies of metal detectors and x-rays, an UWB 3D microwave imaging scanning apparatus using FMCW stepped frequency working in the K and Q bands and with a planar scanning geometry based on an x y stage, has been developed to screen suspicious luggage and footwear. To obtain microwave images of the concealed weapons, the targets are placed above the platform and the single transceiver horn antenna attached to the x y stage is moved mechanically to perform a raster scan to create a 2D synthetic aperture array. The S11 reflection signal of the transmitted sweep frequency from the target is acquired by a VNA in synchronism with each position step. To enhance and filter from clutter and noise the raw data and to obtain the 2D and 3D microwave images of the concealed weapons or explosives, data processing techniques are applied to the acquired signals. These techniques include background subtraction, Inverse Fast Fourier Transform (IFFT), thresholding, filtering by gating and windowing and deconvolving with the transfer function of the system using a reference target. To focus the 3D reconstructed microwave image of the target in range and across the x y aperture without using focusing elements, 3D Synthetic Aperture Radar (SAR) techniques are applied to the post-processed data. The K and Q bands, between 15 to 40 GHz, show good transmission through clothing and dielectric materials found in luggage and footwear. A description of the system, algorithms and some results with replica guns and a comparison of microwave images obtained by IFFT, 2D and 3D SAR techniques are presented.

  16. Velocity and Object Detection Using Quaternion Wavelets

    SciTech Connect

    Traversoni, Leonardo; Xu Yi

    2007-09-06

    DStarting from stereoscopic films we detect corresponding objects in both and stablish an epipolar geometry as well as corresponding moving objects are detected and its movement described all using quaternion wavelets and quaternion phase space decomposition.

  17. Automated detection, 3D segmentation and analysis of high resolution spine MR images using statistical shape models

    NASA Astrophysics Data System (ADS)

    Neubert, A.; Fripp, J.; Engstrom, C.; Schwarz, R.; Lauer, L.; Salvado, O.; Crozier, S.

    2012-12-01

    Recent advances in high resolution magnetic resonance (MR) imaging of the spine provide a basis for the automated assessment of intervertebral disc (IVD) and vertebral body (VB) anatomy. High resolution three-dimensional (3D) morphological information contained in these images may be useful for early detection and monitoring of common spine disorders, such as disc degeneration. This work proposes an automated approach to extract the 3D segmentations of lumbar and thoracic IVDs and VBs from MR images using statistical shape analysis and registration of grey level intensity profiles. The algorithm was validated on a dataset of volumetric scans of the thoracolumbar spine of asymptomatic volunteers obtained on a 3T scanner using the relatively new 3D T2-weighted SPACE pulse sequence. Manual segmentations and expert radiological findings of early signs of disc degeneration were used in the validation. There was good agreement between manual and automated segmentation of the IVD and VB volumes with the mean Dice scores of 0.89 ± 0.04 and 0.91 ± 0.02 and mean absolute surface distances of 0.55 ± 0.18 mm and 0.67 ± 0.17 mm respectively. The method compares favourably to existing 3D MR segmentation techniques for VBs. This is the first time IVDs have been automatically segmented from 3D volumetric scans and shape parameters obtained were used in preliminary analyses to accurately classify (100% sensitivity, 98.3% specificity) disc abnormalities associated with early degenerative changes.

  18. Diagnostic Performance of 3D Standing CT Imaging For Detection of Knee Osteoarthritis Features

    PubMed Central

    Segal, Neil A; Nevitt, Michael C.; Lynch, John A; Niu, Jingbo; Torner, James C; Guermazi, Ali

    2016-01-01

    Objective To determine the diagnostic performance of standing computerized tomography (SCT) of the knee for osteophytes and subchondral cysts compared to fixed-flexion radiography, using magnetic resonance imaging (MRI) as the reference standard. Methods Twenty participants were recruited from the Multicenter Osteoarthritis Study (MOST). Participants' knees were imaged with SCT while standing in a knee-positioning frame, and with PA fixed-flexion radiography and 1T MRI. Medial and lateral marginal osteophytes and subchondral cysts were scored on bilateral radiographs and coronal SCT images using the OARSI grading system and on coronal MRI using Whole Organ MRI Scoring (WORMS). Imaging modalities were read separately with images in random order. Sensitivity, specificity, and accuracy for the detection of lesions were calculated and differences between modalities were tested using McNemar's test. Results Participants' mean age was 66.8 years, BMI was 29.6kg/m2 and 50% were women. Of the 160 surfaces (medial and lateral femur and tibia for 40 knees), MRI revealed 84 osteophytes and 10 subchondral cysts. In comparison with osteophytes and subchondral cysts detected by MRI, SCT was significantly more sensitive (93% and 100%; p<0.004) and accurate (95% and 99%; p<0.001 for osteophytes) than plain radiographs (sensitivity: 60% and 10% and accuracy 79% and 94% respectively). For osteophytes, differences in sensitivity and accuracy were greatest at the medial femur (p=0.002). Conclusions In comparison with MRI, SCT imaging was more sensitive and accurate for detection of osteophytes and subchondral cysts than conventional fixed-flexion radiography. Additional study is warranted to assess diagnostic performance of SCT measures of joint space width, progression of OA features and the patellofemoral joint. PMID:26313455

  19. Joint detection of anatomical points on surface meshes and color images for visual registration of 3D dental models

    NASA Astrophysics Data System (ADS)

    Destrez, Raphaël.; Albouy-Kissi, Benjamin; Treuillet, Sylvie; Lucas, Yves

    2015-04-01

    Computer aided planning for orthodontic treatment requires knowing occlusion of separately scanned dental casts. A visual guided registration is conducted starting by extracting corresponding features in both photographs and 3D scans. To achieve this, dental neck and occlusion surface are firstly extracted by image segmentation and 3D curvature analysis. Then, an iterative registration process is conducted during which feature positions are refined, guided by previously found anatomic edges. The occlusal edge image detection is improved by an original algorithm which follows Canny's poorly detected edges using a priori knowledge of tooth shapes. Finally, the influence of feature extraction and position optimization is evaluated in terms of the quality of the induced registration. Best combination of feature detection and optimization leads to a positioning average error of 1.10 mm and 2.03°.

  20. EM modelling of arbitrary shaped anisotropic dielectric objects using an efficient 3D leapfrog scheme on unstructured meshes

    NASA Astrophysics Data System (ADS)

    Gansen, A.; Hachemi, M. El; Belouettar, S.; Hassan, O.; Morgan, K.

    2016-09-01

    The standard Yee algorithm is widely used in computational electromagnetics because of its simplicity and divergence free nature. A generalization of the classical Yee scheme to 3D unstructured meshes is adopted, based on the use of a Delaunay primal mesh and its high quality Voronoi dual. This allows the problem of accuracy losses, which are normally associated with the use of the standard Yee scheme and a staircased representation of curved material interfaces, to be circumvented. The 3D dual mesh leapfrog-scheme which is presented has the ability to model both electric and magnetic anisotropic lossy materials. This approach enables the modelling of problems, of current practical interest, involving structured composites and metamaterials.

  1. Nickel/cobalt oxide-decorated 3D graphene nanocomposite electrode for enhanced electrochemical detection of urea.

    PubMed

    Nguyen, Nhi Sa; Das, Gautam; Yoon, Hyon Hee

    2016-03-15

    A NiCo2O4 bimetallic electro-catalyst was synthesized on three-dimensional graphene (3D graphene) for the non-enzymatic detection of urea. The structural and morphological properties of the NiCo2O4/3D graphene nanocomposite were characterized by X-ray diffraction, Raman spectroscopy, and scanning electron microscopy. The NiCo2O4/3D graphene was deposited on an indium tin oxide (ITO) glass to fabricate a highly sensitive urea sensor. The electrochemical properties of the prepared electrode were studied by cyclic voltammetry. A high sensitivity of 166 μAmM(-)(1)cm(-)(2) was obtained for the NiCo2O4/3D graphene/ITO sensor. The sensor exhibited a linear range of 0.06-0.30 mM (R(2)=0.998) and a fast response time of approximately 1.0 s with a detection limit of 5.0 µM. Additionally, the sensor exhibited high stability with a sensitivity decrease of only 5.5% after four months of storage in ambient conditions. The urea sensor demonstrates feasibility for urea analysis in urine samples.

  2. Nickel/cobalt oxide-decorated 3D graphene nanocomposite electrode for enhanced electrochemical detection of urea.

    PubMed

    Nguyen, Nhi Sa; Das, Gautam; Yoon, Hyon Hee

    2016-03-15

    A NiCo2O4 bimetallic electro-catalyst was synthesized on three-dimensional graphene (3D graphene) for the non-enzymatic detection of urea. The structural and morphological properties of the NiCo2O4/3D graphene nanocomposite were characterized by X-ray diffraction, Raman spectroscopy, and scanning electron microscopy. The NiCo2O4/3D graphene was deposited on an indium tin oxide (ITO) glass to fabricate a highly sensitive urea sensor. The electrochemical properties of the prepared electrode were studied by cyclic voltammetry. A high sensitivity of 166 μAmM(-)(1)cm(-)(2) was obtained for the NiCo2O4/3D graphene/ITO sensor. The sensor exhibited a linear range of 0.06-0.30 mM (R(2)=0.998) and a fast response time of approximately 1.0 s with a detection limit of 5.0 µM. Additionally, the sensor exhibited high stability with a sensitivity decrease of only 5.5% after four months of storage in ambient conditions. The urea sensor demonstrates feasibility for urea analysis in urine samples. PMID:26433071

  3. 3D micro-XRF for cultural heritage objects: new analysis strategies for the investigation of the Dead Sea Scrolls.

    PubMed

    Mantouvalou, Ioanna; Wolff, Timo; Hahn, Oliver; Rabin, Ira; Lühl, Lars; Pagels, Marcel; Malzer, Wolfgang; Kanngiesser, Birgit

    2011-08-15

    A combination of 3D micro X-ray fluorescence spectroscopy (3D micro-XRF) and micro-XRF was utilized for the investigation of a small collection of highly heterogeneous, partly degraded Dead Sea Scroll parchment samples from known excavation sites. The quantitative combination of the two techniques proves to be suitable for the identification of reliable marker elements which may be used for classification and provenance studies. With 3D micro-XRF, the three-dimensional nature, i.e. the depth-resolved elemental composition as well as density variations, of the samples was investigated and bromine could be identified as a suitable marker element. It is shown through a comparison of quantitative and semiquantitative values for the bromine content derived using both techniques that, for elements which are homogeneously distributed in the sample matrix, quantification with micro-XRF using a one-layer model is feasible. Thus, the possibility for routine provenance studies using portable micro-XRF instrumentation on a vast amount of samples, even on site, is obtained through this work.

  4. Interpixel crosstalk in a 3D-integrated active pixel sensor for x-ray detection

    NASA Astrophysics Data System (ADS)

    LaMarr, Beverly; Bautz, Mark; Foster, Rick; Kissel, Steve; Prigozhin, Gregory; Suntharalingam, Vyshnavi

    2010-07-01

    MIT Lincoln Laboratories and MIT Kavli Institute for Astrophysics and Space Research have developed an active pixel sensor for use as a photon counting device for imaging spectroscopy in the soft X-ray band. A silicon-on-insulator (SOI) readout circuit was integrated with a high-resistivity silicon diode detector array using a per-pixel 3D integration technique developed at Lincoln Laboratory. We have tested these devices at 5.9 keV and 1.5 keV. Here we examine the interpixel cross-talk measured with 5.9 keV X-rays.

  5. The foundation of 3D geometry model in omni-directional laser warning system based on diffuse reflection detection

    NASA Astrophysics Data System (ADS)

    Zhang, Weian; Wang, Long; Dong, Qixin

    2011-06-01

    The omni-directional laser warning equipment based on infrared fish-eye lens and short-wave infrared FPA has been used to protect large-scale targets, which can detect the threat laser scattered by the attacked targets or the objects surrounding them, and image the laser spot on FPA, then fix the position of spot. The application offsets the disadvantage of direct interception warner which need disposed largely. Before study of imaging mechanism about the scattered laser spot, the definition of geometry relationship is needed firstly. In this paper we developed a 3D geometry model by analyzing the position relationships in typical battlefield environment among the enemy's threat laser source, the laser spot radiated on one flat surface and our omni-directional laser warning fish-eye lens. The model including R, α, β, d, θ, φ, ψ, δ etc. 8 parameters and 4 coordinate systems was suitable for any general situations. After achievement of the model foundation, we obtained analytic expression of the laser spot contour on flat surface, then attained analytic expression of spot contour on image surface by calculating the object space half-field angle and the azimuth angle relative to fish-eye lens of an arbitrary point at the spot edge on flat surface. The attainment of the expression makes possible that we can analyze the spot energy distributions on image surface and the imaging characteristic of the scattered laser spot via fish-eye lens, then can compute the transmission direction of the threat laser. The foundation of the model in this paper has an importantly basic and guiding meaning to the latter research on this aspect.

  6. Modeling of 3-D Object Manipulation by Multi-Joint Robot Fingers under Non-Holonomic Constraints and Stable Blind Grasping

    NASA Astrophysics Data System (ADS)

    Arimoto, Suguru; Yoshida, Morio; Bae, Ji-Hun

    This paper derives a mathematical model that expresses motion of a pair of multi-joint robot fingers with hemi-spherical rigid ends grasping and manipulating a 3-D rigid object with parallel flat surfaces. Rolling contacts arising between finger-ends and object surfaces are taken into consideration and modeled as Pfaffian constraints from which constraint forces emerge tangentially to the object surfaces. Another noteworthy difference of modeling of motion of a 3-D object from that of a 2-D object is that the instantaneous axis of rotation of the object is fixed in the 2-D case but that is time-varying in the 3-D case. A further difficulty that has prevented us to model 3-D physical interactions between a pair of fingers and a rigid object lies in the problem of treating spinning motion that may arise around the opposing axis from a contact point between one finger-end with one side of the object to another contact point. This paper shows that, once such spinning motion stops as the object mass center approaches just beneath the opposition axis, then this cease of spinning evokes a further nonholonomic constraint. Hence, the multi-body dynamics of the overall fingers-object system is subject to non-holonomic constraints concerning a 3-D orthogonal matrix expressing three mutually orthogonal unit vectors fixed at the object together with an extra non-holonomic constraint that the instantaneous axis of rotation of the object is always orthogonal to the opposing axis. It is shown that Lagrange's equation of motion of the overall system can be derived without violating the causality that governs the non-holonomic constraints. This immediately suggests possible construction of a numerical simulator of multi-body dynamics that can express motion of the fingers and object physically interactive to each other. By referring to the fact that human grasp an object in the form of precision prehension dynamically and stably by using opposable force between the thumb and another

  7. Assessment of Damage Detection in Composite Structures Using 3D Vibrometry

    NASA Astrophysics Data System (ADS)

    Grigg, S.; Pearson, M.; Marks, R.; Featherston, C.; Pullin, R.

    2015-07-01

    Carbon fibre reinforced polymers (CFRP) have been used significantly more in recent years due to their increased specific strength over aluminium structures. One major area in which their use has grown is the aerospace industry where many now use CFRP in their construction. One major problem with CFRP's is their low resistance to impacts. Structural health monitoring (SHM) aims to continually monitor a structure throughout its entire life and can allow aircraft owners to identify impact damage as it occurs. This means that it can be repaired prior to growth, saving weight with the repair and the time that aircraft is grounded. Two areas of SHM being researched are Acoustic Emission (AE) monitoring and AcoustoUltrasonics (AU) both based on an understanding of the propagation of ultrasonic waves. 3D Scanning laser vibrometry was used to monitor the propagation of AU waves with the aim of gaining a better understanding their interaction with delamination in carbon fibre reinforced polymers. Three frequencies were exited with a PZT transducer and the received signal analysed by a cross correlation method. The results from this and the vibrometer scans revealed 100 kHz as the most effective propagating frequency of the three. A high resolution scan was then conducted at this frequency where it could be seen that only the out of plane component of the wave interacted with the damage, in particular the A0 mode. A 3D Fast Fourier Transform was then plotted, which identified the most effective frequency as 160 kHz.

  8. Detection of ancient morphology and potential hydrocarbon traps using 3-D seismic data and attribute analysis

    SciTech Connect

    Heggland, R.

    1995-12-31

    This paper presents the use of seismic attributes on 3D data to reveal Tertiary and Cretaceous geological features in Norwegian block 9/2. Some of the features would hardly be possible to map using only 2D seismic data. The method which involves a precise interpretation of horizons, attribute analysis and manipulation of colour displays, may be useful when studying morphology, faults and hydrocarbon traps. The interval of interest in this study was from 0 to 1.5 s TWT. Horizontal displays (timeslices and attribute maps), seemed to highlight very nicely geological features such as shallow channels, fractures, karst topography and faults. The attributes used for mapping these features were amplitude, total reflection energy (a volume or time interval attribute), dip and azimuth. The choice of colour scale and manipulation of colour displays were also critical for the results. The data examples clearly demonstrate how it is possible to achieve a very detailed mapping of geological features using 3D seismic data and attribute analysis. The results of this study were useful for the understanding of hydrocarbon migration paths and hydrocarbon traps.

  9. Left ventricular endocardial surface detection based on real-time 3D echocardiographic data

    NASA Technical Reports Server (NTRS)

    Corsi, C.; Borsari, M.; Consegnati, F.; Sarti, A.; Lamberti, C.; Travaglini, A.; Shiota, T.; Thomas, J. D.

    2001-01-01

    OBJECTIVE: A new computerized semi-automatic method for left ventricular (LV) chamber segmentation is presented. METHODS: The LV is imaged by real-time three-dimensional echocardiography (RT3DE). The surface detection model, based on level set techniques, is applied to RT3DE data for image analysis. The modified level set partial differential equation we use is solved by applying numerical methods for conservation laws. The initial conditions are manually established on some slices of the entire volume. The solution obtained for each slice is a contour line corresponding with the boundary between LV cavity and LV endocardium. RESULTS: The mathematical model has been applied to sequences of frames of human hearts (volume range: 34-109 ml) imaged by 2D and reconstructed off-line and RT3DE data. Volume estimation obtained by this new semi-automatic method shows an excellent correlation with those obtained by manual tracing (r = 0.992). Dynamic change of LV volume during the cardiac cycle is also obtained. CONCLUSION: The volume estimation method is accurate; edge based segmentation, image completion and volume reconstruction can be accomplished. The visualization technique also allows to navigate into the reconstructed volume and to display any section of the volume.

  10. A collaborative computing framework of cloud network and WBSN applied to fall detection and 3-D motion reconstruction.

    PubMed

    Lai, Chin-Feng; Chen, Min; Pan, Jeng-Shyang; Youn, Chan-Hyun; Chao, Han-Chieh

    2014-03-01

    As cloud computing and wireless body sensor network technologies become gradually developed, ubiquitous healthcare services prevent accidents instantly and effectively, as well as provides relevant information to reduce related processing time and cost. This study proposes a co-processing intermediary framework integrated cloud and wireless body sensor networks, which is mainly applied to fall detection and 3-D motion reconstruction. In this study, the main focuses includes distributed computing and resource allocation of processing sensing data over the computing architecture, network conditions and performance evaluation. Through this framework, the transmissions and computing time of sensing data are reduced to enhance overall performance for the services of fall events detection and 3-D motion reconstruction.

  11. Mii School: New 3D Technologies Applied in Education to Detect Drug Abuses and Bullying in Adolescents

    NASA Astrophysics Data System (ADS)

    Carmona, José Alberto; Espínola, Moisés; Cangas, Adolfo J.; Iribarne, Luis

    Mii School is a 3D school simulator developed with Blender and used by psychology researchers for the detection of drugs abuses, bullying and mental disorders in adolescents. The school simulator created is an interactive video game where the players, in this case the students, have to choose, along 17 scenes simulated, the options that better define their personalities. In this paper we present a technical characteristics description and the first results obtained in a real school.

  12. 3D Mapping of plasma effective areas via detection of cancer cell damage induced by atmospheric pressure plasma jets

    NASA Astrophysics Data System (ADS)

    Han, Xu; Liu, Yueing; Stack, M. Sharon; Ptasinska, Sylwia

    2014-12-01

    In the present study, a nitrogen atmospheric pressure plasma jet (APPJ) was used for irradiation of oral cancer cells. Since cancer cells are very susceptible to plasma treatment, they can be used as a tool for detection of APPJ-effective areas, which extended much further than the visible part of the APPJ. An immunofluorescence assay was used for DNA damage identification, visualization and quantification. Thus, the effective damage area and damage level were determined and plotted as 3D images.

  13. Features of the urban atmosphere as detected by RASS and 3D sonics

    NASA Astrophysics Data System (ADS)

    Piringer, Martin; Lotteraner, Christoph

    2010-05-01

    In contrast to the classical homogeneous atmospheric boundary layer, the urban boundary layer is more complex due to several specific features and processes caused by the buildings which introduce a large amount of vertical surfaces, high roughness elements, and artificial materials. The most well-known result is the urban heat island, but urban areas also influence the wind field, precipitation, atmospheric stability, and the mixing height. The last two are essential to determine the spread of pollutants in urban areas. Atmospheric stability can properly be derived with 3D sonics via the sensible heat flux; The mixing height can be deduced from vertical temperature profiles provided by Sodar-RASS systems. The contribution will highlight the methodologies, give examples, and critically discuss advantages and shortcomings of the instruments and the methods applied.

  14. Is the effect of 3-D viscosity distributions on postseismic gravity variations detectable?

    NASA Astrophysics Data System (ADS)

    Tanaka, Yoshiyuki

    2016-04-01

    Satellite gravity measurements by GRACE and GOCE have successfully revealed postseismic mass transports caused by megathrust earthquakes. So far, several physical models to interpret the variations in the gravity field have been constructed. Some models consider the effects of self-gravitation and compressibility and others heterogeneous viscoelastic structures. Previous studies have already shown that the effects of compressibility are not negligible compared with the observation accuracy of gravity data. In this presentation, we estimate the effect of lateral heterogeneities in viscosity due to the presence of a subducting slab, using a spectral finite-element approach. This time-domain approach allows us to account for 3-D viscosity distributions without the necessity of artificial surface boundary conditions as used in an ordinary finite-element model. It is also possible to consider compressibility without technical difficulties which conventional normal mode methods encounter. As an example, we compare our model with recent gravity solutions in the case of the 2011 M-9 Tohoku earthquake. When the spatial resolution is increased up to d/o 80, the difference caused by considering the slab can reach 10 cm in equivalent water height at the center of the negative coseismic signal after the first 4 years from the main shock. This difference amounts to 20 per cent of the coseismic signal. The result indicates that satellite gravity data are potentially useful for investigating 3-D viscosity distributions in relatively shallow portions in the subduction zones, which will help predict the stress behaviors there in the context of earthquake cycles.

