An artificial intelligence based improved classification of two-phase flow patterns with feature extracted from acquired images.

PubMed

Shanthi, C; Pappa, N

2017-05-01

Flow pattern recognition is necessary to select design equations for finding operating details of the process and to perform computational simulations. Visual image processing can be used to automate the interpretation of patterns in two-phase flow. In this paper, an attempt has been made to improve the classification accuracy of the flow pattern of gas/ liquid two- phase flow using fuzzy logic and Support Vector Machine (SVM) with Principal Component Analysis (PCA). The videos of six different types of flow patterns namely, annular flow, bubble flow, churn flow, plug flow, slug flow and stratified flow are recorded for a period and converted to 2D images for processing. The textural and shape features extracted using image processing are applied as inputs to various classification schemes namely fuzzy logic, SVM and SVM with PCA in order to identify the type of flow pattern. The results obtained are compared and it is observed that SVM with features reduced using PCA gives the better classification accuracy and computationally less intensive than other two existing schemes. This study results cover industrial application needs including oil and gas and any other gas-liquid two-phase flows. Copyright © 2017 ISA. Published by Elsevier Ltd. All rights reserved.

Automatic Assessment and Reduction of Noise using Edge Pattern Analysis in Non-Linear Image Enhancement

NASA Technical Reports Server (NTRS)

Jobson, Daniel J.; Rahman, Zia-Ur; Woodell, Glenn A.; Hines, Glenn D.

2004-01-01

Noise is the primary visibility limit in the process of non-linear image enhancement, and is no longer a statistically stable additive noise in the post-enhancement image. Therefore novel approaches are needed to both assess and reduce spatially variable noise at this stage in overall image processing. Here we will examine the use of edge pattern analysis both for automatic assessment of spatially variable noise and as a foundation for new noise reduction methods.

Dietary Assessment on a Mobile Phone Using Image Processing and Pattern Recognition Techniques: Algorithm Design and System Prototyping

PubMed Central

Probst, Yasmine; Nguyen, Duc Thanh; Tran, Minh Khoi; Li, Wanqing

2015-01-01

Dietary assessment, while traditionally based on pen-and-paper, is rapidly moving towards automatic approaches. This study describes an Australian automatic food record method and its prototype for dietary assessment via the use of a mobile phone and techniques of image processing and pattern recognition. Common visual features including scale invariant feature transformation (SIFT), local binary patterns (LBP), and colour are used for describing food images. The popular bag-of-words (BoW) model is employed for recognizing the images taken by a mobile phone for dietary assessment. Technical details are provided together with discussions on the issues and future work. PMID:26225994

Grid point extraction and coding for structured light system

NASA Astrophysics Data System (ADS)

Song, Zhan; Chung, Ronald

2011-09-01

A structured light system simplifies three-dimensional reconstruction by illuminating a specially designed pattern to the target object, thereby generating a distinct texture on it for imaging and further processing. Success of the system hinges upon what features are to be coded in the projected pattern, extracted in the captured image, and matched between the projector's display panel and the camera's image plane. The codes have to be such that they are largely preserved in the image data upon illumination from the projector, reflection from the target object, and projective distortion in the imaging process. The features also need to be reliably extracted in the image domain. In this article, a two-dimensional pseudorandom pattern consisting of rhombic color elements is proposed, and the grid points between the pattern elements are chosen as the feature points. We describe how a type classification of the grid points plus the pseudorandomness of the projected pattern can equip each grid point with a unique label that is preserved in the captured image. We also present a grid point detector that extracts the grid points without the need of segmenting the pattern elements, and that localizes the grid points in subpixel accuracy. Extensive experiments are presented to illustrate that, with the proposed pattern feature definition and feature detector, more features points in higher accuracy can be reconstructed in comparison with the existing pseudorandomly encoded structured light systems.

Image processing and 3D visualization in the interpretation of patterned injury of the skin

NASA Astrophysics Data System (ADS)

Oliver, William R.; Altschuler, Bruce R.

1995-09-01

The use of image processing is becoming increasingly important in the evaluation of violent crime. While much work has been done in the use of these techniques for forensic purposes outside of forensic pathology, its use in the pathologic examination of wounding has been limited. We are investigating the use of image processing in the analysis of patterned injuries and tissue damage. Our interests are currently concentrated on 1) the use of image processing techniques to aid the investigator in observing and evaluating patterned injuries in photographs, 2) measurement of the 3D shape characteristics of surface lesions, and 3) correlation of patterned injuries with deep tissue injury as a problem in 3D visualization. We are beginning investigations in data-acquisition problems for performing 3D scene reconstructions from the pathology perspective of correlating tissue injury to scene features and trace evidence localization. Our primary tool for correlation of surface injuries with deep tissue injuries has been the comparison of processed surface injury photographs with 3D reconstructions from antemortem CT and MRI data. We have developed a prototype robot for the acquisition of 3D wound and scene data.