  15. Low-Cost 3D Printers Enable High-Quality and Automated Sample Preparation and Molecular Detection

    PubMed Central

    Chan, Kamfai; Coen, Mauricio; Hardick, Justin; Gaydos, Charlotte A.; Wong, Kah-Yat; Smith, Clayton; Wilson, Scott A.; Vayugundla, Siva Praneeth; Wong, Season

    2016-01-01

    Most molecular diagnostic assays require upfront sample preparation steps to isolate the target’s nucleic acids, followed by its amplification and detection using various nucleic acid amplification techniques. Because molecular diagnostic methods are generally rather difficult to perform manually without highly trained users, automated and integrated systems are highly desirable but too costly for use at point-of-care or low-resource settings. Here, we showcase the development of a low-cost and rapid nucleic acid isolation and amplification platform by modifying entry-level 3D printers that cost between $400 and $750. Our modifications consisted of replacing the extruder with a tip-comb attachment that houses magnets to conduct magnetic particle-based nucleic acid extraction. We then programmed the 3D printer to conduct motions that can perform high-quality extraction protocols. Up to 12 samples can be processed simultaneously in under 13 minutes and the efficiency of nucleic acid isolation matches well against gold-standard spin-column-based extraction technology. Additionally, we used the 3D printer’s heated bed to supply heat to perform water bath-based polymerase chain reactions (PCRs). Using another attachment to hold PCR tubes, the 3D printer was programmed to automate the process of shuttling PCR tubes between water baths. By eliminating the temperature ramping needed in most commercial thermal cyclers, the run time of a 35-cycle PCR protocol was shortened by 33%. This article demonstrates that for applications in resource-limited settings, expensive nucleic acid extraction devices and thermal cyclers that are used in many central laboratories can be potentially replaced by a device modified from inexpensive entry-level 3D printers. PMID:27362424

  16. Low-Cost 3D Printers Enable High-Quality and Automated Sample Preparation and Molecular Detection.

    PubMed

    Chan, Kamfai; Coen, Mauricio; Hardick, Justin; Gaydos, Charlotte A; Wong, Kah-Yat; Smith, Clayton; Wilson, Scott A; Vayugundla, Siva Praneeth; Wong, Season

    2016-01-01

    Most molecular diagnostic assays require upfront sample preparation steps to isolate the target's nucleic acids, followed by its amplification and detection using various nucleic acid amplification techniques. Because molecular diagnostic methods are generally rather difficult to perform manually without highly trained users, automated and integrated systems are highly desirable but too costly for use at point-of-care or low-resource settings. Here, we showcase the development of a low-cost and rapid nucleic acid isolation and amplification platform by modifying entry-level 3D printers that cost between $400 and $750. Our modifications consisted of replacing the extruder with a tip-comb attachment that houses magnets to conduct magnetic particle-based nucleic acid extraction. We then programmed the 3D printer to conduct motions that can perform high-quality extraction protocols. Up to 12 samples can be processed simultaneously in under 13 minutes and the efficiency of nucleic acid isolation matches well against gold-standard spin-column-based extraction technology. Additionally, we used the 3D printer's heated bed to supply heat to perform water bath-based polymerase chain reactions (PCRs). Using another attachment to hold PCR tubes, the 3D printer was programmed to automate the process of shuttling PCR tubes between water baths. By eliminating the temperature ramping needed in most commercial thermal cyclers, the run time of a 35-cycle PCR protocol was shortened by 33%. This article demonstrates that for applications in resource-limited settings, expensive nucleic acid extraction devices and thermal cyclers that are used in many central laboratories can be potentially replaced by a device modified from inexpensive entry-level 3D printers.

  17. Low-Cost 3D Printers Enable High-Quality and Automated Sample Preparation and Molecular Detection.

    PubMed

    Chan, Kamfai; Coen, Mauricio; Hardick, Justin; Gaydos, Charlotte A; Wong, Kah-Yat; Smith, Clayton; Wilson, Scott A; Vayugundla, Siva Praneeth; Wong, Season

    2016-01-01

    Most molecular diagnostic assays require upfront sample preparation steps to isolate the target's nucleic acids, followed by its amplification and detection using various nucleic acid amplification techniques. Because molecular diagnostic methods are generally rather difficult to perform manually without highly trained users, automated and integrated systems are highly desirable but too costly for use at point-of-care or low-resource settings. Here, we showcase the development of a low-cost and rapid nucleic acid isolation and amplification platform by modifying entry-level 3D printers that cost between $400 and $750. Our modifications consisted of replacing the extruder with a tip-comb attachment that houses magnets to conduct magnetic particle-based nucleic acid extraction. We then programmed the 3D printer to conduct motions that can perform high-quality extraction protocols. Up to 12 samples can be processed simultaneously in under 13 minutes and the efficiency of nucleic acid isolation matches well against gold-standard spin-column-based extraction technology. Additionally, we used the 3D printer's heated bed to supply heat to perform water bath-based polymerase chain reactions (PCRs). Using another attachment to hold PCR tubes, the 3D printer was programmed to automate the process of shuttling PCR tubes between water baths. By eliminating the temperature ramping needed in most commercial thermal cyclers, the run time of a 35-cycle PCR protocol was shortened by 33%. This article demonstrates that for applications in resource-limited settings, expensive nucleic acid extraction devices and thermal cyclers that are used in many central laboratories can be potentially replaced by a device modified from inexpensive entry-level 3D printers. PMID:27362424

  18. 3D Detection, Quantification and Correlation of Slope Failures with Geologic Structure in the Mont Blanc massif

    NASA Astrophysics Data System (ADS)

    Allan, Mark; Dunning, Stuart; Lim, Michael; Woodward, John

    2016-04-01

    A thorough understanding of supply from landslides and knowledge of their spatial distribution is of fundamental importance to high-mountain sediment budgets. Advances in 3D data acquisition techniques are heralding new opportunities to create high-resolution topographic models to aid our understanding of landscape change through time. In this study, we use a Structure-from-Motion Multi-View Stereo (SfM-MVS) approach to detect and quantify slope failures at selected sites in the Mont Blanc massif. Past and present glaciations along with its topographical characteristics have resulted in a high rate of geomorphological activity within the range. Data for SfM-MVS processing were captured across variable temporal scales to examine short-term (daily), seasonal and annual change from terrestrial, Unmanned Aerial Vehicle (UAV) and helicopter perspectives. Variable spatial scales were also examined ranging from small focussed slopes (~0.01 km2) to large valley-scale surveys (~3 km2). Alignment and registration were conducted using a series of Ground Control Points (GCPs) across the surveyed slope at various heights and slope aspects. GCPs were also used to optimise data and reduce non-linear distortions. 3D differencing was performed using a multiscale model-to-model comparison algorithm (M3C2) which uses variable thresholding across each slope based on local surface roughness and model alignment quality. Detected change was correlated with local slope structure and 3D discontinuity analysis was undertaken using a plane-detection and clustering approach (DSE). Computation of joint spacing was performed using the classified data and normal distances. Structural analysis allowed us to assign a Slope Mass Rating (SMR) and assess the stability of each slope relative to the detected change and determine likely failure modes. We demonstrate an entirely 3D workflow which preserves the complexity of alpine slope topography to compute volumetric loss using a variable threshold. A

  19. 3D parallel-detection microwave tomography for clinical breast imaging

    NASA Astrophysics Data System (ADS)

    Epstein, N. R.; Meaney, P. M.; Paulsen, K. D.

    2014-12-01

    A biomedical microwave tomography system with 3D-imaging capabilities has been constructed and translated to the clinic. Updates to the hardware and reconfiguration of the electronic-network layouts in a more compartmentalized construct have streamlined system packaging. Upgrades to the data acquisition and microwave components have increased data-acquisition speeds and improved system performance. By incorporating analog-to-digital boards that accommodate the linear amplification and dynamic-range coverage our system requires, a complete set of data (for a fixed array position at a single frequency) is now acquired in 5.8 s. Replacement of key components (e.g., switches and power dividers) by devices with improved operational bandwidths has enhanced system response over a wider frequency range. High-integrity, low-power signals are routinely measured down to -130 dBm for frequencies ranging from 500 to 2300 MHz. Adequate inter-channel isolation has been maintained, and a dynamic range >110 dB has been achieved for the full operating frequency range (500-2900 MHz). For our primary band of interest, the associated measurement deviations are less than 0.33% and 0.5° for signal amplitude and phase values, respectively. A modified monopole antenna array (composed of two interwoven eight-element sub-arrays), in conjunction with an updated motion-control system capable of independently moving the sub-arrays to various in-plane and cross-plane positions within the illumination chamber, has been configured in the new design for full volumetric data acquisition. Signal-to-noise ratios (SNRs) are more than adequate for all transmit/receive antenna pairs over the full frequency range and for the variety of in-plane and cross-plane configurations. For proximal receivers, in-plane SNRs greater than 80 dB are observed up to 2900 MHz, while cross-plane SNRs greater than 80 dB are seen for 6 cm sub-array spacing (for frequencies up to 1500 MHz). We demonstrate accurate recovery

  20. 3D parallel-detection microwave tomography for clinical breast imaging

    PubMed Central

    Meaney, P. M.; Paulsen, K. D.

    2014-01-01

    A biomedical microwave tomography system with 3D-imaging capabilities has been constructed and translated to the clinic. Updates to the hardware and reconfiguration of the electronic-network layouts in a more compartmentalized construct have streamlined system packaging. Upgrades to the data acquisition and microwave components have increased data-acquisition speeds and improved system performance. By incorporating analog-to-digital boards that accommodate the linear amplification and dynamic-range coverage our system requires, a complete set of data (for a fixed array position at a single frequency) is now acquired in 5.8 s. Replacement of key components (e.g., switches and power dividers) by devices with improved operational bandwidths has enhanced system response over a wider frequency range. High-integrity, low-power signals are routinely measured down to −130 dBm for frequencies ranging from 500 to 2300 MHz. Adequate inter-channel isolation has been maintained, and a dynamic range >110 dB has been achieved for the full operating frequency range (500–2900 MHz). For our primary band of interest, the associated measurement deviations are less than 0.33% and 0.5° for signal amplitude and phase values, respectively. A modified monopole antenna array (composed of two interwoven eight-element sub-arrays), in conjunction with an updated motion-control system capable of independently moving the sub-arrays to various in-plane and cross-plane positions within the illumination chamber, has been configured in the new design for full volumetric data acquisition. Signal-to-noise ratios (SNRs) are more than adequate for all transmit/receive antenna pairs over the full frequency range and for the variety of in-plane and cross-plane configurations. For proximal receivers, in-plane SNRs greater than 80 dB are observed up to 2900 MHz, while cross-plane SNRs greater than 80 dB are seen for 6 cm sub-array spacing (for frequencies up to 1500 MHz). We demonstrate accurate

  1. 3D parallel-detection microwave tomography for clinical breast imaging

    SciTech Connect

    Epstein, N. R.; Meaney, P. M.; Paulsen, K. D.

    2014-12-15

    A biomedical microwave tomography system with 3D-imaging capabilities has been constructed and translated to the clinic. Updates to the hardware and reconfiguration of the electronic-network layouts in a more compartmentalized construct have streamlined system packaging. Upgrades to the data acquisition and microwave components have increased data-acquisition speeds and improved system performance. By incorporating analog-to-digital boards that accommodate the linear amplification and dynamic-range coverage our system requires, a complete set of data (for a fixed array position at a single frequency) is now acquired in 5.8 s. Replacement of key components (e.g., switches and power dividers) by devices with improved operational bandwidths has enhanced system response over a wider frequency range. High-integrity, low-power signals are routinely measured down to −130 dBm for frequencies ranging from 500 to 2300 MHz. Adequate inter-channel isolation has been maintained, and a dynamic range >110 dB has been achieved for the full operating frequency range (500–2900 MHz). For our primary band of interest, the associated measurement deviations are less than 0.33% and 0.5° for signal amplitude and phase values, respectively. A modified monopole antenna array (composed of two interwoven eight-element sub-arrays), in conjunction with an updated motion-control system capable of independently moving the sub-arrays to various in-plane and cross-plane positions within the illumination chamber, has been configured in the new design for full volumetric data acquisition. Signal-to-noise ratios (SNRs) are more than adequate for all transmit/receive antenna pairs over the full frequency range and for the variety of in-plane and cross-plane configurations. For proximal receivers, in-plane SNRs greater than 80 dB are observed up to 2900 MHz, while cross-plane SNRs greater than 80 dB are seen for 6 cm sub-array spacing (for frequencies up to 1500 MHz). We demonstrate accurate

  2. Orbital objects detection algorithm using faint streaks

    NASA Astrophysics Data System (ADS)

    Tagawa, Makoto; Yanagisawa, Toshifumi; Kurosaki, Hirohisa; Oda, Hiroshi; Hanada, Toshiya

    2016-02-01

    This study proposes an algorithm to detect orbital objects that are small or moving at high apparent velocities from optical images by utilizing their faint streaks. In the conventional object-detection algorithm, a high signal-to-noise-ratio (e.g., 3 or more) is required, whereas in our proposed algorithm, the signals are summed along the streak direction to improve object-detection sensitivity. Lower signal-to-noise ratio objects were detected by applying the algorithm to a time series of images. The algorithm comprises the following steps: (1) image skewing, (2) image compression along the vertical axis, (3) detection and determination of streak position, (4) searching for object candidates using the time-series streak-position data, and (5) selecting the candidate with the best linearity and reliability. Our algorithm's ability to detect streaks with signals weaker than the background noise was confirmed using images from the Australia Remote Observatory.

  3. Combining a wavelet transform with a channelized Hotelling observer for tumor detection in 3D PET oncology imaging

    NASA Astrophysics Data System (ADS)

    Lartizien, Carole; Tomei, Sandrine; Maxim, Voichita; Odet, Christophe

    2007-03-01

    This study evaluates new observer models for 3D whole-body Positron Emission Tomography (PET) imaging based on a wavelet sub-band decomposition and compares them with the classical constant-Q CHO model. Our final goal is to develop an original method that performs guided detection of abnormal activity foci in PET oncology imaging based on these new observer models. This computer-aided diagnostic method would highly benefit to clinicians for diagnostic purpose and to biologists for massive screening of rodents populations in molecular imaging. Method: We have previously shown good correlation of the channelized Hotelling observer (CHO) using a constant-Q model with human observer performance for 3D PET oncology imaging. We propose an alternate method based on combining a CHO observer with a wavelet sub-band decomposition of the image and we compare it to the standard CHO implementation. This method performs an undecimated transform using a biorthogonal B-spline 4/4 wavelet basis to extract the features set for input to the Hotelling observer. This work is based on simulated 3D PET images of an extended MCAT phantom with randomly located lesions. We compare three evaluation criteria: classification performance using the signal-to-noise ratio (SNR), computation efficiency and visual quality of the derived 3D maps of the decision variable λ. The SNR is estimated on a series of test images for a variable number of training images for both observers. Results: Results show that the maximum SNR is higher with the constant-Q CHO observer, especially for targets located in the liver, and that it is reached with a smaller number of training images. However, preliminary analysis indicates that the visual quality of the 3D maps of the decision variable λ is higher with the wavelet-based CHO and the computation time to derive a 3D λ-map is about 350 times shorter than for the standard CHO. This suggests that the wavelet-CHO observer is a good candidate for use in our guided

  4. Azo-Based Iridium(III) Complexes as Multicolor Phosphorescent Probes to Detect Hypoxia in 3D Multicellular Tumor Spheroids

    PubMed Central

    Sun, Lingli; Li, Guanying; Chen, Xiang; Chen, Yu; Jin, Chengzhi; Ji, Liangnian; Chao, Hui

    2015-01-01

    Hypoxia is an important characteristic of malignant solid tumors and is considered as a possible causative factor for serious resistance to chemo- and radiotherapy. The exploration of novel fluorescent probes capable of detecting hypoxia in solid tumors will aid tumor diagnosis and treatment. In this study, we reported the design and synthesis of a series of “off-on” phosphorescence probes for hypoxia detection in adherent and three-dimensional multicellular spheroid models. All of the iridium(III) complexes incorporate an azo group as an azo-reductase reactive moiety to detect hypoxia. Reduction of non-phosphorescent probes Ir1-Ir8 by reductases under hypoxic conditions resulted in the generation of highly phosphorescent corresponding amines for detection of hypoxic regions. Moreover, these probes can penetrate into 3D multicellular spheroids over 100 μm and image the hypoxic regions. Most importantly, these probes display a high selectivity for the detection of hypoxia in 2D cells and 3D multicellular spheroids. PMID:26423609

  5. 3D Face Model Dataset: Automatic Detection of Facial Expressions and Emotions for Educational Environments

    ERIC Educational Resources Information Center

    Chickerur, Satyadhyan; Joshi, Kartik

    2015-01-01

    Emotion detection using facial images is a technique that researchers have been using for the last two decades to try to analyze a person's emotional state given his/her image. Detection of various kinds of emotion using facial expressions of students in educational environment is useful in providing insight into the effectiveness of tutoring…

  6. 3D and Education

    NASA Astrophysics Data System (ADS)

    Meulien Ohlmann, Odile

    2013-02-01

    Today the industry offers a chain of 3D products. Learning to "read" and to "create in 3D" becomes an issue of education of primary importance. 25 years professional experience in France, the United States and Germany, Odile Meulien set up a personal method of initiation to 3D creation that entails the spatial/temporal experience of the holographic visual. She will present some different tools and techniques used for this learning, their advantages and disadvantages, programs and issues of educational policies, constraints and expectations related to the development of new techniques for 3D imaging. Although the creation of display holograms is very much reduced compared to the creation of the 90ies, the holographic concept is spreading in all scientific, social, and artistic activities of our present time. She will also raise many questions: What means 3D? Is it communication? Is it perception? How the seeing and none seeing is interferes? What else has to be taken in consideration to communicate in 3D? How to handle the non visible relations of moving objects with subjects? Does this transform our model of exchange with others? What kind of interaction this has with our everyday life? Then come more practical questions: How to learn creating 3D visualization, to learn 3D grammar, 3D language, 3D thinking? What for? At what level? In which matter? for whom?

  7. A robust and efficient approach to detect 3D rectal tubes from CT colonography

    SciTech Connect

    Yang Xiaoyun; Slabaugh, Greg

    2011-11-15

    Purpose: The rectal tube (RT) is a common source of false positives (FPs) in computer-aided detection (CAD) systems for CT colonography. A robust and efficient detection of RT can improve CAD performance by eliminating such ''obvious'' FPs and increase radiologists' confidence in CAD. Methods: In this paper, we present a novel and robust bottom-up approach to detect the RT. Probabilistic models, trained using kernel density estimation on simple low-level features, are employed to rank and select the most likely RT tube candidate on each axial slice. Then, a shape model, robustly estimated using random sample consensus (RANSAC), infers the global RT path from the selected local detections. Subimages around the RT path are projected into a subspace formed from training subimages of the RT. A quadratic discriminant analysis (QDA) provides a classification of a subimage as RT or non-RT based on the projection. Finally, a bottom-top clustering method is proposed to merge the classification predictions together to locate the tip position of the RT. Results: Our method is validated using a diverse database, including data from five hospitals. On a testing data with 21 patients (42 volumes), 99.5% of annotated RT paths have been successfully detected. Evaluated with CAD, 98.4% of FPs caused by the RT have been detected and removed without any loss of sensitivity. Conclusions: The proposed method demonstrates a high detection rate of the RT path, and when tested in a CAD system, reduces FPs caused by the RT without the loss of sensitivity.

  8. Buried object detection in GPR images

    DOEpatents

    Paglieroni, David W; Chambers, David H; Bond, Steven W; Beer, W. Reginald

    2014-04-29

    A method and system for detecting the presence of subsurface objects within a medium is provided. In some embodiments, the imaging and detection system operates in a multistatic mode to collect radar return signals generated by an array of transceiver antenna pairs that is positioned across the surface and that travels down the surface. The imaging and detection system pre-processes the return signal to suppress certain undesirable effects. The imaging and detection system then generates synthetic aperture radar images from real aperture radar images generated from the pre-processed return signal. The imaging and detection system then post-processes the synthetic aperture radar images to improve detection of subsurface objects. The imaging and detection system identifies peaks in the energy levels of the post-processed image frame, which indicates the presence of a subsurface object.

  9. A robust method to detect zero velocity for improved 3D personal navigation using inertial sensors.

    PubMed

    Xu, Zhengyi; Wei, Jianming; Zhang, Bo; Yang, Weijun

    2015-01-01

    This paper proposes a robust zero velocity (ZV) detector algorithm to accurately calculate stationary periods in a gait cycle. The proposed algorithm adopts an effective gait cycle segmentation method and introduces a Bayesian network (BN) model based on the measurements of inertial sensors and kinesiology knowledge to infer the ZV period. During the detected ZV period, an Extended Kalman Filter (EKF) is used to estimate the error states and calibrate the position error. The experiments reveal that the removal rate of ZV false detections by the proposed method increases 80% compared with traditional method at high walking speed. Furthermore, based on the detected ZV, the Personal Inertial Navigation System (PINS) algorithm aided by EKF performs better, especially in the altitude aspect. PMID:25831086

  10. Coherent digital demodulation of single-camera N-projections for 3D-object shape measurement: co-phased profilometry.

    PubMed

    Servin, M; Garnica, G; Estrada, J C; Quiroga, A

    2013-10-21

    Fringe projection profilometry is a well-known technique to digitize 3-dimensional (3D) objects and it is widely used in robotic vision and industrial inspection. Probably the single most important problem in single-camera, single-projection profilometry are the shadows and specular reflections generated by the 3D object under analysis. Here a single-camera along with N-fringe-projections is (digital) coherent demodulated in a single-step, solving the shadows and specular reflections problem. Co-phased profilometry coherently phase-demodulates a whole set of N-fringe-pattern perspectives in a single demodulation and unwrapping process. The mathematical theory behind digital co-phasing N-fringe-patterns is mathematically similar to co-phasing a segmented N-mirror telescope.

  11. Optical display of magnified, real and orthoscopic 3-D object images by moving-direct-pixel-mapping in the scalable integral-imaging system

    NASA Astrophysics Data System (ADS)

    Zhang, Miao; Piao, Yongri; Kim, Eun-Soo

    2011-10-01

    In this paper, we proposed a novel approach for reconstruction of the magnified, real and orthoscopic three-dimensional (3-D) object images by using the moving-direct-pixel-mapping (MDPM) method in the MALT(moving-array-lenslet-technique)-based scalable integral-imaging system. In the proposed system, multiple sets of elemental image arrays (EIAs) are captured with the MALT, and these picked-up EIAs are computationally transformed into the depth-converted ones by using the proposed MDPM method. Then, these depth-converted EIAs are combined and interlaced together to form an enlarged EIA, from which a magnified, real and orthoscopic 3-D object images can be optically displayed without any degradation of resolution. Good experimental results finally confirmed the feasibility of the proposed method.

  12. 3D element imaging using NSECT for the detection of renal cancer: a simulation study in MCNP

    NASA Astrophysics Data System (ADS)

    Viana, R. S.; Agasthya, G. A.; Yoriyaz, H.; Kapadia, A. J.

    2013-09-01

    This work describes a simulation study investigating the application of neutron stimulated emission computed tomography (NSECT) for noninvasive 3D imaging of renal cancer in vivo. Using MCNP5 simulations, we describe a method of diagnosing renal cancer in the body by mapping the 3D distribution of elements present in tumors using the NSECT technique. A human phantom containing the kidneys and other major organs was modeled in MCNP5. The element composition of each organ was based on values reported in literature. The two kidneys were modeled to contain elements reported in renal cell carcinoma (RCC) and healthy kidney tissue. Simulated NSECT scans were executed to determine the 3D element distribution of the phantom body. Elements specific to RCC and healthy kidney tissue were then analyzed to identify the locations of the diseased and healthy kidneys and generate tomographic images of the tumor. The extent of the RCC lesion inside the kidney was determined using 3D volume rendering. A similar procedure was used to generate images of each individual organ in the body. Six isotopes were studied in this work—32S, 12C, 23Na, 14N, 31P and 39K. The results demonstrated that through a single NSECT scan performed in vivo, it is possible to identify the location of the kidneys and other organs within the body, determine the extent of the tumor within the organ, and to quantify the differences between cancer and healthy tissue-related isotopes with p ≤ 0.05. All of the images demonstrated appropriate concentration changes between the organs, with some discrepancy observed in 31P, 39K and 23Na. The discrepancies were likely due to the low concentration of the elements in the tissue that were below the current detection sensitivity of the NSECT technique.

  13. 3D modeling of circumferential SH guided waves in pipeline for axial cracking detection in ILI tools.

    PubMed

    Wang, Shen; Huang, Songling; Zhao, Wei; Wei, Zheng

    2015-02-01

    In this paper, SH (shear horizontal) guided waves propagating in the circumferential direction of pipeline are modeled in 3 dimensions, with the aim for axial cracking detection implementation in ILI (in-line inspection) tools in mind. A theoretical formulation is given first, followed by an explanation about the 3D numerical modeling work. Displacement wave structures from the simulation and dispersion equation are compared to verify the effectiveness of the FEM package. Transverse slots along the axial direction are modeled to simulate axial cracking. Reflection and transmission coefficients curves are obtained to provide insight in using circumferential SH guided waves for quantitative testing of axial pipeline cracking.

  14. Interpretation of Magnetic Anomalies in Salihli (Turkey) Geothermal Area Using 3-D Inversion and Edge Detection Techniques

    NASA Astrophysics Data System (ADS)

    Timur, Emre

    2016-04-01

    There are numerous geophysical methods used to investigate geothermal areas. The major purpose of this magnetic survey is to locate the boudaries of active hydrothermal system in the South of Gediz Graben in Salihli (Manisa/Turkey). The presence of the hydrothermal system had already been inferred from surface evidence of hydrothermal activity and drillings. Firstly, 3-D prismatic models were theoretically investigated and edge detection methods were utilized with an iterative inversion method to define the boundaries and the parameters of the structure. In the first step of the application, it was necessary to convert the total field anomaly into a pseudo-gravity anomaly map. Then the geometric boudaries of the structures were determined by applying a MATLAB based software with 3 different edge detection algorithms. The exact location of the structures were obtained by using these boundary coordinates as initial geometric parameters in the inversion process. In addition to these methods, reduction to pole and horizontal gradient methods were applied to the data to achieve more information about the location and shape of the possible reservoir. As a result, the edge detection methods were found to be successful, both in the field and as theoretical data sets for delineating the boundaries of the possible geothermal reservoir structure. The depth of the geothermal reservoir was determined as 2,4 km from 3-D inversion and 2,1 km from power spectrum methods.

  15. Detecting VMAT delivery errors: A study on the sensitivity of the ArcCHECK-3D electronic dosimeter

    NASA Astrophysics Data System (ADS)

    Arumugam, S.; Xing, A.; Goozee, G.; Holloway, L.

    2013-06-01

    The sensitivity of the ArcCHECK 3D dosimeter in detecting VMAT delivery errors has been investigated. Dose and leaf positional errors of different magnitudes were introduced to whole arc and individual control points (CPs) of a simple open arc VMAT plan. The error introduced and error free plans were delivered and measured using the ArcCHECK device. The measured doses were compared against the treatment planning system calculated doses using gamma (γ) criteria with 2%/2mm and 3%/3mm tolerance levels. ArcCHECK effectively detected the dose errors resulting from MLC leaf positioning errors in limited CPs and Whole arc. For errors introduced to MU, ArcCHECK effectively detected the MU delivery errors in whole arc but not the MU errors introduced to CPs in integrated dose comparison.

  16. Voltage compensation based calibration measurement of 3D-acceleration transducer in fall detection system for the elderly.

    PubMed

    Zheng, Li; Wang, Lu; He, Dianning; Geng, Ning; Geng, Ping; Guan, Dejun; Xu, Lisheng

    2014-01-01

    The fall detection algorithm, which can recognize the fall of human body by collecting the acceleration signals in different directions of the body, is an important part of fall detection system for the elderly. The system, however, may have errors during analyzing the acceleration signal, due to that the coordinate system of the transducer does not coincide with the one of human motion. Furthermore, voltage variation of the battery also influences the accuracy of the acceleration signal. Therefore, in this paper, a fall detection system based on the 3D-acceleration transducer MMA7260 is designed, which can calibrate the acceleration data through compensation of voltage and transformation of coordinates. Experiments illustrated that the proposed method can accurately transform the collected data from the coordinate system of the transducer to that of the human motion, and can recognize various postural changes in the course of the motion of human body.

  17. Damage detection in reusable launch vehicle components using guided ultrasonic waves and 3D laser vibrometry

    NASA Astrophysics Data System (ADS)

    Barnoncel, David; Staszewski, Wieslaw J.; Schell, Jochen; Peres, Patrick

    2013-04-01

    Reusable Launch Vehicles are often used in space applications to guarantee space exploration with reduced costs. These structures often use components from newly developed materials. It is inevitable that reliable inspection methods will be required for quality control and maintenance of such structures to avoid potential damage. This paper describes some initial results from evaluation tests based on Lamb waves for damage detection of Reusable Launch Vehicle composite components. Low-profile, surface-bonded piezoceramic transducers were used for Lamb wave generation. Non-contact measurements of Lamb wave responses were taken by a laser vibrometer. The results presented in this paper demonstrate the great potential of the method for quality inspection and structural damage detection of space composite structures.

  18. A comparison of moving object detection methods for real-time moving object detection

    NASA Astrophysics Data System (ADS)

    Roshan, Aditya; Zhang, Yun

    2014-06-01

    Moving object detection has a wide variety of applications from traffic monitoring, site monitoring, automatic theft identification, face detection to military surveillance. Many methods have been developed across the globe for moving object detection, but it is very difficult to find one which can work globally in all situations and with different types of videos. The purpose of this paper is to evaluate existing moving object detection methods which can be implemented in software on a desktop or laptop, for real time object detection. There are several moving object detection methods noted in the literature, but few of them are suitable for real time moving object detection. Most of the methods which provide for real time movement are further limited by the number of objects and the scene complexity. This paper evaluates the four most commonly used moving object detection methods as background subtraction technique, Gaussian mixture model, wavelet based and optical flow based methods. The work is based on evaluation of these four moving object detection methods using two (2) different sets of cameras and two (2) different scenes. The moving object detection methods have been implemented using MatLab and results are compared based on completeness of detected objects, noise, light change sensitivity, processing time etc. After comparison, it is observed that optical flow based method took least processing time and successfully detected boundary of moving objects which also implies that it can be implemented for real-time moving object detection.

  19. Transforming clinical imaging and 3D data for virtual reality learning objects: HTML5 and mobile devices implementation.

    PubMed

    Trelease, Robert B; Nieder, Gary L

    2013-01-01

    Web deployable anatomical simulations or "virtual reality learning objects" can easily be produced with QuickTime VR software, but their use for online and mobile learning is being limited by the declining support for web browser plug-ins for personal computers and unavailability on popular mobile devices like Apple iPad and Android tablets. This article describes complementary methods for creating comparable, multiplatform VR learning objects in the new HTML5 standard format, circumventing platform-specific limitations imposed by the QuickTime VR multimedia file format. Multiple types or "dimensions" of anatomical information can be embedded in such learning objects, supporting different kinds of online learning applications, including interactive atlases, examination questions, and complex, multi-structure presentations. Such HTML5 VR learning objects are usable on new mobile devices that do not support QuickTime VR, as well as on personal computers. Furthermore, HTML5 VR learning objects can be embedded in "ebook" document files, supporting the development of new types of electronic textbooks on mobile devices that are increasingly popular and self-adopted for mobile learning.

  20. Transforming clinical imaging and 3D data for virtual reality learning objects: HTML5 and mobile devices implementation.

    PubMed

    Trelease, Robert B; Nieder, Gary L

    2013-01-01

    Web deployable anatomical simulations or "virtual reality learning objects" can easily be produced with QuickTime VR software, but their use for online and mobile learning is being limited by the declining support for web browser plug-ins for personal computers and unavailability on popular mobile devices like Apple iPad and Android tablets. This article describes complementary methods for creating comparable, multiplatform VR learning objects in the new HTML5 standard format, circumventing platform-specific limitations imposed by the QuickTime VR multimedia file format. Multiple types or "dimensions" of anatomical information can be embedded in such learning objects, supporting different kinds of online learning applications, including interactive atlases, examination questions, and complex, multi-structure presentations. Such HTML5 VR learning objects are usable on new mobile devices that do not support QuickTime VR, as well as on personal computers. Furthermore, HTML5 VR learning objects can be embedded in "ebook" document files, supporting the development of new types of electronic textbooks on mobile devices that are increasingly popular and self-adopted for mobile learning. PMID:23212750

  1. Enhanced detection of 3D individual trees in forested areas using airborne full-waveform LiDAR data by combining normalized cuts with spatial density clustering

    NASA Astrophysics Data System (ADS)

    Yao, W.; Krzystek, P.; Heurich, M.

    2013-10-01

    A detailed understanding of the spatial distribution of forest understory is important but difficult. LiDAR remote sensing has been developing as a promising additional instrument to the conventional field work towards automated forest inventory. Unfortunately, understory (up to 50% of the top-tree height) in mixed and multilayered forests is often ignored due to a difficult observation scenario and limitation of the tree detection algorithm. Currently, the full-waveform (FWF) LiDAR with high penetration ability against overstory crowns can give us new hope to resolve the forest understory. Former approach based on 3D segmentation confirmed that the tree detection rates in both middle and lower forest layers are still low. Therefore, detecting sub-dominant and suppressed trees cannot be regarded as fully solved. In this work, we aim to improve the performance of the FWF laser scanner for the mapping of forest understory. The paper is to develop an enhanced methodology for detecting 3D individual trees by partitioning point clouds of airborne LiDAR. After extracting 3D coordinates of the laser beam echoes, the pulse intensity and width by waveform decomposition, the newly developed approach resolves 3D single trees are by an integrated approach, which delineates tree crowns by applying normalized cuts segmentation to the graph structure of local dense modes in point clouds constructed by mean shift clustering. In the context of our strategy, the mean shift clusters approximate primitives of (sub) single trees in LiDAR data and allow to define more significant features to reflect geometric and reflectional characteristics towards the single tree level. The developed methodology can be regarded as an object-based point cloud analysis approach for tree detection and is applied to datasets captured with the Riegl LMS-Q560 laser scanner at a point density of 25 points/m2 in the Bavarian Forest National Park, Germany, respectively under leaf-on and leaf-off conditions

  2. 3D Inversion of a Self-Potential Dataset for Contaminant Detection and Mapping

    NASA Astrophysics Data System (ADS)

    Minsley, B. J.; Sogade, J.; Briggs, V.; Lambert, M.; Reppert, P.; Coles, D.; Morgan, F.; Rossabi, J.; Riha, B.; Shi, W.

    2003-12-01

    Due to the complicated nature of subsurface contaminant migration, it is difficult to determine the spatial extent and severity of contamination, which can provide essential information for efficient remediation efforts. Self-potential (SP) geophysics is employed to provide a minimally invasive, fast, and inexpensive method for remote in-situ detection and three-dimensional mapping of subsurface DNAPL (Dense Non-Aqueous Phase Liquid) in conjunction with inverse methods. The self-potential method is commonly used to detect a variety of phenomena that are typically related to thermoelectric, electrochemical, or electrokinetic coupling processes. Surface self-potential surveys have been documented to show anomalies over areas known to be contaminated, but interpretation of these datasets is often mostly qualitative, and can be plagued with problems of non-uniqueness. In this study, oxidation-reduction (redox) reactions, one of the mechanisms associated with the attenuation of chemicals released into the environment, provide an electrochemical source for the SP signal. Electrochemical potentials associated with subsurface zones of redox activity are analogous to localized 'batteries' buried within native earth materials, and produce an electric field that is remotely detected using electrodes placed at the surface and in nearby boreholes. Three-dimensional inversion of the self-potential data incorporating resistivity information is the necessary step in characterizing the source parameters, which are directly related to the redox activity, and therefore to the contaminant itself. Surface and borehole SP data are collected in order to help constrain the solution in depth, and resistivity information is taken from an induced polarization survey performed over the same area during this field excursion. Inversion results are correlated with contaminant concentration data sampled from a series of ground-truth boreholes within the region of interest.

  3. Transforming Clinical Imaging and 3D Data for Virtual Reality Learning Objects: HTML5 and Mobile Devices Implementation

    ERIC Educational Resources Information Center

    Trelease, Robert B.; Nieder, Gary L.

    2013-01-01

    Web deployable anatomical simulations or "virtual reality learning objects" can easily be produced with QuickTime VR software, but their use for online and mobile learning is being limited by the declining support for web browser plug-ins for personal computers and unavailability on popular mobile devices like Apple iPad and Android…

  4. 3D-Modeling of deformed halite hopper crystals: Object based image analysis and support vector machine, a first evaluation

    NASA Astrophysics Data System (ADS)

    Leitner, Christoph; Hofmann, Peter; Marschallinger, Robert

    2014-05-01

    Halite hopper crystals are thought to develop by displacive growth in unconsolidated mud (Gornitz & Schreiber, 1984). The Alpine Haselgebirge, but also e.g. the salt deposits of the Rhine graben (mined at the beginning of the 20th century), comprise hopper crystals with shapes of cuboids, parallelepipeds and rhombohedrons (Görgey, 1912). Obviously, they deformed under oriented stress, which had been tried to reconstruct with respect to the sedimentary layering (Leitner et al., 2013). In the present work, deformed halite hopper crystals embedded in mudrock were automated reconstructed. Object based image analysis (OBIA) has been used successfully in remote sensing for 2D images before. The present study represents the first time that the method was used for reconstruction of three dimensional geological objects. First, manually a reference (gold standard) was created by redrawing contours of the halite crystals on each HRXCT scanning slice. Then, for OBIA, the computer program eCognition was used. For the automated reconstruction a rule set was developed. Thereby, the strength of OBIA was to recognize all objects similar to halite hopper crystals and in particular to eliminate cracks. In a second step, all the objects unsuitable for a structural deformation analysis were dismissed using a support vector machine (SVM) (clusters, polyhalite-coated crystals and spherical halites) The SVM simultaneously drastically reduced the number of halites. From 184 OBIA-objects 67 well shaped remained, which comes close to the number of pre-selected 52 objects. To assess the accuracy of the automated reconstruction, the result before and after SVM was compared to the reference, i.e. the gold standard. State-of the art per-scene statistics were extended to a per-object statistics. Görgey R (1912) Zur Kenntnis der Kalisalzlager von Wittelsheim im Ober-Elsaß. Tschermaks Mineral Petrogr Mitt 31:339-468 Gornitz VM, Schreiber BC (1981) Displacive halite hoppers from the dead sea

  5. Binary partition trees for object detection.

    PubMed

    Vilaplana, Veronica; Marques, Ferran; Salembier, Philippe

    2008-11-01

    This paper discusses the use of Binary Partition Trees (BPTs) for object detection. BPTs are hierarchical region-based representations of images. They define a reduced set of regions that covers the image support and that spans various levels of resolution. They are attractive for object detection as they tremendously reduce the search space. In this paper, several issues related to the use of BPT for object detection are studied. Concerning the tree construction, we analyze the compromise between computational complexity reduction and accuracy. This will lead us to define two parts in the BPT: one providing accuracy and one representing the search space for the object detection task. Then we analyze and objectively compare various similarity measures for the tree construction. We conclude that different similarity criteria should be used for the part providing accuracy in the BPT and for the part defining the search space and specific criteria are proposed for each case. Then we discuss the object detection strategy based on BPT. The notion of node extension is proposed and discussed. Finally, several object detection examples illustrating the generality of the approach and its efficiency are reported.

  6. Estimating the detectability of faults in 3D-seismic data - A valuable input to Induced Seismic Hazard Assessment (ISHA)

    NASA Astrophysics Data System (ADS)

    Goertz, A.; Kraft, T.; Wiemer, S.; Spada, M.

    2012-12-01

    In the past several years, some geotechnical operations that inject fluid into the deep subsurface, such as oil and gas development, waste disposal, and geothermal energy development, have been found or suspected to cause small to moderate sized earthquakes. In several cases the largest events occurred on previously unmapped faults, within or in close vicinity to the operated reservoirs. The obvious conclusion drawn from this finding, also expressed in most recently published best practice guidelines and recommendations, is to avoid injecting into faults. Yet, how certain can we be that all faults relevant to induced seismic hazard have been identified, even around well studied sites? Here we present a probabilistic approach to assess the capability of detecting faults by means of 3D seismic imaging. First, we populate a model reservoir with seed faults of random orientation and slip direction. Drawing random samples from a Gutenberg-Richter distribution, each seed fault is assigned a magnitude and corresponding size using standard scaling relations based on a circular rupture model. We then compute the minimum resolution of a 3D seismic survey for given acquisition parameters and frequency bandwidth. Assuming a random distribution of medium properties and distribution of image frequencies, we obtain a probability that a fault of a given size is detected, or respectively overlooked, by the 3D seismic. Weighting the initial Gutenberg-Richter fault size distribution with the probability of imaging a fault, we obtain a modified fault size distribution in the imaged volume from which we can constrain the maximum magnitude to be considered in the seismic hazard assessment of the operation. We can further quantify the value of information associated with the seismic image by comparing the expected insured value loss between the image-weighted and the unweighted hazard estimates.

  7. 3D cloud detection and tracking system for solar forecast using multiple sky imagers

    SciTech Connect

    Peng, Zhenzhou; Yu, Dantong; Huang, Dong; Heiser, John; Yoo, Shinjae; Kalb, Paul

    2015-06-23

    We propose a system for forecasting short-term solar irradiance based on multiple total sky imagers (TSIs). The system utilizes a novel method of identifying and tracking clouds in three-dimensional space and an innovative pipeline for forecasting surface solar irradiance based on the image features of clouds. First, we develop a supervised classifier to detect clouds at the pixel level and output cloud mask. In the next step, we design intelligent algorithms to estimate the block-wise base height and motion of each cloud layer based on images from multiple TSIs. Thus, this information is then applied to stitch images together into larger views, which are then used for solar forecasting. We examine the system’s ability to track clouds under various cloud conditions and investigate different irradiance forecast models at various sites. We confirm that this system can 1) robustly detect clouds and track layers, and 2) extract the significant global and local features for obtaining stable irradiance forecasts with short forecast horizons from the obtained images. Finally, we vet our forecasting system at the 32-megawatt Long Island Solar Farm (LISF). Compared with the persistent model, our system achieves at least a 26% improvement for all irradiance forecasts between one and fifteen minutes.

  8. 3D cloud detection and tracking system for solar forecast using multiple sky imagers

    DOE PAGES

    Peng, Zhenzhou; Yu, Dantong; Huang, Dong; Heiser, John; Yoo, Shinjae; Kalb, Paul

    2015-06-23

    We propose a system for forecasting short-term solar irradiance based on multiple total sky imagers (TSIs). The system utilizes a novel method of identifying and tracking clouds in three-dimensional space and an innovative pipeline for forecasting surface solar irradiance based on the image features of clouds. First, we develop a supervised classifier to detect clouds at the pixel level and output cloud mask. In the next step, we design intelligent algorithms to estimate the block-wise base height and motion of each cloud layer based on images from multiple TSIs. Thus, this information is then applied to stitch images together intomore » larger views, which are then used for solar forecasting. We examine the system’s ability to track clouds under various cloud conditions and investigate different irradiance forecast models at various sites. We confirm that this system can 1) robustly detect clouds and track layers, and 2) extract the significant global and local features for obtaining stable irradiance forecasts with short forecast horizons from the obtained images. Finally, we vet our forecasting system at the 32-megawatt Long Island Solar Farm (LISF). Compared with the persistent model, our system achieves at least a 26% improvement for all irradiance forecasts between one and fifteen minutes.« less

  9. Detecting small anatomical change with 3D serial MR subtraction images

    NASA Astrophysics Data System (ADS)

    Holden, Mark; Denton, Erica R. E.; Jarosz, J. M.; Cox, T. C.; Studholme, Colin; Hawkes, David J.; Hill, Derek L.

    1999-05-01

    Spoiled gradient echo volume MR scans were obtained from 5 growth hormone (GH) patients and 6 normal controls. The patients were scanned before treatment and after 3 and 6 months of GH therapy. The controls were scanned at similar intervals. A calibration phantom was scanned on the same day as each subject. The phantom images were registered with a 9 degree of freedom algorithm to measure scaling errors due to changes in scanner calibration. The second and third images were each registered with a 6 degree of freedom algorithm to the first (baseline) image by maximizing normalized mutual information, and transformed, with and without scaling error correction, using sinc interpolation. Each registered and transformed image had the baseline image subtracted to generate a difference image. Two neuro-radiologists were trained to detect structural change with difference images containing synthetic misregistration and scale changes. They carried out a blinded assessment of anatomical change for the unregistered; aligned and subtracted; and scale corrected, aligned and subtracted images. The results show a significant improvement in the detection of structural change and inter-observer agreement when aligned and subtracted images were used instead of unregistered ones. The structural change corresponded to an increase in brain: CSF ratio.

  10. Photon-counting lidar for aerosol detection and 3D imaging

    NASA Astrophysics Data System (ADS)

    Marino, Richard M.; Richardson, Jonathan; Garnier, Robert; Ireland, David; Bickmeier, Laura; Siracusa, Christina; Quinn, Patrick

    2009-05-01

    Laser-based remote sensing is undergoing a remarkable advance due to novel technologies developed at MIT Lincoln Laboratory. We have conducted recent experiments that have demonstrated the utility of detecting and imaging low-density aerosol clouds. The Mobile Active Imaging LIDAR (MAIL) system uses a Lincoln Laboratory-developed microchip laser to transmit short pulses at 14-16 kHz Pulse Repetition Frequency (PRF), and a Lincoln Laboratory-developed 32x32 Geiger-mode Avalanche-Photodiode Detector (GmAPD) array for singlephoton counting and ranging. The microchip laser is a frequency-doubled passively Q-Switched Nd:YAG laser providing an average transmitted power of less than 64 milli-Watts. When the avalanche photo-diodes are operated in the Geiger-mode, they are reverse-biased above the breakdown voltage for a time that corresponds to the effective range-gate or range-window of interest. The time-of-flight, and therefore range, is determined from the measured laser transmit time and the digital time value from each pixel. The optical intensity of the received pulse is not measured because the GmAPD is saturated by the electron avalanche. Instead, the reflectivity of the scene, or relative density of aerosols in this case, is determined from the temporally and/or spatially analyzed detection statistics.