Method and apparatus for optical encoding with compressible imaging

NASA Technical Reports Server (NTRS)

Leviton, Douglas B. (Inventor)

2006-01-01

The present invention presents an optical encoder with increased conversion rates. Improvement in the conversion rate is a result of combining changes in the pattern recognition encoder's scale pattern with an image sensor readout technique which takes full advantage of those changes, and lends itself to operation by modern, high-speed, ultra-compact microprocessors and digital signal processors (DSP) or field programmable gate array (FPGA) logic elements which can process encoder scale images at the highest speeds. Through these improvements, all three components of conversion time (reciprocal conversion rate)--namely exposure time, image readout time, and image processing time--are minimized.

Pixelated camouflage patterns from the perspective of hyperspectral imaging

NASA Astrophysics Data System (ADS)

Racek, František; Jobánek, Adam; Baláž, Teodor; Krejčí, Jaroslav

2016-10-01

Pixelated camouflage patterns fulfill the role of both principles the matching and the disrupting that are exploited for blending the target into the background. It means that pixelated pattern should respect natural background in spectral and spatial characteristics embodied in micro and macro patterns. The HS imaging plays the similar, however the reverse role in the field of reconnaissance systems. The HS camera fundamentally records and extracts both the spectral and spatial information belonging to the recorded scenery. Therefore, the article deals with problems of hyperspectral (HS) imaging and subsequent processing of HS images of pixelated camouflage patterns which are among others characterized by their specific spatial frequency heterogeneity.

Introduction to computer image processing

NASA Technical Reports Server (NTRS)

Moik, J. G.

1973-01-01

Theoretical backgrounds and digital techniques for a class of image processing problems are presented. Image formation in the context of linear system theory, image evaluation, noise characteristics, mathematical operations on image and their implementation are discussed. Various techniques for image restoration and image enhancement are presented. Methods for object extraction and the problem of pictorial pattern recognition and classification are discussed.

Automated characterisation of ultrasound images of ovarian tumours: the diagnostic accuracy of a support vector machine and image processing with a local binary pattern operator.

PubMed

Khazendar, S; Sayasneh, A; Al-Assam, H; Du, H; Kaijser, J; Ferrara, L; Timmerman, D; Jassim, S; Bourne, T

2015-01-01

Preoperative characterisation of ovarian masses into benign or malignant is of paramount importance to optimise patient management. In this study, we developed and validated a computerised model to characterise ovarian masses as benign or malignant. Transvaginal 2D B mode static ultrasound images of 187 ovarian masses with known histological diagnosis were included. Images were first pre-processed and enhanced, and Local Binary Pattern Histograms were then extracted from 2 × 2 blocks of each image. A Support Vector Machine (SVM) was trained using stratified cross validation with randomised sampling. The process was repeated 15 times and in each round 100 images were randomly selected. The SVM classified the original non-treated static images as benign or malignant masses with an average accuracy of 0.62 (95% CI: 0.59-0.65). This performance significantly improved to an average accuracy of 0.77 (95% CI: 0.75-0.79) when images were pre-processed, enhanced and treated with a Local Binary Pattern operator (mean difference 0.15: 95% 0.11-0.19, p < 0.0001, two-tailed t test). We have shown that an SVM can classify static 2D B mode ultrasound images of ovarian masses into benign and malignant categories. The accuracy improves if texture related LBP features extracted from the images are considered.

Using artificial intelligence to improve identification of nanofluid gas-liquid two-phase flow pattern in mini-channel

NASA Astrophysics Data System (ADS)

Xiao, Jian; Luo, Xiaoping; Feng, Zhenfei; Zhang, Jinxin

2018-01-01

This work combines fuzzy logic and a support vector machine (SVM) with a principal component analysis (PCA) to create an artificial-intelligence system that identifies nanofluid gas-liquid two-phase flow states in a vertical mini-channel. Flow-pattern recognition requires finding the operational details of the process and doing computer simulations and image processing can be used to automate the description of flow patterns in nanofluid gas-liquid two-phase flow. This work uses fuzzy logic and a SVM with PCA to improve the accuracy with which the flow pattern of a nanofluid gas-liquid two-phase flow is identified. To acquire images of nanofluid gas-liquid two-phase flow patterns of flow boiling, a high-speed digital camera was used to record four different types of flow-pattern images, namely annular flow, bubbly flow, churn flow, and slug flow. The textural features extracted by processing the images of nanofluid gas-liquid two-phase flow patterns are used as inputs to various identification schemes such as fuzzy logic, SVM, and SVM with PCA to identify the type of flow pattern. The results indicate that the SVM with reduced characteristics of PCA provides the best identification accuracy and requires less calculation time than the other two schemes. The data reported herein should be very useful for the design and operation of industrial applications.