  11. New method for detection of complex 3D fracture motion - Verification of an optical motion analysis system for biomechanical studies

    PubMed Central

    2012-01-01

    Background Fracture-healing depends on interfragmentary motion. For improved osteosynthesis and fracture-healing, the micromotion between fracture fragments is undergoing intensive research. The detection of 3D micromotions at the fracture gap still presents a challenge for conventional tactile measurement systems. Optical measurement systems may be easier to use than conventional systems, but, as yet, cannot guarantee accuracy. The purpose of this study was to validate the optical measurement system PONTOS 5M for use in biomechanical research, including measurement of micromotion. Methods A standardized transverse fracture model was created to detect interfragmentary motions under axial loadings of up to 200 N. Measurements were performed using the optical measurement system and compared with a conventional high-accuracy tactile system consisting of 3 standard digital dial indicators (1 μm resolution; 5 μm error limit). Results We found that the deviation in the mean average motion detection between the systems was at most 5.3 μm, indicating that detection of micromotion was possible with the optical measurement system. Furthermore, we could show two considerable advantages while using the optical measurement system. Only with the optical system interfragmentary motion could be analyzed directly at the fracture gap. Furthermore, the calibration of the optical system could be performed faster, safer and easier than that of the tactile system. Conclusion The PONTOS 5 M optical measurement system appears to be a favorable alternative to previously used tactile measurement systems for biomechanical applications. Easy handling, combined with a high accuracy for 3D detection of micromotions (≤ 5 μm), suggests the likelihood of high user acceptance. This study was performed in the context of the deployment of a new implant (dynamic locking screw; Synthes, Oberdorf, Switzerland). PMID:22405047

  12. Slow speed object detection for haul trucks

    SciTech Connect

    2009-09-15

    Caterpillar integrates radar technology with its current camera based system. Caterpillar has developed the Integrated Object Detection System, a slow speed object detection system for mining haul trucks. Object detection is a system that aids the truck operator's awareness of their surroundings. The system consists of a color touch screen display along with medium- and short-range radar as well as cameras, harnesses and mounting hardware. It is integrated into the truck's Work Area Vision System (WAVS). After field testing in 2007, system commercialization began in 2008. Prototype systems are in operation in Australia, Utah and Arizona and the Integrated Object Detection System will be available in the fourth quarter of 2009 and on production trucks 785C, 789C, 793D and 797B. The article is adapted from a presentation by Mark Richards of Caterpillar to the Haulage & Loading 2009 conference, May, held in Phoenix, AZ. 1 fig., 5 photos.

  13. Investigation on viewing direction dependent detectability in a reconstructed 3D volume for a cone beam CT system

    NASA Astrophysics Data System (ADS)

    Park, Junhan; Lee, Changwoo; Baek, Jongduk

    2015-03-01

    In medical imaging systems, several factors (e.g., reconstruction algorithm, noise structures, target size, contrast, etc) affect the detection performance and need to be considered for object detection. In a cone beam CT system, FDK reconstruction produces different noise structures in axial and coronal slices, and thus we analyzed directional dependent detectability of objects using detection SNR of Channelized Hotelling observer. To calculate the detection SNR, difference-of-Gaussian channel model with 10 channels was implemented, and 20 sphere objects with different radius (i.e., 0.25 (mm) to 5 (mm) equally spaced by 0.25 (mm)), reconstructed by FDK algorithm, were used as object templates. Covariance matrix in axial and coronal direction was estimated from 3000 reconstructed noise volumes, and then the SNR ratio between axial and coronal direction was calculated. Corresponding 2D noise power spectrum was also calculated. The results show that as the object size increases, the SNR ratio decreases, especially lower than 1 when the object size is larger than 2.5 mm radius. The reason is because the axial (coronal) noise power is higher in high (low) frequency band, and therefore the detectability of a small (large) object is higher in coronal (axial) images. Our results indicate that it is more beneficial to use coronal slices in order to improve the detectability of a small object in a cone beam CT system.

  14. Detection of patient's bed statuses in 3D using a Microsoft Kinect.

    PubMed

    Li, Yun; Berkowitz, Lyle; Noskin, Gary; Mehrotra, Sanjay

    2014-01-01

    Patients spend the vast majority of their hospital stay in an unmonitored bed where various mobility factors can impact patient safety and quality. Specifically, bed positioning and a patient's related mobility in that bed can have a profound impact on risks such as pneumonias, blood clots, bed ulcers and falls. This issue has been exacerbated as the nurse-per-bed (NPB) ratio has decreased in recent years. To help assess these risks, it is critical to monitor a hospital bed's positional status (BPS). Two bed positional statuses, bed height (BH) and bed chair angle (BCA), are of critical interests for bed monitoring. In this paper, we develop a bed positional status detection system using a single Microsoft Kinect. Experimental results show that we are able to achieve 94.5% and 93.0% overall accuracy of the estimated BCA and BH in a simulated patient's room environment.

  15. D Geological Outcrop Characterization: Automatic Detection of 3d Planes (azimuth and Dip) Using LiDAR Point Clouds

    NASA Astrophysics Data System (ADS)

    Anders, K.; Hämmerle, M.; Miernik, G.; Drews, T.; Escalona, A.; Townsend, C.; Höfle, B.

    2016-06-01

    Terrestrial laser scanning constitutes a powerful method in spatial information data acquisition and allows for geological outcrops to be captured with high resolution and accuracy. A crucial aspect for numerous geologic applications is the extraction of rock surface orientations from the data. This paper focuses on the detection of planes in rock surface data by applying a segmentation algorithm directly to a 3D point cloud. Its performance is assessed considering (1) reduced spatial resolution of data and (2) smoothing in the course of data pre-processing. The methodology is tested on simulations of progressively reduced spatial resolution defined by varying point cloud density. Smoothing of the point cloud data is implemented by modifying the neighborhood criteria during normals estima-tion. The considerable alteration of resulting planes emphasizes the influence of smoothing on the plane detection prior to the actual segmentation. Therefore, the parameter needs to be set in accordance with individual purposes and respective scales of studies. Fur-thermore, it is concluded that the quality of segmentation results does not decline even when the data volume is significantly reduced down to 10%. The azimuth and dip values of individual segments are determined for planes fit to the points belonging to one segment. Based on these results, azimuth and dip as well as strike character of the surface planes in the outcrop are assessed. Thereby, this paper contributes to a fully automatic and straightforward workflow for a comprehensive geometric description of outcrops in 3D.

  16. Salient object detection approach in UAV video

    NASA Astrophysics Data System (ADS)

    Zhang, Yueqiang; Su, Ang; Zhu, Xianwei; Zhang, Xiaohu; Shang, Yang

    2013-10-01

    The automatic detection of visually salient information from abundant video imagery is crucial, as it plays an important role in surveillance and reconnaissance tasks for Unmanned Aerial Vehicle (UAV). A real-time approach for the detection of salient objects on road, e.g. stationary and moving vehicle or people, is proposed, which is based on region segmentation and saliency detection within related domains. Generally, the traditional method specifically depends upon additional scene information and auxiliary thermal or IR sensing for secondary confirmation. However, this proposed approach can detect the interesting objects directly from video imagery captured by optical camera fixed on the small level UAV platform. To validate this proposed salient object detection approach, the 25 Hz video data from our low speed small UAV are tested. The results have demonstrated the proposed approach performs excellently in isolated rural environments.

  17. Change detection for objects on surfaces slanted in depth.

    PubMed

    Ozkan, Kerem; Braunstein, Myron L

    2010-09-15

    Change detection for objects associated with a surface extended in depth might be more difficult than for a frontal surface if it is easier to shift attention within a frontal surface. On the other hand, previous research has shown that ground surfaces have a special role in organizing the 3-D layout of objects shown against scene backgrounds. In the current study, we examined whether a frontal background or a ground surface background would result in superior change detection performance using a change detection flicker paradigm. In the first experiment, we considered whether background slant affects change detection performance. In Experiment 2, we examined the effect of height in the image on change detection performance. In Experiment 3, we examined change detection performance on slanted ceiling surfaces. The results of these experiments indicate that change detection is more efficient on near-ground planes than on surfaces at intermediate slants or ceiling surfaces. This suggests that any superiority of frontal plane backgrounds in a change detection task may be equivalent to the superiority of a near-ground plane in organizing a scene, with the lowest level of performance occurring for surfaces that are not frontal but further from a ground surface orientation.

  18. 3D seismic detection of shallow faults and fluid migration pathways offshore Southern Costa Rica: Application of neural-network meta-attributes

    NASA Astrophysics Data System (ADS)

    Kluesner, J. W.; Silver, E. A.; Nale, S. M.; Bangs, N. L.; McIntosh, K. D.

    2013-12-01

    We employ a seismic meta-attribute workflow to detect and analyze probable faults and fluid-pathways in 3D within the sedimentary section offshore Southern Costa Rica. During the CRISP seismic survey in 2011 we collected an 11 x 55 km grid of 3D seismic reflection data and high-resolvability EM122 multibeam data, with coverage extending from the incoming plate to the outer-shelf. We mapped numerous seafloor seep indicators, with distributions ranging from the lower-slope to ~15 km landward of the shelf break [Kluesner et al., 2013, G3, doi:10.1002/ggge.20058; Silver et al., this meeting]. We used the OpendTect software package to calculate meta-attribute volumes from the 3D seismic data in order to detect and visualize seismic discontinuities in 3D. This methodology consists of dip-steered filtering to pre-condition the data, followed by combining a set of advanced dip-steered seismic attributes into a single object probability attribute using a user-trained neural-network pattern-recognition algorithm. The parameters of the advanced seismic attributes are set for optimal detection of the desired geologic discontinuity (e.g. faults or fluid-pathways). The product is a measure of probability for the desired target that ranges between 0 and 1, with 1 representing the highest probability. Within the sedimentary section of the CRISP survey the results indicate focused fluid-migration pathways along dense networks of intersecting normal faults with approximately N-S and E-W trends. This pattern extends from the middle slope to the outer-shelf region. Dense clusters of fluid-migration pathways are located above basement highs and deeply rooted reverse faults [see Bangs et al., this meeting], including a dense zone of fluid-pathways imaged below IODP Site U1413. In addition, fault intersections frequently show an increased signal of fluid-migration and these zones may act as major conduits for fluid-flow through the sedimentary cover. Imaged fluid pathways root into high

  19. 3D Multi-Object Segmentation of Cardiac MSCT Imaging by using a Multi-Agent Approach

    PubMed Central

    Fleureau, Julien; Garreau, Mireille; Boulmier, Dominique; Hernandez, Alfredo

    2007-01-01

    We propose a new technique for general purpose, semi-interactive and multi-object segmentation in N-dimensional images, applied to the extraction of cardiac structures in MultiSlice Computed Tomography (MSCT) imaging. The proposed approach makes use of a multi-agent scheme combined with a supervised classification methodology allowing the introduction of a priori information and presenting fast computing times. The multi-agent system is organised around a communicating agent which manages a population of situated agents which segment the image through cooperative and competitive interactions. The proposed technique has been tested on several patient data sets. Some typical results are finally presented and discussed. PMID:18003382

  20. Evaluation of 3D-CPA, HR-HPV, and TCT joint detection on cervical disease screening

    PubMed Central

    Liang, Hui; Fu, Min; Zhou, Jian; Song, Lei

    2016-01-01

    The application value of three-dimensional color power angiography (3D-CPA), high-risk human papillomavirus (HR-HPV), ThinPrep cytology test (TCT) joint detection on cervical disease screening was investigated. In total, 1,900 patients that were examined in Gynecological and Cervix Clinic of Maternal and Child Care Service Center of Xuzhou from June 2012 to March 2015 were enrolled in the present study. After admission, the patients underwent TCT, HR-HPV and 3D-CPA examinations, and vascular morphology and typing, vascularization index (VI) were recorded. Colposcopic biopsy was performed in patients with a positive outcome of any of the three indices. Pathological diagnosis was taken as the golden standard to assess the sensitivity, specificity, diagnostic rate, and Youden index of the three methods being used independently or jointly. Of the 1,900 patients, 276 cases (14.53%) were HR-HPV-positive, 214 cases (11.26%) were VI-positive and 164 cases (8.63%) were TCT-positive. A total of 418 cases were confirmed with a positive outcome of any of the three indices and a cervical biopsy was obtained. Of the 418 cases, 162 cases (38.75%) were diagnosed with chronic cervicitis, 146 cases with low-level cervical intraepithelial neoplasia (CIN) (34.93%), 104 cases (24.88%) with high level CIN, 6 cases (1.44%) with cervical cancer. Histology more than low level CIN was defined as positive: i) screening results when the three methods were used independently: HPV was confirmed with the highest sensitivity (90.63%), VI with the highest specificity (83.95%), and HPV with the highest diagnostic accuracy (83.73%); ii) screening results under HPV+TCT and HPV+TCT+VI: HPV+TCT+VI was confirmed with the highest sensitivity and specificity: sensitivity (94.53%), specificity (81.48%), diagnosis coincidence rate (89.47%) and the highest Youden index of 0.760; and iii) vascular morphology and grading were significantly different in the early stage cervical carcinoma, high level CIM, and

  1. Applications of neural networks to landmark detection in 3-D surface data

    NASA Astrophysics Data System (ADS)

    Arndt, Craig M.

    1992-09-01

    The problem of identifying key landmarks in 3-dimensional surface data is of considerable interest in solving a number of difficult real-world tasks, including object recognition and image processing. The specific problem that we address in this research is to identify the specific landmarks (anatomical) in human surface data. This is a complex task, currently performed visually by an expert human operator. In order to replace these human operators and increase reliability of the data acquisition, we need to develop a computer algorithm which will utilize the interrelations between the 3-dimensional data to identify the landmarks of interest. The current presentation describes a method for designing, implementing, training, and testing a custom architecture neural network which will perform the landmark identification task. We discuss the performance of the net in relationship to human performance on the same task and how this net has been integrated with other AI and traditional programming methods to produce a powerful analysis tool for computer anthropometry.

  2. Detection of latent fingerprints using high-resolution 3D confocal microscopy in non-planar acquisition scenarios

    NASA Astrophysics Data System (ADS)

    Kirst, Stefan; Vielhauer, Claus

    2015-03-01

    In digitized forensics the support of investigators in any manner is one of the main goals. Using conservative lifting methods, the detection of traces is done manually. For non-destructive contactless methods, the necessity for detecting traces is obvious for further biometric analysis. High resolutional 3D confocal laser scanning microscopy (CLSM) grants the possibility for a detection by segmentation approach with improved detection results. Optimal scan results with CLSM are achieved on surfaces orthogonal to the sensor, which is not always possible due to environmental circumstances or the surface's shape. This introduces additional noise, outliers and a lack of contrast, making a detection of traces even harder. Prior work showed the possibility of determining angle-independent classification models for the detection of latent fingerprints (LFP). Enhancing this approach, we introduce a larger feature space containing a variety of statistical-, roughness-, color-, edge-directivity-, histogram-, Gabor-, gradient- and Tamura features based on raw data and gray-level co-occurrence matrices (GLCM) using high resolutional data. Our test set consists of eight different surfaces for the detection of LFP in four different acquisition angles with a total of 1920 single scans. For each surface and angles in steps of 10, we capture samples from five donors to introduce variance by a variety of sweat compositions and application influences such as pressure or differences in ridge thickness. By analyzing the present test set with our approach, we intend to determine angle- and substrate-dependent classification models to determine optimal surface specific acquisition setups and also classification models for a general detection purpose for both, angles and substrates. The results on overall models with classification rates up to 75.15% (kappa 0.50) already show a positive tendency regarding the usability of the proposed methods for LFP detection on varying surfaces in non

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

    PubMed

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

    2015-01-01

    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.

  4. A Model-Based 3D Template Matching Technique for Pose Acquisition of an Uncooperative Space Object

    PubMed Central

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

    2015-01-01

    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. PMID:25785309

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

    PubMed

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

    2015-01-01

    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. PMID:25785309

  6. a Uav Based 3-D Positioning Framework for Detecting Locations of Buried Persons in Collapsed Disaster Area

    NASA Astrophysics Data System (ADS)

    Moon, H.; Kim, C.; Lee, W.

    2016-06-01

    Regarding spatial location positioning, indoor location positioning theories based on wireless communication techniques such as Wi-Fi, beacon, UWB and Bluetooth has widely been developing across the world. These techniques are mainly focusing on spatial location detection of customers using fixed wireless APs and unique Tags in the indoor environment. Besides, since existing detection equipment and techniques using ultrasound or sound etc. to detect buried persons and identify survival status for them cause 2nd damages on the collapsed debris for rescuers. In addition, it might take time to check the buried persons. However, the collapsed disaster sites should consider both outdoor and indoor environments because empty spaces under collapsed debris exists. In order to detect buried persons from the empty spaces, we should collect wireless signals with Wi-Fi from their mobile phone. Basically, the Wi-Fi signal measure 2-D location. However, since the buried persons have Z value with burial depth, we also should collect barometer sensor data from their mobile phones in order to measure Z values according to weather conditions. Specially, for quick accessibility to the disaster area, a drone (UAV; Unmanned Arial Vehicle) system, which is equipped with a wireless detection module, was introduced. Using these framework, this study aims to provide the rescuers with effective rescue information by calculating 3-D location for buried persons based on the wireless and barometer sensor fusion.

  7. Automated detection of retinal cell nuclei in 3D micro-CT images of zebrafish using support vector machine classification

    NASA Astrophysics Data System (ADS)

    Ding, Yifu; Tavolara, Thomas; Cheng, Keith

    2016-03-01

    Our group is developing a method to examine biological specimens in cellular detail using synchrotron microCT. The method can acquire 3D images of tissue at micrometer-scale resolutions, allowing for individual cell types to be visualized in the context of the entire specimen. For model organism research, this tool will enable the rapid characterization of tissue architecture and cellular morphology from every organ system. This characterization is critical for proposed and ongoing "phenome" projects that aim to phenotype whole-organism mutants and diseased tissues from different organisms including humans. With the envisioned collection of hundreds to thousands of images for a phenome project, it is important to develop quantitative image analysis tools for the automated scoring of organism phenotypes across organ systems. Here we present a first step towards that goal, demonstrating the use of support vector machines (SVM) in detecting retinal cell nuclei in 3D images of wild-type zebrafish. In addition, we apply the SVM classifier on a mutant zebrafish to examine whether SVMs can be used to capture phenotypic differences in these images. The longterm goal of this work is to allow cellular and tissue morphology to be characterized quantitatively for many organ systems, at the level of the whole-organism.

  8. A 3D Microfluidic Chip for Electrochemical Detection of Hydrolysed Nucleic Bases by a Modified Glassy Carbon Electrode

    PubMed Central

    Vlachova, Jana; Tmejova, Katerina; Kopel, Pavel; Korabik, Maria; Zitka, Jan; Hynek, David; Kynicky, Jindrich; Adam, Vojtech; Kizek, Rene

    2015-01-01

    Modification of carbon materials, especially graphene-based materials, has wide applications in electrochemical detection such as electrochemical lab-on-chip devices. A glassy carbon electrode (GCE) modified with chemically alternated graphene oxide was used as a working electrode (glassy carbon modified by graphene oxide with sulphur containing compounds and Nafion) for detection of nucleobases in hydrolysed samples (HCl pH = 2.9, 100 °C, 1 h, neutralization by NaOH). It was found out that modification, especially with trithiocyanuric acid, increased the sensitivity of detection in comparison with pure GCE. All processes were finally implemented in a microfluidic chip formed with a 3D printer by fused deposition modelling technology. As a material for chip fabrication, acrylonitrile butadiene styrene was chosen because of its mechanical and chemical stability. The chip contained the one chamber for the hydrolysis of the nucleic acid and another for the electrochemical detection by the modified GCE. This chamber was fabricated to allow for replacement of the GCE. PMID:25621613

  9. Robust and highly performant ring detection algorithm for 3d particle tracking using 2d microscope imaging

    PubMed Central

    Afik, Eldad

    2015-01-01

    Three-dimensional particle tracking is an essential tool in studying dynamics under the microscope, namely, fluid dynamics in microfluidic devices, bacteria taxis, cellular trafficking. The 3d position can be determined using 2d imaging alone by measuring the diffraction rings generated by an out-of-focus fluorescent particle, imaged on a single camera. Here I present a ring detection algorithm exhibiting a high detection rate, which is robust to the challenges arising from ring occlusion, inclusions and overlaps, and allows resolving particles even when near to each other. It is capable of real time analysis thanks to its high performance and low memory footprint. The proposed algorithm, an offspring of the circle Hough transform, addresses the need to efficiently trace the trajectories of many particles concurrently, when their number in not necessarily fixed, by solving a classification problem, and overcomes the challenges of finding local maxima in the complex parameter space which results from ring clusters and noise. Several algorithmic concepts introduced here can be advantageous in other cases, particularly when dealing with noisy and sparse data. The implementation is based on open-source and cross-platform software packages only, making it easy to distribute and modify. It is implemented in a microfluidic experiment allowing real-time multi-particle tracking at 70 Hz, achieving a detection rate which exceeds 94% and only 1% false-detection. PMID:26329642

  10. Saliency-Guided Detection of Unknown Objects in RGB-D Indoor Scenes

    PubMed Central

    Bao, Jiatong; Jia, Yunyi; Cheng, Yu; Xi, Ning

    2015-01-01

    This paper studies the problem of detecting unknown objects within indoor environments in an active and natural manner. The visual saliency scheme utilizing both color and depth cues is proposed to arouse the interests of the machine system for detecting unknown objects at salient positions in a 3D scene. The 3D points at the salient positions are selected as seed points for generating object hypotheses using the 3D shape. We perform multi-class labeling on a Markov random field (MRF) over the voxels of the 3D scene, combining cues from object hypotheses and 3D shape. The results from MRF are further refined by merging the labeled objects, which are spatially connected and have high correlation between color histograms. Quantitative and qualitative evaluations on two benchmark RGB-D datasets illustrate the advantages of the proposed method. The experiments of object detection and manipulation performed on a mobile manipulator validate its effectiveness and practicability in robotic applications. PMID:26343656

  11. Saliency-Guided Detection of Unknown Objects in RGB-D Indoor Scenes.

    PubMed

    Bao, Jiatong; Jia, Yunyi; Cheng, Yu; Xi, Ning

    2015-01-01

    This paper studies the problem of detecting unknown objects within indoor environments in an active and natural manner. The visual saliency scheme utilizing both color and depth cues is proposed to arouse the interests of the machine system for detecting unknown objects at salient positions in a 3D scene. The 3D points at the salient positions are selected as seed points for generating object hypotheses using the 3D shape. We perform multi-class labeling on a Markov random field (MRF) over the voxels of the 3D scene, combining cues from object hypotheses and 3D shape. The results from MRF are further refined by merging the labeled objects, which are spatially connected and have high correlation between color histograms. Quantitative and qualitative evaluations on two benchmark RGB-D datasets illustrate the advantages of the proposed method. The experiments of object detection and manipulation performed on a mobile manipulator validate its effectiveness and practicability in robotic applications. PMID:26343656

  12. Patellar segmentation from 3D magnetic resonance images using guided recursive ray-tracing for edge pattern detection

    NASA Astrophysics Data System (ADS)

    Cheng, Ruida; Jackson, Jennifer N.; McCreedy, Evan S.; Gandler, William; Eijkenboom, J. J. F. A.; van Middelkoop, M.; McAuliffe, Matthew J.; Sheehan, Frances T.

    2016-03-01

    The paper presents an automatic segmentation methodology for the patellar bone, based on 3D gradient recalled echo and gradient recalled echo with fat suppression magnetic resonance images. Constricted search space outlines are incorporated into recursive ray-tracing to segment the outer cortical bone. A statistical analysis based on the dependence of information in adjacent slices is used to limit the search in each image to between an outer and inner search region. A section based recursive ray-tracing mechanism is used to skip inner noise regions and detect the edge boundary. The proposed method achieves higher segmentation accuracy (0.23mm) than the current state-of-the-art methods with the average dice similarity coefficient of 96.0% (SD 1.3%) agreement between the auto-segmentation and ground truth surfaces.

  13. About Non-Line-Of-Sight satellite detection and exclusion in a 3D map-aided localization algorithm.

    PubMed

    Peyraud, Sébastien; Bétaille, David; Renault, Stéphane; Ortiz, Miguel; Mougel, Florian; Meizel, Dominique; Peyret, François

    2013-01-01

    Reliable GPS positioning in city environment is a key issue: actually, signals are prone to multipath, with poor satellite geometry in many streets. Using a 3D urban model to forecast satellite visibility in urban contexts in order to improve GPS localization is the main topic of the present article. A virtual image processing that detects and eliminates possible faulty measurements is the core of this method. This image is generated using the position estimated a priori by the navigation process itself, under road constraints. This position is then updated by measurements to line-of-sight satellites only. This closed-loop real-time processing has shown very first promising full-scale test results.

  14. A 3D clustering approach for point clouds to detect and quantify changes at a rock glacier front

    NASA Astrophysics Data System (ADS)

    Micheletti, Natan; Tonini, Marj; Lane, Stuart N.

    2016-04-01

    Terrestrial Laser Scanners (TLS) are extensively used in geomorphology to remotely-sense landforms and surfaces of any type and to derive digital elevation models (DEMs). Modern devices are able to collect many millions of points, so that working on the resulting dataset is often troublesome in terms of computational efforts. Indeed, it is not unusual that raw point clouds are filtered prior to DEM creation, so that only a subset of points is retained and the interpolation process becomes less of a burden. Whilst this procedure is in many cases necessary, it implicates a considerable loss of valuable information. First, and even without eliminating points, the common interpolation of points to a regular grid causes a loss of potentially useful detail. Second, it inevitably causes the transition from 3D information to only 2.5D data where each (x,y) pair must have a unique z-value. Vector-based DEMs (e.g. triangulated irregular networks) partially mitigate these issues, but still require a set of parameters to be set and a considerable burden in terms of calculation and storage. Because of the reasons above, being able to perform geomorphological research directly on point clouds would be profitable. Here, we propose an approach to identify erosion and deposition patterns on a very active rock glacier front in the Swiss Alps to monitor sediment dynamics. The general aim is to set up a semiautomatic method to isolate mass movements using 3D-feature identification directly from LiDAR data. An ultra-long range LiDAR RIEGL VZ-6000 scanner was employed to acquire point clouds during three consecutive summers. In order to isolate single clusters of erosion and deposition we applied the Density-Based Scan Algorithm with Noise (DBSCAN), previously successfully employed by Tonini and Abellan (2014) in a similar case for rockfall detection. DBSCAN requires two input parameters, strongly influencing the number, shape and size of the detected clusters: the minimum number of

  15. About Non-Line-Of-Sight Satellite Detection and Exclusion in a 3D Map-Aided Localization Algorithm

    PubMed Central

    Peyraud, Sébastien; Bétaille, David; Renault, Stéphane; Ortiz, Miguel; Mougel, Florian; Meizel, Dominique; Peyret, François

    2013-01-01

    Reliable GPS positioning in city environment is a key issue actually, signals are prone to multipath, with poor satellite geometry in many streets. Using a 3D urban model to forecast satellite visibility in urban contexts in order to improve GPS localization is the main topic of the present article. A virtual image processing that detects and eliminates possible faulty measurements is the core of this method. This image is generated using the position estimated a priori by the navigation process itself, under road constraints. This position is then updated by measurements to line-of-sight satellites only. This closed-loop real-time processing has shown very first promising full-scale test results. PMID:23344379

  16. Development of a Displacement- and Frequency-Noise-Free Interferometer in a 3D Configuration for Gravitational Wave Detection

    SciTech Connect

    Kokeyama, Keiko; Sato, Shuichi; Nishizawa, Atsushi; Kawamura, Seiji; Chen Yanbei; Sugamoto, Akio

    2009-10-23

    The displacement- and frequency-noise-free interferometer (DFI) is a multiple laser interferometer array for gravitational-wave detection free from both the displacement noise of optics and laser frequency noise. So far, partial experimental demonstrations of the DFI have been done in 2D table top experiments. In this Letter, we report the complete demonstration of a 3D DFI. The DFI consists of four Mach-Zehnder interferometers with four mirrors and two beam splitters The attained maximum suppression of the displacement noise of both mirrors and beam splitters was 40 dB at about 50 MHz. The nonvanishing DFI response to a gravitational wave was successfully confirmed using multiple electro-optic modulators and computing methods.

  17. A highly automated moving object detection package

    NASA Astrophysics Data System (ADS)

    Petit, J.-M.; Holman, M.; Scholl, H.; Kavelaars, J.; Gladman, B.

    2004-01-01

    With the deployment of large CCD mosaic cameras and their use in large-scale surveys to discover Solar system objects, there is a need for fast detection algorithms that can handle large data loads in a nearly automatic way. We present here an algorithm that we have developed. Our approach, by using two independent detection algorithms and combining the results, maintains high efficiency while producing low false-detection rates. These properties are crucial in order to reduce the operator time associated with searching these huge data sets. We have used this algorithm on two different mosaic data sets obtained using the CFH12K camera at the Canada-France-Hawaii Telescope (CFHT). Comparing the detection efficiency and false-detection rate of each individual algorithm with the combination of both, we show that our approach decreases the false detection rate by a factor of a few hundred to a thousand, while decreasing the `limiting magnitude' (where the detection rate drops to 50 per cent) by only 0.1-0.3 mag. The limiting magnitude is similar to that of a human operator blinking the images. Our full pipeline also characterizes the magnitude efficiency of the entire system by implanting artificial objects in the data set. The detection portion of the package is publicly available.

  18. Object detection in real-time

    NASA Astrophysics Data System (ADS)

    Solder, Ulrich; Graefe, Volker

    1991-03-01

    An algorithm working on monocular gray-scale image sequences for object detection combined with a road tracker is presented. This algorithm appropriate for the real-time demands of an autonomous car driving with speeds over 40 km/h may be used for triggering obstacle avoidance maneuvers such as coming to a safe stop automatically in front of an obstacle or following another car. Moving and static objects have been detected in real-world experiments on various types of roads even under unfavorable weather conditions. . Morgenthaler and

  19. Distributed object detection with linear SVMs.

    PubMed

    Pang, Yanwei; Zhang, Kun; Yuan, Yuan; Wang, Kongqiao

    2014-11-01

    In vision and learning, low computational complexity and high generalization are two important goals for video object detection. Low computational complexity here means not only fast speed but also less energy consumption. The sliding window object detection method with linear support vector machines (SVMs) is a general object detection framework. The computational cost is herein mainly paid in complex feature extraction and innerproduct-based classification. This paper first develops a distributed object detection framework (DOD) by making the best use of spatial-temporal correlation, where the process of feature extraction and classification is distributed in the current frame and several previous frames. In each framework, only subfeature vectors are extracted and the response of partial linear classifier (i.e., subdecision value) is computed. To reduce the dimension of traditional block-based histograms of oriented gradients (BHOG) feature vector, this paper proposes a cell-based HOG (CHOG) algorithm, where the features in one cell are not shared with overlapping blocks. Using CHOG as feature descriptor, we develop CHOG-DOD as an instance of DOD framework. Experimental results on detection of hand, face, and pedestrian in video show the superiority of the proposed method. PMID:25330474

  20. Data-Driven Detection of Prominent Objects.

    PubMed

    Rodriguez-Serrano, Jose A; Larlus, Diane; Dai, Zhenwen

    2016-10-01

    This article deals with the detection of prominent objects in images. As opposed to the standard approaches based on sliding windows, we study a fundamentally different solution by formulating the supervised prediction of a bounding box as an image retrieval task. Indeed, given a global image descriptor, we find the most similar images in an annotated dataset, and transfer the object bounding boxes. We refer to this approach as data-driven detection (DDD). Our key novelty is to design or learn image similarities that explicitly optimize some aspect of the transfer unlike previous work which uses generic representations and unsupervised similarities. In a first variant, we explicitly learn to transfer, by adapting a metric learning approach to work with image and bounding box pairs. Second, we use a representation of images as object probability maps computed from low-level patch classifiers. Experiments show that these two contributions yield in some cases comparable or better results than standard sliding window detectors - despite its conceptual simplicity and run-time efficiency. Our third contribution is an application of prominent object detection, where we improve fine-grained categorization by pre-cropping images with the proposed approach. Finally, we also extend the proposed approach to detect multiple parts of rigid objects. PMID:26700971

  1. Moving object detection for video surveillance.

    PubMed

    Kalirajan, K; Sudha, M

    2015-01-01

    The emergence of video surveillance is the most promising solution for people living independently in their home. Recently several contributions for video surveillance have been proposed. However, a robust video surveillance algorithm is still a challenging task because of illumination changes, rapid variations in target appearance, similar nontarget objects in background, and occlusions. In this paper, a novel approach of object detection for video surveillance is presented. The proposed algorithm consists of various steps including video compression, object detection, and object localization. In video compression, the input video frames are compressed with the help of two-dimensional discrete cosine transform (2D DCT) to achieve less storage requirements. In object detection, key feature points are detected by computing the statistical correlation and the matching feature points are classified into foreground and background based on the Bayesian rule. Finally, the foreground feature points are localized in successive video frames by embedding the maximum likelihood feature points over the input video frames. Various frame based surveillance metrics are employed to evaluate the proposed approach. Experimental results and comparative study clearly depict the effectiveness of the proposed approach. PMID:25861686

  2. 3-D visualisation of palaeoseismic trench stratigraphy and trench logging using terrestrial remote sensing and GPR - combining techniques towards an objective multiparametric interpretation

    NASA Astrophysics Data System (ADS)

    Schneiderwind, S.; Mason, J.; Wiatr, T.; Papanikolaou, I.; Reicherter, K.

    2015-09-01

    Two normal faults on the Island of Crete and mainland Greece were studied to create and test an innovative workflow to make palaeoseismic trench logging more objective, and visualise the sedimentary architecture within the trench wall in 3-D. This is achieved by combining classical palaeoseismic trenching techniques with multispectral approaches. A conventional trench log was firstly compared to results of iso cluster analysis of a true colour photomosaic representing the spectrum of visible light. Passive data collection disadvantages (e.g. illumination) were addressed by complementing the dataset with active near-infrared backscatter signal image from t-LiDAR measurements. The multispectral analysis shows that distinct layers can be identified and it compares well with the conventional trench log. According to this, a distinction of adjacent stratigraphic units was enabled by their particular multispectral composition signature. Based on the trench log, a 3-D-interpretation of GPR data collected on the vertical trench wall was then possible. This is highly beneficial for measuring representative layer thicknesses, displacements and geometries at depth within the trench wall. Thus, misinterpretation due to cutting effects is minimised. Sedimentary feature geometries related to earthquake magnitude can be used to improve the accuracy of seismic hazard assessments. Therefore, this manuscript combines multiparametric approaches and shows: (i) how a 3-D visualisation of palaeoseismic trench stratigraphy and logging can be accomplished by combining t-LiDAR and GRP techniques, and (ii) how a multispectral digital analysis can offer additional advantages and a higher objectivity in the interpretation of palaeoseismic and stratigraphic information. The multispectral datasets are stored allowing unbiased input for future (re-)investigations.

  3. Detection of human genome mutations associated with pregnancy complications using 3-D microarray based on macroporous polymer monoliths.

    PubMed

    Glotov, A S; Sinitsyna, E S; Danilova, M M; Vashukova, E S; Walter, J G; Stahl, F; Baranov, V S; Vlakh, E G; Tennikova, T B

    2016-01-15

    Analysis of variations in DNA structure using a low-density microarray technology for routine diagnostic in evidence-based medicine is still relevant. In this work the applicability of 3-D macroporous monolithic methacrylate-based platforms for detection of different pathogenic genomic substitutions was studied. The detection of nucleotide replacements in F5 (Leiden G/A, rs6025), MTHFR (C/T, rs1801133) and ITGB3 (T/C, rs5918), involved in coagulation, and COMT (C/G, rs4818), TPH2 (T/A, rs11178997), PON1 (T/A rs854560), AGTR2 (C/A, rs11091046) and SERPINE1 (5G/4G, rs1799889), associated with pregnancy complications, was performed. The effect of such parameters as amount and type of oligonucleotide probe, amount of PCR product on signal-to-noise ratio, as well as mismatch discrimination was analyzed. Sensitivity and specificity of mutation detections were coincided and equal to 98.6%. The analysis of SERPINE1 and MTHFR genotypes by both NGS and developed microarray was performed and compared. PMID:26592644

  4. 3D photothermal microscope for the detection of nano-sized absorbing defects responsible for laser-induced damage initiation

    NASA Astrophysics Data System (ADS)

    Bertussi, Bertrand; Natoli, Jean Yves; Commandre, Mireille

    2005-02-01

    The recent progresses in optical components manufacturing have permitted to increase strongly the laser-induced damage threshold. However, in high power laser applications, the slightest inhomogeneity of the material can lead to an irreversible breakdown. Considering the difficulty to eliminate the whole defects, it is important to have an accurate tool to exhibit the smallest absorbing centers assumed to be precursors of laser damage. We propose in this paper to describe a non destructive technique based on the photothermal effect induced by local absorbing inhomogeneities in order to detect nano-scale absorbing defects. The purpose will be illustrated by the detection of artificial isolated metallic inclusions of a few ten nanometers in the bulk of transparent substrates and thin-film coatings. The high spatial resolution of detection is obtained thank to a piezolectric 3D stage. Moreover, the photothermal setup coupled with a laser damage facility, permits to follow with high accuracy the evolution of these defects under laser irradiation and determine a pre-damage stage ten times lower than the surface damage.

  5. Detecting and Analyzing Corrosion Spots on the Hull of Large Marine Vessels Using Colored 3d LIDAR Point Clouds

    NASA Astrophysics Data System (ADS)

    Aijazi, A. K.; Malaterre, L.; Tazir, M. L.; Trassoudaine, L.; Checchin, P.

    2016-06-01

    This work presents a new method that automatically detects and analyzes surface defects such as corrosion spots of different shapes and sizes, on large ship hulls. In the proposed method several scans from different positions and viewing angles around the ship are registered together to form a complete 3D point cloud. The R, G, B values associated with each scan, obtained with the help of an integrated camera are converted into HSV space to separate out the illumination invariant color component from the intensity. Using this color component, different surface defects such as corrosion spots of different shapes and sizes are automatically detected, within a selected zone, using two different methods depending upon the level of corrosion/defects. The first method relies on a histogram based distribution whereas the second on adaptive thresholds. The detected corrosion spots are then analyzed and quantified to help better plan and estimate the cost of repair and maintenance. Results are evaluated on real data using different standard evaluation metrics to demonstrate the efficacy as well as the technical strength of the proposed method.

  6. Hip2Norm: an object-oriented cross-platform program for 3D analysis of hip joint morphology using 2D pelvic radiographs.

    PubMed

    Zheng, G; Tannast, M; Anderegg, C; Siebenrock, K A; Langlotz, F

    2007-07-01

    We developed an object-oriented cross-platform program to perform three-dimensional (3D) analysis of hip joint morphology using two-dimensional (2D) anteroposterior (AP) pelvic radiographs. Landmarks extracted from 2D AP pelvic radiographs and optionally an additional lateral pelvic X-ray were combined with a cone beam projection model to reconstruct 3D hip joints. Since individual pelvic orientation can vary considerably, a method for standardizing pelvic orientation was implemented to determine the absolute tilt/rotation. The evaluation of anatomically morphologic differences was achieved by reconstructing the projected acetabular rim and the measured hip parameters as if obtained in a standardized neutral orientation. The program had been successfully used to interactively objectify acetabular version in hips with femoro-acetabular impingement or developmental dysplasia. Hip(2)Norm is written in object-oriented programming language C++ using cross-platform software Qt (TrollTech, Oslo, Norway) for graphical user interface (GUI) and is transportable to any platform. PMID:17499878

  7. Hip2Norm: an object-oriented cross-platform program for 3D analysis of hip joint morphology using 2D pelvic radiographs.

    PubMed

    Zheng, G; Tannast, M; Anderegg, C; Siebenrock, K A; Langlotz, F

    2007-07-01

    We developed an object-oriented cross-platform program to perform three-dimensional (3D) analysis of hip joint morphology using two-dimensional (2D) anteroposterior (AP) pelvic radiographs. Landmarks extracted from 2D AP pelvic radiographs and optionally an additional lateral pelvic X-ray were combined with a cone beam projection model to reconstruct 3D hip joints. Since individual pelvic orientation can vary considerably, a method for standardizing pelvic orientation was implemented to determine the absolute tilt/rotation. The evaluation of anatomically morphologic differences was achieved by reconstructing the projected acetabular rim and the measured hip parameters as if obtained in a standardized neutral orientation. The program had been successfully used to interactively objectify acetabular version in hips with femoro-acetabular impingement or developmental dysplasia. Hip(2)Norm is written in object-oriented programming language C++ using cross-platform software Qt (TrollTech, Oslo, Norway) for graphical user interface (GUI) and is transportable to any platform.

  8. Neutron detection and characterization for non-proliferation applications using 3D computer optical memories [Use of 3D optical computer memory for radiation detectors/dosimeters. Final progress report

    SciTech Connect

    Gary W. Phillips

    2000-12-20

    We have investigated 3-dimensional optical random access memory (3D-ORAM) materials for detection and characterization of charged particles of neutrons by detecting tracks left by the recoil charged particles produced by the neutrons. We have characterized the response of these materials to protons, alpha particles and carbon-12 nuclei as a functions of dose and energy. We have observed individual tracks using scanning electron microscopy and atomic force microscopy. We are investigating the use of neural net analysis to characterize energetic neutron fields from their track structure in these materials.

  9. Identifying Standing Dead Trees in Forest Areas Based on 3d Single Tree Detection from Full Waveform LIDAR Data

    NASA Astrophysics Data System (ADS)

    Yao, W.; Krzystek, P.; Heurich, M.

    2012-07-01

    In forest ecology, a snag refers to a standing, partly or completely dead tree, often missing a top or most of the smaller branches. The accurate estimation of live and dead biomass in forested ecosystems is important for studies of carbon dynamics, biodiversity, and forest management. Therefore, an understanding of its availability and spatial distribution is required. So far, LiDAR remote sensing has been successfully used to assess live trees and their biomass, but studies focusing on dead trees are rare. The paper develops a methodology for retrieving individual dead trees in a mixed mountain forest using features that are derived from small-footprint airborne full waveform LIDAR data. First, 3D coordinates of the laser beam reflections, the pulse intensity and width are extracted by waveform decomposition. Secondly, 3D single trees are detected by an integrated approach, which delineates both dominate tree crowns and understory small trees in the canopy height model (CHM) using the watershed algorithm followed by applying normalized cuts segmentation to merged watershed areas. Thus, single trees can be obtained as 3D point segments associated with waveform-specific features per point. Furthermore, the tree segments are delivered to feature definition process to derive geometric and reflectional features at single tree level, e.g. volume and maximal diameter of crown, mean intensity, gap fraction, etc. Finally, the spanned feature space for the tree segments is forwarded to a binary classifier using support vector machine (SVM) in order to discriminate dead trees from the living ones. The methodology is applied to datasets that have been captured with the Riegl LMSQ560 laser scanner at a point density of 25 points/m2 in the Bavarian Forest National Park, Germany, respectively under leaf-on and leaf-off conditions for Norway spruces, European beeches and Sycamore maples. The classification experiments lead in the best case to an overall accuracy of 73% in a leaf

  10. Modeling and simulation of a 3D-CMOS silicon photodetector for low-intensity light detection

    NASA Astrophysics Data System (ADS)

    Sabri Alirezaei, Iman; Burte, Edmund P.

    2016-03-01

    This paper presents a design and simulation of a novel high performance 3D-silicon photodetector for implementing in the low intensity light detection at room temperature (300K). The photodetector is modeled by inspiration of general MEMS fabrication to make a 3D- structure in the silicon substrate using a bulk micromachining process, and based on a complementary metal-oxide semiconductor (CMOS) technology. The design includes a vertical n+/p junction as an optical window for lateral illumination. The simulation is carried out using COMSOL Multiphysics relying on theoretical and physical concepts, and then, the assessment of the results is done by the numerical analysis with SILVACO (Atlas) device simulator. Light is regarded as a monochromatic beam with a wavelength of 633nm that is placed 1μm far from the optical window. The simulation is considered under the reverse bias dc voltage in the steadystate. We present photocurrent-voltage (Iph-V) characteristics under different light intensities (2… 10[mW/cm2]), and dark current-voltage (Id-V) characteristics. Comparative studies of sensitivity dependence on the dopant concentration in the substrate as an intrinsic region are accomplished utilizing two different p-type silicon substrates with 1×1015 [1/cm3] and 4×1012 [1/cm3] doping concentration. Moreover, the sensitivity is evaluated with respect to the active substrate thickness. The simulated results confirmed that the high optical sensitivity of the photodetector with low dark current can be realized in this model.

  11. The subjective experience of object recognition: comparing metacognition for object detection and object categorization.

    PubMed

    Meuwese, Julia D I; van Loon, Anouk M; Lamme, Victor A F; Fahrenfort, Johannes J

    2014-05-01

    Perceptual decisions seem to be made automatically and almost instantly. Constructing a unitary subjective conscious experience takes more time. For example, when trying to avoid a collision with a car on a foggy road you brake or steer away in a reflex, before realizing you were in a near accident. This subjective aspect of object recognition has been given little attention. We used metacognition (assessed with confidence ratings) to measure subjective experience during object detection and object categorization for degraded and masked objects, while objective performance was matched. Metacognition was equal for degraded and masked objects, but categorization led to higher metacognition than did detection. This effect turned out to be driven by a difference in metacognition for correct rejection trials, which seemed to be caused by an asymmetry of the distractor stimulus: It does not contain object-related information in the detection task, whereas it does contain such information in the categorization task. Strikingly, this asymmetry selectively impacted metacognitive ability when objective performance was matched. This finding reveals a fundamental difference in how humans reflect versus act on information: When matching the amount of information required to perform two tasks at some objective level of accuracy (acting), metacognitive ability (reflecting) is still better in tasks that rely on positive evidence (categorization) than in tasks that rely more strongly on an absence of evidence (detection).

  12. The subjective experience of object recognition: comparing metacognition for object detection and object categorization.

    PubMed

    Meuwese, Julia D I; van Loon, Anouk M; Lamme, Victor A F; Fahrenfort, Johannes J

    2014-05-01

    Perceptual decisions seem to be made automatically and almost instantly. Constructing a unitary subjective conscious experience takes more time. For example, when trying to avoid a collision with a car on a foggy road you brake or steer away in a reflex, before realizing you were in a near accident. This subjective aspect of object recognition has been given little attention. We used metacognition (assessed with confidence ratings) to measure subjective experience during object detection and object categorization for degraded and masked objects, while objective performance was matched. Metacognition was equal for degraded and masked objects, but categorization led to higher metacognition than did detection. This effect turned out to be driven by a difference in metacognition for correct rejection trials, which seemed to be caused by an asymmetry of the distractor stimulus: It does not contain object-related information in the detection task, whereas it does contain such information in the categorization task. Strikingly, this asymmetry selectively impacted metacognitive ability when objective performance was matched. This finding reveals a fundamental difference in how humans reflect versus act on information: When matching the amount of information required to perform two tasks at some objective level of accuracy (acting), metacognitive ability (reflecting) is still better in tasks that rely on positive evidence (categorization) than in tasks that rely more strongly on an absence of evidence (detection). PMID:24554231

  13. DETECTABILITY OF OORT CLOUD OBJECTS USING KEPLER

    SciTech Connect

    Ofek, Eran O.; Nakar, Ehud

    2010-03-01

    The size distribution and total mass of objects in the Oort Cloud have important implications to the theory of planet formation, including the properties of, and the processes taking place in the early solar system. We discuss the potential of space missions, such as Kepler and CoRoT, designed to discover transiting exoplanets, to detect Oort Cloud, Kuiper Belt, and main belt objects by occultations of background stars. Relying on published dynamical estimates of the content of the Oort Cloud, we find that Kepler's main program is expected to detect between 0 and {approx}100 occultation events by deca-kilometer-sized Oort Cloud objects. The occultation rate depends on the mass of the Oort Cloud, the distance to its 'inner edge', and the size distribution of its objects. In contrast, Kepler is unlikely to find occultations by Kuiper Belt or main belt asteroids, mainly due to the fact that it is observing a high ecliptic latitude field. Occultations by solar system objects will appear as a photometric deviation in a single measurement, implying that the information regarding the timescale and light-curve shape of each event is lost. We present statistical methods that have the potential to verify the authenticity of occultation events by solar system objects, to estimate the distance to the occulting population, and to constrain their size distribution. Our results are useful for planning of future space-based exoplanet searches in a way that will maximize the probability of detecting solar system objects, without hampering the main science goals.

  14. Portable, Easy-to-Operate, and Antifouling Microcapsule Array Chips Fabricated by 3D Ice Printing for Visual Target Detection.

    PubMed

    Zhang, Hong-Ze; Zhang, Fang-Ting; Zhang, Xiao-Hui; Huang, Dong; Zhou, Ying-Lin; Li, Zhi-Hong; Zhang, Xin-Xiang

    2015-06-16

    Herein, we proposed a portable, easy-to-operate, and antifouling microcapsule array chip for target detection. This prepackaged chip was fabricated by innovative and cost-effective 3D ice printing integrating with photopolymerization sealing which could eliminate complicated preparation of wet chemistry and effectively resist outside contaminants. Only a small volume of sample (2 μL for each microcapsule) was consumed to fulfill the assay. All the reagents required for the analysis were stored in ice form within the microcapsule before use, which guaranteed the long-term stability of microcapsule array chips. Nitrite and glucose were chosen as models for proof of concept to achieve an instant quantitative detection by naked eyes without the need of external sophisticated instruments. The simplicity, low cost, and small sample consumption endowed ice-printing microcapsule array chips with potential commercial value in the fields of on-site environmental monitoring, medical diagnostics, and rapid high-throughput point-of-care quantitative assay. PMID:25970032

  15. Portable, Easy-to-Operate, and Antifouling Microcapsule Array Chips Fabricated by 3D Ice Printing for Visual Target Detection.

    PubMed

    Zhang, Hong-Ze; Zhang, Fang-Ting; Zhang, Xiao-Hui; Huang, Dong; Zhou, Ying-Lin; Li, Zhi-Hong; Zhang, Xin-Xiang

    2015-06-16

    Herein, we proposed a portable, easy-to-operate, and antifouling microcapsule array chip for target detection. This prepackaged chip was fabricated by innovative and cost-effective 3D ice printing integrating with photopolymerization sealing which could eliminate complicated preparation of wet chemistry and effectively resist outside contaminants. Only a small volume of sample (2 μL for each microcapsule) was consumed to fulfill the assay. All the reagents required for the analysis were stored in ice form within the microcapsule before use, which guaranteed the long-term stability of microcapsule array chips. Nitrite and glucose were chosen as models for proof of concept to achieve an instant quantitative detection by naked eyes without the need of external sophisticated instruments. The simplicity, low cost, and small sample consumption endowed ice-printing microcapsule array chips with potential commercial value in the fields of on-site environmental monitoring, medical diagnostics, and rapid high-throughput point-of-care quantitative assay.

  16. Object detection in side scan sonar

    NASA Astrophysics Data System (ADS)

    Wang, Wenwu; Cheng, Binbin; Chen, Yao

    2015-12-01

    Automatic target detection is a challenging task as the response from an underwater target may vary greatly depending on its configuration, sonar parameters and the environment. We propose a Z- test algorithm for target detection in side scan sonar image which avoids this problem that covers the variation in the target response. A Z-test is performed on the means of the pixel gray levels within and outside the window area, a detection being called when the value of test statistic feature exceeds a certain threshold. The algorithm is formulated for real-time execution on limited memory commercial-of-the-shelf platforms and is capable of detection objects on the seabed-bottom.

  17. Method for the determination of the modulation transfer function (MTF) in 3D x-ray imaging systems with focus on correction for finite extent of test objects

    NASA Astrophysics Data System (ADS)

    Schäfer, Dirk; Wiegert, Jens; Bertram, Matthias

    2007-03-01

    It is well known that rotational C-arm systems are capable of providing 3D tomographic X-ray images with much higher spatial resolution than conventional CT systems. Using flat X-ray detectors, the pixel size of the detector typically is in the range of the size of the test objects. Therefore, the finite extent of the "point" source cannot be neglected for the determination of the MTF. A practical algorithm has been developed that includes bias estimation and subtraction, averaging in the spatial domain, and correction for the frequency content of the imaged bead or wire. Using this algorithm, the wire and the bead method are analyzed for flat detector based 3D X-ray systems with the use of standard CT performance phantoms. Results on both experimental and simulated data are presented. It is found that the approximation of applying the analysis of the wire method to a bead measurement is justified within 3% accuracy up to the first zero of the MTF.

  18. Combining contour detection algorithms for the automatic extraction of the preparation line from a dental 3D measurement

    NASA Astrophysics Data System (ADS)

    Ahlers, Volker; Weigl, Paul; Schachtzabel, Hartmut

    2005-04-01

    Due to the increasing demand for high-quality ceramic crowns and bridges, the CAD/CAM-based production of dental restorations has been a subject of intensive research during the last fifteen years. A prerequisite for the efficient processing of the 3D measurement of prepared teeth with a minimal amount of user interaction is the automatic determination of the preparation line, which defines the sealing margin between the restoration and the prepared tooth. Current dental CAD/CAM systems mostly require the interactive definition of the preparation line by the user, at least by means of giving a number of start points. Previous approaches to the automatic extraction of the preparation line rely on single contour detection algorithms. In contrast, we use a combination of different contour detection algorithms to find several independent potential preparation lines from a height profile of the measured data. The different algorithms (gradient-based, contour-based, and region-based) show their strengths and weaknesses in different clinical situations. A classifier consisting of three stages (range check, decision tree, support vector machine), which is trained by human experts with real-world data, finally decides which is the correct preparation line. In a test with 101 clinical preparations, a success rate of 92.0% has been achieved. Thus the combination of different contour detection algorithms yields a reliable method for the automatic extraction of the preparation line, which enables the setup of a turn-key dental CAD/CAM process chain with a minimal amount of interactive screen work.

  19. 3D-printed chip for detection of methicillin-resistant Staphylococcus aureus labeled with gold nanoparticles.

    PubMed

    Chudobova, Dagmar; Cihalova, Kristyna; Skalickova, Sylvie; Zitka, Jan; Rodrigo, Miguel Angel Merlos; Milosavljevic, Vedran; Hynek, David; Kopel, Pavel; Vesely, Radek; Adam, Vojtech; Kizek, Rene

    2015-02-01

    Methicillin-resistant Staphylococcus aureus (MRSA) is a dangerous pathogen occurring not only in hospitals but also in foodstuff. Currently, discussions on the issue of the increasing resistance, and timely and rapid diagnostic of resistance strains have become more frequent and sought. Therefore, the aim of this study was to design an effective platform for DNA isolation from different species of microorganisms as well as the amplification of mecA gene that encodes the resistance to β-lactam antibiotic formation and is contained in MRSA. For this purpose, we fabricated 3D-printed chip that was suitable for bacterial cultivation, DNA isolation, PCR, and detection of amplified gene using gold nanoparticle (AuNP) probes as an indicator of MRSA. Confirmation of the MRSA presence in the samples was based on a specific interaction between mecA gene with the AuNP probes and a colorimetric detection, which utilized the noncross-linking aggregation phenomenon of DNA-functionalized AuNPs. To test the whole system, we analyzed several real refractive indexes, in which two of them were positively scanned to find the presence of mecA gene. The aggregation of AuNP probes were reflected by 75% decrease of absorbance (λ = 530 nm) and change in AuNPs size from 3 ± 0.05 to 4 ± 0.05 nm (n = 5). We provide the one-step identification of mecA gene using the unique platform that employs the rapid, low-cost, and easy-to-use colorimetric method for MRSA detection in various samples.

  20. Computer aided detection of surgical retained foreign object for prevention

    SciTech Connect

    Hadjiiski, Lubomir Marentis, Theodore C.; Rondon, Lucas; Chan, Heang-Ping; Chaudhury, Amrita R.; Chronis, Nikolaos

    2015-03-15

    Purpose: Surgical retained foreign objects (RFOs) have significant morbidity and mortality. They are associated with approximately $1.5 × 10{sup 9} annually in preventable medical costs. The detection accuracy of radiographs for RFOs is a mediocre 59%. The authors address the RFO problem with two complementary technologies: a three-dimensional (3D) gossypiboma micro tag, the μTag that improves the visibility of RFOs on radiographs, and a computer aided detection (CAD) system that detects the μTag. It is desirable for the CAD system to operate in a high specificity mode in the operating room (OR) and function as a first reader for the surgeon. This allows for fast point of care results and seamless workflow integration. The CAD system can also operate in a high sensitivity mode as a second reader for the radiologist to ensure the highest possible detection accuracy. Methods: The 3D geometry of the μTag produces a similar two dimensional (2D) depiction on radiographs regardless of its orientation in the human body and ensures accurate detection by a radiologist and the CAD. The authors created a data set of 1800 cadaver images with the 3D μTag and other common man-made surgical objects positioned randomly. A total of 1061 cadaver images contained a single μTag and the remaining 739 were without μTag. A radiologist marked the location of the μTag using an in-house developed graphical user interface. The data set was partitioned into three independent subsets: a training set, a validation set, and a test set, consisting of 540, 560, and 700 images, respectively. A CAD system with modules that included preprocessing μTag enhancement, labeling, segmentation, feature analysis, classification, and detection was developed. The CAD system was developed using the training and the validation sets. Results: On the training set, the CAD achieved 81.5% sensitivity with 0.014 false positives (FPs) per image in a high specificity mode for the surgeons in the OR and 96

  1. Preliminary study of statistical pattern recognition-based coin counterfeit detection by means of high resolution 3D scanners

    NASA Astrophysics Data System (ADS)

    Leich, Marcus; Kiltz, Stefan; Krätzer, Christian; Dittmann, Jana; Vielhauer, Claus

    2011-03-01

    According to the European Commission around 200,000 counterfeit Euro coins are removed from circulation every year. While approaches exist to automatically detect these coins, satisfying error rates are usually only reached for low quality forgeries, so-called "local classes". High-quality minted forgeries ("common classes") pose a problem for these methods as well as for trained humans. This paper presents a first approach for statistical analysis of coins based on high resolution 3D data acquired with a chromatic white light sensor. The goal of this analysis is to determine whether two coins are of common origin. The test set for these first and new investigations consists of 62 coins from not more than five different sources. The analysis is based on the assumption that, apart from markings caused by wear such as scratches and residue consisting of grease and dust, coins from equal origin have a more similar height field than coins from different mints. First results suggest that the selected approach is heavily affected by influences of wear like dents and scratches and the further research is required the eliminate this influence. A course for future work is outlined.

  2. Automated 3D detection and classification of Giardia lamblia cysts using digital holographic microscopy with partially coherent source

    NASA Astrophysics Data System (ADS)

    El Mallahi, A.; Detavernier, A.; Yourassowsky, C.; Dubois, F.

    2012-06-01

    Over the past century, monitoring of Giardia lamblia became a matter of concern for all drinking water suppliers worldwide. Indeed, this parasitic flagellated protozoan is responsible for giardiasis, a widespread diarrhoeal disease (200 million symptomatic individuals) that can lead immunocompromised individuals to death. The major difficulty raised by Giardia lamblia's cyst, its vegetative transmission form, is its ability to survive for long periods in harsh environments, including the chlorine concentrations and treatment duration used traditionally in water disinfection. Currently, there is a need for a reliable, inexpensive, and easy-to-use sensor for the identification and quantification of cysts in the incoming water. For this purpose, we investigated the use of a digital holographic microscope working with partially coherent spatial illumination that reduces the coherent noise. Digital holography allows one to numerically investigate a volume by refocusing the different plane of depth of a hologram. In this paper, we perform an automated 3D analysis that computes the complex amplitude of each hologram, detects all the particles present in the whole volume given by one hologram and refocuses them if there are out of focus using a refocusing criterion based on the integrated complex amplitude modulus and we obtain the (x,y,z) coordinates of each particle. Then the segmentation of the particles is processed and a set of morphological and textures features characteristic to Giardia lamblia cysts is computed in order to classify each particles in the right classes.

  3. Radar detection of moving objects around corners

    NASA Astrophysics Data System (ADS)

    Sume, A.; Gustafsson, M.; Jänis, A.; Nilsson, S.; Rahm, J.; Örbom, A.

    2009-05-01

    Detection of moving objects around corners, with no direct line-of-sight to the objects, is demonstrated in experiments using a coherent test-range radar. A setting was built up on the test-range ground consisting of two perpendicular wall sections forming a corner, with an opposite wall, intended to mimic a street scenario on a reduced scale. Two different wall materials were used, viz. light concrete and metallic walls. The latter choice served as reference, with elimination of transmission through the walls, e.g. facilitating comparison with theoretical calculations. Standard radar reflectors were used as one kind of target objects, in horizontal, circular movement, produced by a turntable. A human formed a second target, both walking and at standstill with micro-Doppler movements of body parts. The radar signal was produced by frequency stepping of a gated CW (Continuous Wave) waveform over a bandwidth of 2 or 4 GHz, between 8.5 and 12.5 GHz. Standard Doppler signal processing has been applied, consisting of a double FFT. The first of these produced "range profiles", on which the second FFT was applied for specific range gates, which resulted in Doppler frequency spectra, used for the detection. The reference reflectors as well as the human could be detected in this scenario. The target detections were achieved both in the wave component having undergone specular reflection in the opposite wall (strongest) as well as the diffracted component around the corner. Time-frequency analysis using Short Time Fourier Transform technique brought out micro-Doppler components in the signature of a walking human. These experiments have been complemented with theoretical field calculations and separate reflection measurements of common building materials.

  4. Object and activity detection from aerial video

    NASA Astrophysics Data System (ADS)

    Se, Stephen; Shi, Feng; Liu, Xin; Ghazel, Mohsen

    2015-05-01

    Aerial video surveillance has advanced significantly in recent years, as inexpensive high-quality video cameras and airborne platforms are becoming more readily available. Video has become an indispensable part of military operations and is now becoming increasingly valuable in the civil and paramilitary sectors. Such surveillance capabilities are useful for battlefield intelligence and reconnaissance as well as monitoring major events, border control and critical infrastructure. However, monitoring this growing flood of video data requires significant effort from increasingly large numbers of video analysts. We have developed a suite of aerial video exploitation tools that can alleviate mundane monitoring from the analysts, by detecting and alerting objects and activities that require analysts' attention. These tools can be used for both tactical applications and post-mission analytics so that the video data can be exploited more efficiently and timely. A feature-based approach and a pixel-based approach have been developed for Video Moving Target Indicator (VMTI) to detect moving objects at real-time in aerial video. Such moving objects can then be classified by a person detector algorithm which was trained with representative aerial data. We have also developed an activity detection tool that can detect activities of interests in aerial video, such as person-vehicle interaction. We have implemented a flexible framework so that new processing modules can be added easily. The Graphical User Interface (GUI) allows the user to configure the processing pipeline at run-time to evaluate different algorithms and parameters. Promising experimental results have been obtained using these tools and an evaluation has been carried out to characterize their performance.

  5. Diagnostic performance of 3D TSE MRI versus 2D TSE MRI of the knee at 1.5 T, with prompt arthroscopic correlation, in the detection of meniscal and cruciate ligament tears*

    PubMed Central

    Chagas-Neto, Francisco Abaeté; Nogueira-Barbosa, Marcello Henrique; Lorenzato, Mário Müller; Salim, Rodrigo; Kfuri-Junior, Maurício; Crema, Michel Daoud

    2016-01-01

    Objective To compare the diagnostic performance of the three-dimensional turbo spin-echo (3D TSE) magnetic resonance imaging (MRI) technique with the performance of the standard two-dimensional turbo spin-echo (2D TSE) protocol at 1.5 T, in the detection of meniscal and ligament tears. Materials and Methods Thirty-eight patients were imaged twice, first with a standard multiplanar 2D TSE MR technique, and then with a 3D TSE technique, both in the same 1.5 T MRI scanner. The patients underwent knee arthroscopy within the first three days after the MRI. Using arthroscopy as the reference standard, we determined the diagnostic performance and agreement. Results For detecting anterior cruciate ligament tears, the 3D TSE and routine 2D TSE techniques showed similar values for sensitivity (93% and 93%, respectively) and specificity (80% and 85%, respectively). For detecting medial meniscal tears, the two techniques also had similar sensitivity (85% and 83%, respectively) and specificity (68% and 71%, respectively). In addition, for detecting lateral meniscal tears, the two techniques had similar sensitivity (58% and 54%, respectively) and specificity (82% and 92%, respectively). There was a substantial to almost perfect intraobserver and interobserver agreement when comparing the readings for both techniques. Conclusion The 3D TSE technique has a diagnostic performance similar to that of the routine 2D TSE protocol for detecting meniscal and anterior cruciate ligament tears at 1.5 T, with the advantage of faster acquisition. PMID:27141127

  6. Water Detection Based on Object Reflections

    NASA Technical Reports Server (NTRS)

    Rankin, Arturo L.; Matthies, Larry H.

    2012-01-01

    Water bodies are challenging terrain hazards for terrestrial unmanned ground vehicles (UGVs) for several reasons. Traversing through deep water bodies could cause costly damage to the electronics of UGVs. Additionally, a UGV that is either broken down due to water damage or becomes stuck in a water body during an autonomous operation will require rescue, potentially drawing critical resources away from the primary operation and increasing the operation cost. Thus, robust water detection is a critical perception requirement for UGV autonomous navigation. One of the properties useful for detecting still water bodies is that their surface acts as a horizontal mirror at high incidence angles. Still water bodies in wide-open areas can be detected by geometrically locating the exact pixels in the sky that are reflecting on candidate water pixels on the ground, predicting if ground pixels are water based on color similarity to the sky and local terrain features. But in cluttered areas where reflections of objects in the background dominate the appearance of the surface of still water bodies, detection based on sky reflections is of marginal value. Specifically, this software attempts to solve the problem of detecting still water bodies on cross-country terrain in cluttered areas at low cost.

  7. Development of an iterative reconstruction method to overcome 2D detector low resolution limitations in MLC leaf position error detection for 3D dose verification in IMRT.

    PubMed

    Visser, R; Godart, J; Wauben, D J L; Langendijk, J A; Van't Veld, A A; Korevaar, E W

    2016-05-21

    The objective of this study was to introduce a new iterative method to reconstruct multi leaf collimator (MLC) positions based on low resolution ionization detector array measurements and to evaluate its error detection performance. The iterative reconstruction method consists of a fluence model, a detector model and an optimizer. Expected detector response was calculated using a radiotherapy treatment plan in combination with the fluence model and detector model. MLC leaf positions were reconstructed by minimizing differences between expected and measured detector response. The iterative reconstruction method was evaluated for an Elekta SLi with 10.0 mm MLC leafs in combination with the COMPASS system and the MatriXX Evolution (IBA Dosimetry) detector with a spacing of 7.62 mm. The detector was positioned in such a way that each leaf pair of the MLC was aligned with one row of ionization chambers. Known leaf displacements were introduced in various field geometries ranging from  -10.0 mm to 10.0 mm. Error detection performance was tested for MLC leaf position dependency relative to the detector position, gantry angle dependency, monitor unit dependency, and for ten clinical intensity modulated radiotherapy (IMRT) treatment beams. For one clinical head and neck IMRT treatment beam, influence of the iterative reconstruction method on existing 3D dose reconstruction artifacts was evaluated. The described iterative reconstruction method was capable of individual MLC leaf position reconstruction with millimeter accuracy, independent of the relative detector position within the range of clinically applied MU's for IMRT. Dose reconstruction artifacts in a clinical IMRT treatment beam were considerably reduced as compared to the current dose verification procedure. The iterative reconstruction method allows high accuracy 3D dose verification by including actual MLC leaf positions reconstructed from low resolution 2D measurements. PMID:27100169

  8. Development of an iterative reconstruction method to overcome 2D detector low resolution limitations in MLC leaf position error detection for 3D dose verification in IMRT

    NASA Astrophysics Data System (ADS)

    Visser, R.; Godart, J.; Wauben, D. J. L.; Langendijk, J. A.; van't Veld, A. A.; Korevaar, E. W.

    2016-05-01

    The objective of this study was to introduce a new iterative method to reconstruct multi leaf collimator (MLC) positions based on low resolution ionization detector array measurements and to evaluate its error detection performance. The iterative reconstruction method consists of a fluence model, a detector model and an optimizer. Expected detector response was calculated using a radiotherapy treatment plan in combination with the fluence model and detector model. MLC leaf positions were reconstructed by minimizing differences between expected and measured detector response. The iterative reconstruction method was evaluated for an Elekta SLi with 10.0 mm MLC leafs in combination with the COMPASS system and the MatriXX Evolution (IBA Dosimetry) detector with a spacing of 7.62 mm. The detector was positioned in such a way that each leaf pair of the MLC was aligned with one row of ionization chambers. Known leaf displacements were introduced in various field geometries ranging from  -10.0 mm to 10.0 mm. Error detection performance was tested for MLC leaf position dependency relative to the detector position, gantry angle dependency, monitor unit dependency, and for ten clinical intensity modulated radiotherapy (IMRT) treatment beams. For one clinical head and neck IMRT treatment beam, influence of the iterative reconstruction method on existing 3D dose reconstruction artifacts was evaluated. The described iterative reconstruction method was capable of individual MLC leaf position reconstruction with millimeter accuracy, independent of the relative detector position within the range of clinically applied MU’s for IMRT. Dose reconstruction artifacts in a clinical IMRT treatment beam were considerably reduced as compared to the current dose verification procedure. The iterative reconstruction method allows high accuracy 3D dose verification by including actual MLC leaf positions reconstructed from low resolution 2D measurements.

  9. Development of an iterative reconstruction method to overcome 2D detector low resolution limitations in MLC leaf position error detection for 3D dose verification in IMRT

    NASA Astrophysics Data System (ADS)

    Visser, R.; Godart, J.; Wauben, D. J. L.; Langendijk, J. A.; van’t Veld, A. A.; Korevaar, E. W.

    2016-05-01

    The objective of this study was to introduce a new iterative method to reconstruct multi leaf collimator (MLC) positions based on low resolution ionization detector array measurements and to evaluate its error detection performance. The iterative reconstruction method consists of a fluence model, a detector model and an optimizer. Expected detector response was calculated using a radiotherapy treatment plan in combination with the fluence model and detector model. MLC leaf positions were reconstructed by minimizing differences between expected and measured detector response. The iterative reconstruction method was evaluated for an Elekta SLi with 10.0 mm MLC leafs in combination with the COMPASS system and the MatriXX Evolution (IBA Dosimetry) detector with a spacing of 7.62 mm. The detector was positioned in such a way that each leaf pair of the MLC was aligned with one row of ionization chambers. Known leaf displacements were introduced in various field geometries ranging from  ‑10.0 mm to 10.0 mm. Error detection performance was tested for MLC leaf position dependency relative to the detector position, gantry angle dependency, monitor unit dependency, and for ten clinical intensity modulated radiotherapy (IMRT) treatment beams. For one clinical head and neck IMRT treatment beam, influence of the iterative reconstruction method on existing 3D dose reconstruction artifacts was evaluated. The described iterative reconstruction method was capable of individual MLC leaf position reconstruction with millimeter accuracy, independent of the relative detector position within the range of clinically applied MU’s for IMRT. Dose reconstruction artifacts in a clinical IMRT treatment beam were considerably reduced as compared to the current dose verification procedure. The iterative reconstruction method allows high accuracy 3D dose verification by including actual MLC leaf positions reconstructed from low resolution 2D measurements.

  10. Evaluation of object level change detection techniques

    NASA Astrophysics Data System (ADS)

    Irvine, John M.; Bergeron, Stuart; Hugo, Doug; O'Brien, Michael A.

    2007-04-01

    A variety of change detection (CD) methods have been developed and employed to support imagery analysis for applications including environmental monitoring, mapping, and support to military operations. Evaluation of these methods is necessary to assess technology maturity, identify areas for improvement, and support transition to operations. This paper presents a methodology for conducting this type of evaluation, discusses the challenges, and illustrates the techniques. The evaluation of object-level change detection methods is more complicated than for automated techniques for processing a single image. We explore algorithm performance assessments, emphasizing the definition of the operating conditions (sensor, target, and environmental factors) and the development of measures of performance. Specific challenges include image registration; occlusion due to foliage, cultural clutter and terrain masking; diurnal differences; and differences in viewing geometry. Careful planning, sound experimental design, and access to suitable imagery with image truth and metadata are critical.

  11. Continuous section extraction and over-underbreak detection of tunnel based on 3D laser technology and image analysis

    NASA Astrophysics Data System (ADS)

    Wang, Weixing; Wang, Zhiwei; Han, Ya; Li, Shuang; Zhang, Xin

    2015-03-01

    Over Underbreak detection of road and solve the problemof the roadway data collection difficulties, this paper presents a new method of continuous section extraction and Over Underbreak detection of road based on 3D laser scanning technology and image processing, the method is divided into the following three steps: based on Canny edge detection, local axis fitting, continuous extraction section and Over Underbreak detection of section. First, after Canny edge detection, take the least-squares curve fitting method to achieve partial fitting in axis. Then adjust the attitude of local roadway that makes the axis of the roadway be consistent with the direction of the extraction reference, and extract section along the reference direction. Finally, we compare the actual cross-sectional view and the cross-sectional design to complete Overbreak detected. Experimental results show that the proposed method have a great advantage in computing costs and ensure cross-section orthogonal intercept terms compared with traditional detection methods.

  12. A novel abandoned object detection system based on three-dimensional image information.

    PubMed

    Zeng, Yiliang; Lan, Jinhui; Ran, Bin; Gao, Jing; Zou, Jinlin

    2015-01-01

    A new idea of an abandoned object detection system for road traffic surveillance systems based on three-dimensional image information is proposed in this paper to prevent traffic accidents. A novel Binocular Information Reconstruction and Recognition (BIRR) algorithm is presented to implement the new idea. As initial detection, suspected abandoned objects are detected by the proposed static foreground region segmentation algorithm based on surveillance video from a monocular camera. After detection of suspected abandoned objects, three-dimensional (3D) information of the suspected abandoned object is reconstructed by the proposed theory about 3D object information reconstruction with images from a binocular camera. To determine whether the detected object is hazardous to normal road traffic, road plane equation and height of suspected-abandoned object are calculated based on the three-dimensional information. Experimental results show that this system implements fast detection of abandoned objects and this abandoned object system can be used for road traffic monitoring and public area surveillance.

  13. Detecting abandoned objects using interacting multiple models

    NASA Astrophysics Data System (ADS)

    Becker, Stefan; Münch, David; Kieritz, Hilke; Hübner, Wolfgang; Arens, Michael

    2015-10-01

    In recent years, the wide use of video surveillance systems has caused an enormous increase in the amount of data that has to be stored, monitored, and processed. As a consequence, it is crucial to support human operators with automated surveillance applications. Towards this end an intelligent video analysis module for real-time alerting in case of abandoned objects in public spaces is proposed. The overall processing pipeline consists of two major parts. First, person motion is modeled using an Interacting Multiple Model (IMM) filter. The IMM filter estimates the state of a person according to a finite-state, discrete-time Markov chain. Second, the location of persons that stay at a fixed position defines a region of interest, in which a nonparametric background model with dynamic per-pixel state variables identifies abandoned objects. In case of a detected abandoned object, an alarm event is triggered. The effectiveness of the proposed system is evaluated on the PETS 2006 dataset and the i-Lids dataset, both reflecting prototypical surveillance scenarios.

  14. Determining root correspondence between previously and newly detected objects

    SciTech Connect

    Paglieroni, David W.; Beer, N Reginald

    2014-06-17

    A system that applies attribute and topology based change detection to networks of objects that were detected on previous scans of a structure, roadway, or area of interest. The attributes capture properties or characteristics of the previously detected objects, such as location, time of detection, size, elongation, orientation, etc. The topology of the network of previously detected objects is maintained in a constellation database that stores attributes of previously detected objects and implicitly captures the geometrical structure of the network. A change detection system detects change by comparing the attributes and topology of new objects detected on the latest scan to the constellation database of previously detected objects.

  15. Detection of antibodies against foot-and-mouth disease virus using a liquid-phase blocking sandwich ELISA (LPBE) with a bioengineered 3D protein.

    PubMed

    O'Donnell, V K; Boyle, D B; Sproat, K; Fondevila, N A; Forman, A; Schudel, A A; Smitsaart, E N

    1996-04-01

    A liquid-phase blocking sandwich enzyme-linked immunosorbent assay (ELISA-3D) was developed to detect specific antibodies to the 3D protein in sera from foot-and-mouth disease (FMD) virus (FMDV)-infected animals. The assay uses a nonstructural 3D recombinant protein and two polyclonal antisera, one for capture (bovine) and the other for detector (guinea pig). The specificity of the assay was demonstrated by negative results with 101 sera of cattle from the FMD-free zone in Argentina and with bovine and porcine sera raised against various RNA and DNA viruses. The ELISA-3D was able to detect antibodies in cattle after natural or experimental infection with FMDV of A, O, or C types as early as 5 days postinfection and at later stages in persistently infected animals. Comparison of the results with those obtained with the routinely used agar gel immunodiffusion test and a previously described ELISA, both employing a partially purified virus-infection-associated antigen, shows that the ELISA-3D is highly sensitive and specific and gives reproducible results. Its use as a tool for monitoring viral activity and for certification of FMDV-free animals is recommended. PMID:8744733

  16. Detection of antibodies against foot-and-mouth disease virus using a liquid-phase blocking sandwich ELISA (LPBE) with a bioengineered 3D protein.

    PubMed

    O'Donnell, V K; Boyle, D B; Sproat, K; Fondevila, N A; Forman, A; Schudel, A A; Smitsaart, E N

    1996-04-01

    A liquid-phase blocking sandwich enzyme-linked immunosorbent assay (ELISA-3D) was developed to detect specific antibodies to the 3D protein in sera from foot-and-mouth disease (FMD) virus (FMDV)-infected animals. The assay uses a nonstructural 3D recombinant protein and two polyclonal antisera, one for capture (bovine) and the other for detector (guinea pig). The specificity of the assay was demonstrated by negative results with 101 sera of cattle from the FMD-free zone in Argentina and with bovine and porcine sera raised against various RNA and DNA viruses. The ELISA-3D was able to detect antibodies in cattle after natural or experimental infection with FMDV of A, O, or C types as early as 5 days postinfection and at later stages in persistently infected animals. Comparison of the results with those obtained with the routinely used agar gel immunodiffusion test and a previously described ELISA, both employing a partially purified virus-infection-associated antigen, shows that the ELISA-3D is highly sensitive and specific and gives reproducible results. Its use as a tool for monitoring viral activity and for certification of FMDV-free animals is recommended.

  17. Improvement and characterization of the adhesion of electrospun PLDLA nanofibers on PLDLA-based 3D object substrates for orthopedic application.

    PubMed

    Wimpenny, I; Lahteenkorva, K; Suokas, E; Ashammakhi, N; Yang, Y

    2012-01-01

    Intensive research has demonstrated the clear biological potential of electrospun nanofibers for tissue regeneration and repair. However, nanofibers alone have limited mechanical properties. In this study we took poly(L-lactide-co-D-lactide) (PLDLA)-based 3D objects, one existing medical device (interference screws) and one medical device model (discs) as examples to form composites through coating their surface with electrospun PLDLA nanofibers. We specifically investigated the effects of electrospinning parameters on the improvement of adhesion of the electrospun nanofibers to the PLDLA-based substrates. To reveal the adhesion mechanisms, a novel peel test protocol was developed for the characterization of the adhesion and delamination phenomenon of the nanofibers deposited to substrates. The effect of incubation of the composites under physiological conditions on the adhesion of the nanofibers has also been studied. It was revealed that reduction of the working distance to 10 cm resulted in deposition of residual solvent during electrospinning of nanofibers onto the substrate, causing fiber-fiber bonding. Delamination of this coating occurred between the whole nanofiber layer and substrate, at low stress. Fibers deposited at 15 cm working distance were of smaller diameter and no residual solvent was observed during deposition. Delamination occurred between nanofiber layers, which peeled off under greater stress. This study represents a novel method for the alteration of nanofiber adhesion to substrates, and quantification of the change in the adhesion state, which has potential applications to develop better medical devices for orthopedic tissue repair and regeneration. PMID:21943952

  18. Object detectability at increased ambient lighting conditions.

    PubMed

    Pollard, Benjamin J; Chawla, Amarpreet S; Delong, David M; Hashimoto, Noriyuki; Samei, Ehsan

    2008-06-01

    Under typical dark conditions encountered in diagnostic reading rooms, a reader's pupils will contract and dilate as the visual focus intermittently shifts between the high luminance display and the darker background wall, resulting in increased visual fatigue and the degradation of diagnostic performance. A controlled increase of ambient lighting may, however, reduce the severity of these pupillary adjustments by minimizing the difference between the luminance level to which the eyes adapt while viewing an image (L(adp)) and the luminance level of diffusely reflected light from the area surrounding the display (L(s)). Although ambient lighting in reading rooms has conventionally been kept at a minimum to maintain the perceived contrast of film images, proper Digital Imaging and Communications in Medicine (DICOM) calibration of modern medical-grade liquid crystal displays can compensate for minor lighting increases with very little loss of image contrast. This paper describes two psychophysical studies developed to evaluate and refine optimum reading room ambient lighting conditions through the use of observational tasks intended to simulate real clinical practices. The first study utilized the biologic contrast response of the human visual system to determine a range of representative L(adp) values for typical medical images. Readers identified low contrast horizontal objects in circular foregrounds of uniform luminance (5, 12, 20, and 30 cd/m2) embedded within digitized mammograms. The second study examined the effect of increased ambient lighting on the detection of subtle objects embedded in circular foregrounds of uniform luminance (5, 12, and 35 cd/m2) centered within a constant background of 12 cd/m2 luminance. The images were displayed under a dark room condition (1 lux) and an increased ambient lighting level (50 lux) such that the luminance level of the diffusely reflected light from the background wall was approximately equal to the image L(adp) value of

  19. 3D Elevation Program—Virtual USA in 3D

    USGS Publications Warehouse

    Lukas, Vicki; Stoker, J.M.

    2016-01-01

    The U.S. Geological Survey (USGS) 3D Elevation Program (3DEP) uses a laser system called ‘lidar’ (light detection and ranging) to create a virtual reality map of the Nation that is very accurate. 3D maps have many uses with new uses being discovered all the time.  

  20. 3D Elevation Program—Virtual USA in 3D

    USGS Publications Warehouse

    Lukas, Vicki; Stoker, J.M.

    2016-04-14

    The U.S. Geological Survey (USGS) 3D Elevation Program (3DEP) uses a laser system called ‘lidar’ (light detection and ranging) to create a virtual reality map of the Nation that is very accurate. 3D maps have many uses with new uses being discovered all the time.  

  1. Bimetallic 3D nanostar dimers in ring cavities: recyclable and robust surface-enhanced Raman scattering substrates for signal detection from few molecules.

    PubMed

    Gopalakrishnan, Anisha; Chirumamilla, Manohar; De Angelis, Francesco; Toma, Andrea; Zaccaria, Remo Proietti; Krahne, Roman

    2014-08-26

    Top-down fabrication of electron-beam lithography (EBL)-defined metallic nanostructures is a successful route to obtain extremely high electromagnetic field enhancement via plasmonic effects in well-defined regions. To this aim, various geometries have been introduced such as disks, triangles, dimers, rings, self-similar lenses, and more. In particular, metallic dimers are highly efficient for surface-enhanced Raman spectroscopy (SERS), and their decoupling from the substrate in a three-dimensional design has proven to further improve their performance. However, the large fabrication time and cost has hindered EBL-defined structures from playing a role in practical applications. Here we present three-dimensional nanostar dimer devices that can be recycled via maskless metal etching and deposition processes, due to conservation of the nanostructure pattern in the 3D geometry of the underlying Si substrate. Furthermore, our 3D-nanostar-dimer-in-ring structures (3D-NSDiRs) incorporate several advantageous aspects for SERS by enhancing the performance of plasmonic dimers via an external ring cavity, by efficient decoupling from the substrate through an elevated 3D design, and by bimetallic AuAg layers that exploit the increased performance of Ag while maintaining the biocompatibility of Au. We demonstrate SERS detection on rhodamine and adenine at extremely low density up to the limit of few molecules and analyze the field enhancement of the 3D-NSDiRs with respect to the exciting wavelength and metal composition.

  2. 3D TiO{sub 2} submicrostructures decorated by silver nanoparticles as SERS substrate for organic pollutants detection and degradation

    SciTech Connect

    Chen, Jianjun; Su, Huilan; You, Xueling; Gao, Jing; Lau, Woon Ming; Zhang, Di

    2014-01-01

    Graphical abstract: - Highlights: • Contrive a multifunctional SERS substrate with 3D sub-micrometer structure and multicomponent. • The blue wing of butterfly (Euploea mulciber) is used as template for Ag/TiO{sub 2} nanocomposites. • The 3D submicrostructures Ag/TiO{sub 2} presents superior SERS effect and photocatalytic activity. • Pave a facile route to prepare multifunctional material by utilizing smart structural designs in nature. - Abstract: The blue wing of butterfly Euploea mulciber is used as a template to generate Ag/TiO{sub 2} nanocomposites. Thereinto, Ag nanoparticles are deposited uniformly onto TiO{sub 2} substrate with three dimensional (3D) submicrometer structures. This unique 3D sub-micrometer structures featured with ridges, ribs and struts can provide a large number of active “hot spots” for enhanced Raman signal. Meanwhile, depositing Ag onto the TiO{sub 2} surface can greatly boost its SERS effect and photocatalytic activity by bringing additional electrons into the molecules and inhibiting electrons–holes recombination. Thus, the as-prepared 3D Ag/TiO{sub 2} submicrostructures can not only offer sensitive and reproducible SERS signals, but also present superior photocatalytic activity, which can be utilized to detect and eliminate organic pollutants.

  3. Automated Detection of 3D Landmarks for the Elimination of Non-Biological Variation in Geometric Morphometric Analyses

    PubMed Central

    Aneja, D; Vora, SR; Camci, ED; Shapiro, LG; Cox, TC

    2015-01-01

    Landmark-based morphometric analyses are used by anthropologists, developmental and evolutionary biologists to understand shape and size differences (eg. in the cranioskeleton) between groups of specimens. The standard, labor intensive approach is for researchers to manually place landmarks on 3D image datasets. As landmark recognition is subject to inaccuracies of human perception, digitization of landmark coordinates is typically repeated (often by more than one person) and the mean coordinates are used. In an attempt to improve efficiency and reproducibility between researchers, we have developed an algorithm to locate landmarks on CT mouse hemi-mandible data. The method is evaluated on 3D meshes of 28-day old mice, and results compared to landmarks manually identified by experts. Quantitative shape comparison between two inbred mouse strains demonstrate that data obtained using our algorithm also has enhanced statistical power when compared to data obtained by manual landmarking. PMID:26258171

  4. Validation of the BacT/ALERT®3D automated culture system for the detection of microbial contamination of epithelial cell culture medium.

    PubMed

    Plantamura, E; Huyghe, G; Panterne, B; Delesalle, N; Thépot, A; Reverdy, M E; Damour, O; Auxenfans, Céline

    2012-08-01

    Living tissue engineering for regenerative therapy cannot withstand the usual pharmacopoeia methods of purification and terminal sterilization. Consequently, these products must be manufactured under aseptic conditions at microbiologically controlled environment facilities. This study was proposed to validate BacT/ALERT(®)3D automated culture system for microbiological control of epithelial cell culture medium (ECCM). Suspensions of the nine microorganisms recommended by the European Pharmacopoeia (Chap. 2.6.27: "Microbiological control of cellular products"), plus one species from oral mucosa and two negative controls with no microorganisms were prepared in ECCM. They were inoculated in FA (anaerobic) and SN (aerobic) culture bottles (Biomérieux, Lyon, France) and incubated in a BacT/ALERT(®)3D automated culture system. For each species, five sets of bottles were inoculated for reproducibility testing: one sample was incubated at the French Health Products Agency laboratory (reference) and the four others at Cell and Tissue Bank of Lyon, France. The specificity of the positive culture bottles was verified by Gram staining and then subcultured to identify the microorganism grown. The BacT/ALERT(®)3D system detected all the inoculated microorganisms in less than 2 days except Propionibacterium acnes which was detected in 3 days. In conclusion, this study demonstrates that the BacT/ALERT(®)3D system can detect both aerobic and anaerobic bacterial and fungal contamination of an epithelial cell culture medium consistent with the European Pharmacopoeia chapter 2.6.27 recommendations. It showed the specificity, sensitivity, and precision of the BacT/ALERT(®)3D method, since all the microorganisms seeded were detected in both sites and the uncontaminated medium ECCM remained negative at 7 days. PMID:22160810

  5. Using the Flow-3D General Moving Object Model to Simulate Coupled Liquid Slosh - Container Dynamics on the SPHERES Slosh Experiment: Aboard the International Space Station

    NASA Technical Reports Server (NTRS)

    Schulman, Richard; Kirk, Daniel; Marsell, Brandon; Roth, Jacob; Schallhorn, Paul

    2013-01-01

    The SPHERES Slosh Experiment (SSE) is a free floating experimental platform developed for the acquisition of long duration liquid slosh data aboard the International Space Station (ISS). The data sets collected will be used to benchmark numerical models to aid in the design of rocket and spacecraft propulsion systems. Utilizing two SPHERES Satellites, the experiment will be moved through different maneuvers designed to induce liquid slosh in the experiment's internal tank. The SSE has a total of twenty-four thrusters to move the experiment. In order to design slosh generating maneuvers, a parametric study with three maneuvers types was conducted using the General Moving Object (GMO) model in Flow-30. The three types of maneuvers are a translation maneuver, a rotation maneuver and a combined rotation translation maneuver. The effectiveness of each maneuver to generate slosh is determined by the deviation of the experiment's trajectory as compared to a dry mass trajectory. To fully capture the effect of liquid re-distribution on experiment trajectory, each thruster is modeled as an independent force point in the Flow-3D simulation. This is accomplished by modifying the total number of independent forces in the GMO model from the standard five to twenty-four. Results demonstrate that the most effective slosh generating maneuvers for all motions occurs when SSE thrusters are producing the highest changes in SSE acceleration. The results also demonstrate that several centimeters of trajectory deviation between the dry and slosh cases occur during the maneuvers; while these deviations seem small, they are measureable by SSE instrumentation.

  6. An analysis of TA-Student Interaction and the Development of Concepts in 3-d Space Through Language, Objects, and Gesture in a College-level Geoscience Laboratory

    NASA Astrophysics Data System (ADS)

    King, S. L.

    2015-12-01

    The purpose of this study is twofold: 1) to describe how a teaching assistant (TA) in an undergraduate geology laboratory employs a multimodal system in order to mediate the students' understanding of scientific knowledge and develop a contextualization of a concept in three-dimensional space and 2) to describe how a linguistic awareness of gestural patterns can be used to inform TA training assessment of students' conceptual understanding in situ. During the study the TA aided students in developing the conceptual understanding and reconstruction of a meteoric impact, which produces shatter cone formations. The concurrent use of speech, gesture, and physical manipulation of objects is employed by the TA in order to aid the conceptual understanding of this particular phenomenon. Using the methods of gestural analysis in works by Goldin-Meadow, 2000 and McNeill, 1992, this study describes the gestures of the TA and the students as well as the purpose and motivation of the meditational strategies employed by TA in order to build the geological concept in the constructed 3-dimensional space. Through a series of increasingly complex gestures, the TA assists the students to construct the forensic concept of the imagined 3-D space, which can then be applied to a larger context. As the TA becomes more familiar with the students' meditational needs, the TA adapts teaching and gestural styles to meet their respective ZPDs (Vygotsky 1978). This study shows that in the laboratory setting language, gesture, and physical manipulation of the experimental object are all integral to the learning and demonstration of scientific concepts. Recognition of the gestural patterns of the students allows the TA the ability to dynamically assess the students understanding of a concept. Using the information from this example of student-TA interaction, a brief short course has been created to assist TAs in recognizing the mediational power as well as the assessment potential of gestural

  7. The use of a low-cost visible light 3D scanner to create virtual reality environment models of actors and objects

    NASA Astrophysics Data System (ADS)

    Straub, Jeremy

    2015-05-01

    A low-cost 3D scanner has been developed with a parts cost of approximately USD $5,000. This scanner uses visible light sensing to capture both structural as well as texture and color data of a subject. This paper discusses the use of this type of scanner to create 3D models for incorporation into a virtual reality environment. It describes the basic scanning process (which takes under a minute for a single scan), which can be repeated to collect multiple positions, if needed for actor model creation. The efficacy of visible light versus other scanner types is also discussed.

  8. Coupled object detection and tracking from static cameras and moving vehicles.

    PubMed

    Leibe, Bastian; Schindler, Konrad; Cornelis, Nico; Van Gool, Luc

    2008-10-01

    We present a novel approach for multi-object tracking which considers object detection and spacetime trajectory estimation as a coupled optimization problem. Our approach is formulated in a Minimum Description Length hypothesis selection framework, which allows it to recover from mismatches and temporarily lost tracks. Building upon a state-of-the-art object detector, it performs multiview/multicategory object recognition to detect cars and pedestrians in the input images. The 2D object detections are checked for their consistency with (automatically estimated) scene geometry and are converted to 3D observations which are accumulated in a world coordinate frame. A subsequent trajectory estimation module analyzes the resulting 3D observations to find phyically plausible spacetime trajectories. Tracking is achieved by performing model selection after every frame. At each time instant, our approach searches for the globally optimal set of spacetime trajectories which provides the best explanation for the current image and for all evidence collected so far, while satisfying the constraints that no two objects may occupy the same physical space, nor explain the same image pixels at any point in time. Successful trajectory hypotheses are then fed back to guide object detection in future frames. The optimization procedure is kept efficient throught incremental computation and conservative hypothesis pruning. We evaluate our approach on several challenging video sequences and demonstrate its performance on both a surveillance-type scenario and a scenario where the input videos are taken from inside a moving vehicle passing through crowded city areas.

  9. A statistical model of ChIA-PET data for accurate detection of chromatin 3D interactions

    PubMed Central

    Paulsen, Jonas; Rødland, Einar A.; Holden, Lars; Holden, Marit; Hovig, Eivind

    2014-01-01

    Identification of three-dimensional (3D) interactions between regulatory elements across the genome is crucial to unravel the complex regulatory machinery that orchestrates proliferation and differentiation of cells. ChIA-PET is a novel method to identify such interactions, where physical contacts between regions bound by a specific protein are quantified using next-generation sequencing. However, determining the significance of the observed interaction frequencies in such datasets is challenging, and few methods have been proposed. Despite the fact that regions that are close in linear genomic distance have a much higher tendency to interact by chance, no methods to date are capable of taking such dependency into account. Here, we propose a statistical model taking into account the genomic distance relationship, as well as the general propensity of anchors to be involved in contacts overall. Using both real and simulated data, we show that the previously proposed statistical test, based on Fisher's exact test, leads to invalid results when data are dependent on genomic distance. We also evaluate our method on previously validated cell-line specific and constitutive 3D interactions, and show that relevant interactions are significant, while avoiding over-estimating the significance of short nearby interactions. PMID:25114054

  10. Automatic Detection, Segmentation and Classification of Retinal Horizontal Neurons in Large-scale 3D Confocal Imagery

    SciTech Connect

    Karakaya, Mahmut; Kerekes, Ryan A; Gleason, Shaun Scott; Martins, Rodrigo; Dyer, Michael

    2011-01-01

    Automatic analysis of neuronal structure from wide-field-of-view 3D image stacks of retinal neurons is essential for statistically characterizing neuronal abnormalities that may be causally related to neural malfunctions or may be early indicators for a variety of neuropathies. In this paper, we study classification of neuron fields in large-scale 3D confocal image stacks, a challenging neurobiological problem because of the low spatial resolution imagery and presence of intertwined dendrites from different neurons. We present a fully automated, four-step processing approach for neuron classification with respect to the morphological structure of their dendrites. In our approach, we first localize each individual soma in the image by using morphological operators and active contours. By using each soma position as a seed point, we automatically determine an appropriate threshold to segment dendrites of each neuron. We then use skeletonization and network analysis to generate the morphological structures of segmented dendrites, and shape-based features are extracted from network representations of each neuron to characterize the neuron. Based on qualitative results and quantitative comparisons, we show that we are able to automatically compute relevant features that clearly distinguish between normal and abnormal cases for postnatal day 6 (P6) horizontal neurons.

  11. Three Dimensional (3D) Printing: A Straightforward, User-Friendly Protocol to Convert Virtual Chemical Models to Real-Life Objects

    ERIC Educational Resources Information Center

    Rossi, Sergio; Benaglia, Maurizio; Brenna, Davide; Porta, Riccardo; Orlandi, Manuel

    2015-01-01

    A simple procedure to convert protein data bank files (.pdb) into a stereolithography file (.stl) using VMD software (Virtual Molecular Dynamic) is reported. This tutorial allows generating, with a very simple protocol, three-dimensional customized structures that can be printed by a low-cost 3D-printer, and used for teaching chemical education…

  12. Impulse radar imaging system for concealed object detection

    NASA Astrophysics Data System (ADS)

    Podd, F. J. W.; David, M.; Iqbal, G.; Hussain, F.; Morris, D.; Osakue, E.; Yeow, Y.; Zahir, S.; Armitage, D. W.; Peyton, A. J.

    2013-10-01

    -to-noise parameter to determine how the frequencies contained in the echo dataset are normalised. The chosen image reconstruction algorithm is based on the back-projection method. The algorithm was implemented in MATLAB and uses a pre-calculated sensitivity matrix to increase the computation speed. The results include both 2D and 3D image datasets. The 3D datasets were obtained by scanning the dual sixteen element linear antenna array over the test object. The system has been tested on both humans and mannequin test objects. The front surface of an object placed on the human/mannequin torso is clearly visible, but its presence is also seen from a tell-tale imaging characteristic. This characteristic is caused by a reduction in the wave velocity as the electromagnetic radiation passes through the object, and manifests as an indentation in the reconstructed image that is readily identifiable. The prototype system has been shown to easily detect a 12 mm x 30 mm x70 mm plastic object concealed under clothing.

  13. Optimal detection of near-earth objects

    SciTech Connect

    Canavan, G.H.

    1997-09-01

    Improved technology and search strategies could significantly increase debris detection rates and tracking accuracies with modest investment. Improving the focal planes of current telescopes could significantly increase detection rates. For large systems, proportional increases in aperture area and array size are appropriate.

  14. Mixture of expert 3D massive-training ANNs for reduction of multiple types of false positives in CAD for detection of polyps in CT colonography.

    PubMed

    Suzuki, Kenji; Yoshida, Hiroyuki; Näppi, Janne; Armato, Samuel G; Dachman, Abraham H

    2008-02-01

    One of the major challenges in computer-aided detection (CAD) of polyps in CT colonography (CTC) is the reduction of false-positive detections (FPs) without a concomitant reduction in sensitivity. A large number of FPs is likely to confound the radiologist's task of image interpretation, lower the radiologist's efficiency, and cause radiologists to lose their confidence in CAD as a useful tool. Major sources of FPs generated by CAD schemes include haustral folds, residual stool, rectal tubes, the ileocecal valve, and extra-colonic structures such as the small bowel and stomach. Our purpose in this study was to develop a method for the removal of various types of FPs in CAD of polyps while maintaining a high sensitivity. To achieve this, we developed a "mixture of expert" three-dimensional (3D) massive-training artificial neural networks (MTANNs) consisting of four 3D MTANNs that were designed to differentiate between polyps and four categories of FPs: (1) rectal tubes, (2) stool with bubbles, (3) colonic walls with haustral folds, and (4) solid stool. Each expert 3D MTANN was trained with examples from a specific non-polyp category along with typical polyps. The four expert 3D MTANNs were combined with a mixing artificial neural network (ANN) such that different types of FPs could be removed. Our database consisted of 146 CTC datasets obtained from 73 patients whose colons were prepared by standard pre-colonoscopy cleansing. Each patient was scanned in both supine and prone positions. Radiologists established the locations of polyps through the use of optical-colonoscopy reports. Fifteen patients had 28 polyps, 15 of which were 5-9 mm and 13 were 10-25 mm in size. The CTC cases were subjected to our previously reported CAD method consisting of centerline-based extraction of the colon, shape-based detection of polyp candidates, and a Bayesian-ANN-based classification of polyps. The original CAD method yielded 96.4% (27/28) by-polyp sensitivity with an average of 3

  15. C2SM: a mobile system for detecting and 3D mapping of chemical, radiological, and nuclear contamination

    NASA Astrophysics Data System (ADS)

    Jasiobedzki, Piotr; Ng, Ho-Kong; Bondy, Michel; McDiarmid, C. H.

    2009-05-01

    CBRN Crime Scene Modeler (C2SM) is a prototype mobile CBRN mapping system for First Responders in events where Chemical, Biological, Radiological and Nuclear agents where used. The prototype operates on board a small robotic platform, increases situational awareness of the robot operator by providing geo-located images and data, and current robot location. The sensor suite includes stereo and high resolution cameras, a long wave infra red (thermal) camera and gamma and chemical detectors. The system collects and sends geo-located data to a remote command post in near real-time and automatically creates 3D photorealistic model augmented with CBRN measurements. Two prototypes have been successfully tested in field trials and a fully ruggedised commercial version is expected in 2010.

  16. Real time moving object detection using motor signal and depth map for robot car

    NASA Astrophysics Data System (ADS)

    Wu, Hao; Siu, Wan-Chi

    2013-12-01

    Moving object detection from a moving camera is a fundamental task in many applications. For the moving robot car vision, the background movement is 3D motion structure in nature. In this situation, the conventional moving object detection algorithm cannot be use to handle the 3D background modeling effectively and efficiently. In this paper, a novel scheme is proposed by utilizing the motor control signal and depth map obtained from a stereo camera to model the perspective transform matrix between different frames under a moving camera. In our approach, the coordinate relationship between frames during camera moving is modeled by a perspective transform matrix which is obtained by using current motor control signals and the pixel depth value. Hence, the relationship between a static background pixel and the moving foreground corresponding to the camera motion can be related by a perspective matrix. To enhance the robustness of classification, we allowed a tolerance range during the perspective transform matrix prediction and used multi-reference frames to classify the pixel on current frame. The proposed scheme has been found to be able to detect moving objects for our moving robot car efficiently. Different from conventional approaches, our method can model the moving background in 3D structure, without online model training. More importantly, the computational complexity and memory requirement are low making it possible to implement this scheme in real-time, which is even valuable for a robot vision system.

  17. Proton-detected 3D 1H/13C/1H correlation experiment for structural analysis in rigid solids under ultrafast-MAS above 60 kHz

    NASA Astrophysics Data System (ADS)

    Zhang, Rongchun; Nishiyama, Yusuke; Ramamoorthy, Ayyalusamy

    2015-10-01

    A proton-detected 3D 1H/13C/1H chemical shift correlation experiment is proposed for the assignment of chemical shift resonances, identification of 13C-1H connectivities, and proximities of 13C-1H and 1H-1H nuclei under ultrafast magic-angle-spinning (ultrafast-MAS) conditions. Ultrafast-MAS is used to suppress all anisotropic interactions including 1H-1H dipolar couplings, while the finite-pulse radio frequency driven dipolar recoupling (fp-RFDR) pulse sequence is used to recouple dipolar couplings among protons and the insensitive nuclei enhanced by polarization transfer technique is used to transfer magnetization between heteronuclear spins. The 3D experiment eliminates signals from non-carbon-bonded protons and non-proton-bonded carbons to enhance spectral resolution. The 2D (F1/F3) 1H/1H and 2D 13C/1H (F2/F3) chemical shift correlation spectra extracted from the 3D spectrum enable the identification of 1H-1H proximity and 13C-1H connectivity. In addition, the 2D (F1/F2) 1H/13C chemical shift correlation spectrum, incorporated with proton magnetization exchange via the fp-RFDR recoupling of 1H-1H dipolar couplings, enables the measurement of proximities between 13C and even the remote non-carbon-bonded protons. The 3D experiment also gives three-spin proximities of 1H-1H-13C chains. Experimental results obtained from powder samples of L-alanine and L-histidine ṡ H2O ṡ HCl demonstrate the efficiency of the 3D experiment.

  18. Proton-detected 3D (1)H/(13)C/(1)H correlation experiment for structural analysis in rigid solids under ultrafast-MAS above 60 kHz.

    PubMed

    Zhang, Rongchun; Nishiyama, Yusuke; Ramamoorthy, Ayyalusamy

    2015-10-28

    A proton-detected 3D (1)H/(13)C/(1)H chemical shift correlation experiment is proposed for the assignment of chemical shift resonances, identification of (13)C-(1)H connectivities, and proximities of (13)C-(1)H and (1)H-(1)H nuclei under ultrafast magic-angle-spinning (ultrafast-MAS) conditions. Ultrafast-MAS is used to suppress all anisotropic interactions including (1)H-(1)H dipolar couplings, while the finite-pulse radio frequency driven dipolar recoupling (fp-RFDR) pulse sequence is used to recouple dipolar couplings among protons and the insensitive nuclei enhanced by polarization transfer technique is used to transfer magnetization between heteronuclear spins. The 3D experiment eliminates signals from non-carbon-bonded protons and non-proton-bonded carbons to enhance spectral resolution. The 2D (F1/F3) (1)H/(1)H and 2D (13)C/(1)H (F2/F3) chemical shift correlation spectra extracted from the 3D spectrum enable the identification of (1)H-(1)H proximity and (13)C-(1)H connectivity. In addition, the 2D (F1/F2) (1)H/(13)C chemical shift correlation spectrum, incorporated with proton magnetization exchange via the fp-RFDR recoupling of (1)H-(1)H dipolar couplings, enables the measurement of proximities between (13)C and even the remote non-carbon-bonded protons. The 3D experiment also gives three-spin proximities of (1)H-(1)H-(13)C chains. Experimental results obtained from powder samples of L-alanine and L-histidine ⋅ H2O ⋅ HCl demonstrate the efficiency of the 3D experiment.

  19. Sensor feature fusion for detecting buried objects

    SciTech Connect

    Clark, G.A.; Sengupta, S.K.; Sherwood, R.J.; Hernandez, J.E.; Buhl, M.R.; Schaich, P.C.; Kane, R.J.; Barth, M.J.; DelGrande, N.K.

    1993-04-01

    Given multiple registered images of the earth`s surface from dual-band sensors, our system fuses information from the sensors to reduce the effects of clutter and improve the ability to detect buried or surface target sites. The sensor suite currently includes two sensors (5 micron and 10 micron wavelengths) and one ground penetrating radar (GPR) of the wide-band pulsed synthetic aperture type. We use a supervised teaming pattern recognition approach to detect metal and plastic land mines buried in soil. The overall process consists of four main parts: Preprocessing, feature extraction, feature selection, and classification. These parts are used in a two step process to classify a subimage. Thee first step, referred to as feature selection, determines the features of sub-images which result in the greatest separability among the classes. The second step, image labeling, uses the selected features and the decisions from a pattern classifier to label the regions in the image which are likely to correspond to buried mines. We extract features from the images, and use feature selection algorithms to select only the most important features according to their contribution to correct detections. This allows us to save computational complexity and determine which of the sensors add value to the detection system. The most important features from the various sensors are fused using supervised teaming pattern classifiers (including neural networks). We present results of experiments to detect buried land mines from real data, and evaluate the usefulness of fusing feature information from multiple sensor types, including dual-band infrared and ground penetrating radar. The novelty of the work lies mostly in the combination of the algorithms and their application to the very important and currently unsolved operational problem of detecting buried land mines from an airborne standoff platform.

  20. Detection of Leptomeningeal Metastasis by Contrast-Enhanced 3D T1-SPACE: Comparison with 2D FLAIR and Contrast-Enhanced 2D T1-Weighted Images

    PubMed Central

    Gil, Bomi; Hwang, Eo-Jin; Lee, Song; Jang, Jinhee; Jung, So-Lyung; Ahn, Kook-Jin; Kim, Bum-soo

    2016-01-01

    Introduction To compare the diagnostic accuracy of contrast-enhanced 3D(dimensional) T1-weighted sampling perfection with application-optimized contrasts by using different flip angle evolutions (T1-SPACE), 2D fluid attenuated inversion recovery (FLAIR) images and 2D contrast-enhanced T1-weighted image in detection of leptomeningeal metastasis except for invasive procedures such as a CSF tapping. Materials and Methods Three groups of patients were included retrospectively for 9 months (from 2013-04-01 to 2013-12-31). Group 1 patients with positive malignant cells in CSF cytology (n = 22); group 2, stroke patients with steno-occlusion in ICA or MCA (n = 16); and group 3, patients with negative results on MRI, whose symptom were dizziness or headache (n = 25). A total of 63 sets of MR images are separately collected and randomly arranged: (1) CE 3D T1-SPACE; (2) 2D FLAIR; and (3) CE T1-GRE using a 3-Tesla MR system. A faculty neuroradiologist with 8-year-experience and another 2nd grade trainee in radiology reviewed each MR image- blinded by the results of CSF cytology and coded their observations as positives or negatives of leptomeningeal metastasis. The CSF cytology result was considered as a gold standard. Sensitivity and specificity of each MR images were calculated. Diagnostic accuracy was compared using a McNemar’s test. A Cohen's kappa analysis was performed to assess inter-observer agreements. Results Diagnostic accuracy was not different between 3D T1-SPACE and CSF cytology by both raters. However, the accuracy test of 2D FLAIR and 2D contrast-enhanced T1-weighted GRE was inconsistent by the two raters. The Kappa statistic results were 0.657 (3D T1-SPACE), 0.420 (2D FLAIR), and 0.160 (2D contrast-enhanced T1-weighted GRE). The 3D T1-SPACE images showed the highest inter-observer agreements between the raters. Conclusions Compared to 2D FLAIR and 2D contrast-enhanced T1-weighted GRE, contrast-enhanced 3D T1 SPACE showed a better detection rate of

  1. Detecting concealed objects at a checkpoint

    DOEpatents

    McMakin, Douglas L.; Hall, Thomas E.; Sheen, David M.; Severtsen, Ronald H.

    2008-07-29

    Disclosed are systems, methods, devices, and apparatus to interrogate a clothed individual with electromagnetic radiation to determine if a concealed object is being carried. This determination includes establishing data corresponding to an image of the individual with a pair of opposed, semi-cylindrical array panels each configured to interrogate the individual with electromagnetic radiation in the 200 MHz to 1 THz range.

  2. Point pattern match-based change detection in a constellation of previously detected objects

    DOEpatents

    Paglieroni, David W.

    2016-06-07

    A method and system is provided that applies attribute- and topology-based change detection to objects that were detected on previous scans of a medium. The attributes capture properties or characteristics of the previously detected objects, such as location, time of detection, detection strength, size, elongation, orientation, etc. The locations define a three-dimensional network topology forming a constellation of previously detected objects. The change detection system stores attributes of the previously detected objects in a constellation database. The change detection system detects changes by comparing the attributes and topological consistency of newly detected objects encountered during a new scan of the medium to previously detected objects in the constellation database. The change detection system may receive the attributes of the newly detected objects as the objects are detected by an object detection system in real time.

  3. Guided-wave-based damage detection in a composite T-joint using 3D scanning laser Doppler vibrometer

    NASA Astrophysics Data System (ADS)

    Kolappan Geetha, Ganesh; Roy Mahapatra, D.; Srinivasan, Gopalakrishnan

    2012-04-01

    Composite T-joints are commonly used in modern composite airframe, pressure vessels and piping structures, mainly to increase the bending strength of the joint and prevents buckling of plates and shells, and in multi-cell thin-walled structures. Here we report a detailed study on the propagation of guided ultrasonic wave modes in a composite T-joint and their interactions with delamination in the co-cured co-bonded flange. A well designed guiding path is employed wherein the waves undergo a two step mode conversion process, one is due to the web and joint filler on the back face of the flange and the other is due to the delamination edges close to underneath the accessible surface of the flange. A 3D Laser Doppler Vibrometer is used to obtain the three components of surface displacements/velocities of the accessible face of the flange of the T-joint. The waves are launched by a piezo ceramic wafer bonded on to the back surface of the flange. What is novel in the proposed method is that the location of any change in material/geometric properties can be traced by computing a frequency domain power flow along a scan line. The scan line can be chosen over a grid either during scan or during post-processing of the scan data off-line. The proposed technique eliminates the necessity of baseline data and disassembly of structure for structural interrogation.

  4. Detection and Classification of Pole-Like Objects from Mobile Mapping Data

    NASA Astrophysics Data System (ADS)

    Fukano, K.; Masuda, H.

    2015-08-01

    Laser scanners on a vehicle-based mobile mapping system can capture 3D point-clouds of roads and roadside objects. Since roadside objects have to be maintained periodically, their 3D models are useful for planning maintenance tasks. In our previous work, we proposed a method for detecting cylindrical poles and planar plates in a point-cloud. However, it is often required to further classify pole-like objects into utility poles, streetlights, traffic signals and signs, which are managed by different organizations. In addition, our previous method may fail to extract low pole-like objects, which are often observed in urban residential areas. In this paper, we propose new methods for extracting and classifying pole-like objects. In our method, we robustly extract a wide variety of poles by converting point-clouds into wireframe models and calculating cross-sections between wireframe models and horizontal cutting planes. For classifying pole-like objects, we subdivide a pole-like object into five subsets by extracting poles and planes, and calculate feature values of each subset. Then we apply a supervised machine learning method using feature variables of subsets. In our experiments, our method could achieve excellent results for detection and classification of pole-like objects.

  5. Metrological characterization of 3D imaging devices

    NASA Astrophysics Data System (ADS)

    Guidi, G.

    2013-04-01

    Manufacturers often express the performance of a 3D imaging device in various non-uniform ways for the lack of internationally recognized standard requirements for metrological parameters able to identify the capability of capturing a real scene. For this reason several national and international organizations in the last ten years have been developing protocols for verifying such performance. Ranging from VDI/VDE 2634, published by the Association of German Engineers and oriented to the world of mechanical 3D measurements (triangulation-based devices), to the ASTM technical committee E57, working also on laser systems based on direct range detection (TOF, Phase Shift, FM-CW, flash LADAR), this paper shows the state of the art about the characterization of active range devices, with special emphasis on measurement uncertainty, accuracy and resolution. Most of these