Image-plane processing of visual information

NASA Technical Reports Server (NTRS)

Huck, F. O.; Fales, C. L.; Park, S. K.; Samms, R. W.

1984-01-01

Shannon's theory of information is used to optimize the optical design of sensor-array imaging systems which use neighborhood image-plane signal processing for enhancing edges and compressing dynamic range during image formation. The resultant edge-enhancement, or band-pass-filter, response is found to be very similar to that of human vision. Comparisons of traits in human vision with results from information theory suggest that: (1) Image-plane processing, like preprocessing in human vision, can improve visual information acquisition for pattern recognition when resolving power, sensitivity, and dynamic range are constrained. Improvements include reduced sensitivity to changes in lighter levels, reduced signal dynamic range, reduced data transmission and processing, and reduced aliasing and photosensor noise degradation. (2) Information content can be an appropriate figure of merit for optimizing the optical design of imaging systems when visual information is acquired for pattern recognition. The design trade-offs involve spatial response, sensitivity, and sampling interval.

Image processing applications: From particle physics to society

NASA Astrophysics Data System (ADS)

Sotiropoulou, C.-L.; Luciano, P.; Gkaitatzis, S.; Citraro, S.; Giannetti, P.; Dell'Orso, M.

2017-01-01

We present an embedded system for extremely efficient real-time pattern recognition execution, enabling technological advancements with both scientific and social impact. It is a compact, fast, low consumption processing unit (PU) based on a combination of Field Programmable Gate Arrays (FPGAs) and the full custom associative memory chip. The PU has been developed for real time tracking in particle physics experiments, but delivers flexible features for potential application in a wide range of fields. It has been proposed to be used in accelerated pattern matching execution for Magnetic Resonance Fingerprinting (biomedical applications), in real time detection of space debris trails in astronomical images (space applications) and in brain emulation for image processing (cognitive image processing). We illustrate the potentiality of the PU for the new applications.

Optical Processing of Speckle Images with Bacteriorhodopsin for Pattern Recognition

NASA Technical Reports Server (NTRS)

Downie, John D.; Tucker, Deanne (Technical Monitor)

1994-01-01

Logarithmic processing of images with multiplicative noise characteristics can be utilized to transform the image into one with an additive noise distribution. This simplifies subsequent image processing steps for applications such as image restoration or correlation for pattern recognition. One particularly common form of multiplicative noise is speckle, for which the logarithmic operation not only produces additive noise, but also makes it of constant variance (signal-independent). We examine the optical transmission properties of some bacteriorhodopsin films here and find them well suited to implement such a pointwise logarithmic transformation optically in a parallel fashion. We present experimental results of the optical conversion of speckle images into transformed images with additive, signal-independent noise statistics using the real-time photochromic properties of bacteriorhodopsin. We provide an example of improved correlation performance in terms of correlation peak signal-to-noise for such a transformed speckle image.

Image processing and pattern recognition with CVIPtools MATLAB toolbox: automatic creation of masks for veterinary thermographic images

NASA Astrophysics Data System (ADS)

Mishra, Deependra K.; Umbaugh, Scott E.; Lama, Norsang; Dahal, Rohini; Marino, Dominic J.; Sackman, Joseph

2016-09-01

CVIPtools is a software package for the exploration of computer vision and image processing developed in the Computer Vision and Image Processing Laboratory at Southern Illinois University Edwardsville. CVIPtools is available in three variants - a) CVIPtools Graphical User Interface, b) CVIPtools C library and c) CVIPtools MATLAB toolbox, which makes it accessible to a variety of different users. It offers students, faculty, researchers and any user a free and easy way to explore computer vision and image processing techniques. Many functions have been implemented and are updated on a regular basis, the library has reached a level of sophistication that makes it suitable for both educational and research purposes. In this paper, the detail list of the functions available in the CVIPtools MATLAB toolbox are presented and how these functions can be used in image analysis and computer vision applications. The CVIPtools MATLAB toolbox allows the user to gain practical experience to better understand underlying theoretical problems in image processing and pattern recognition. As an example application, the algorithm for the automatic creation of masks for veterinary thermographic images is presented.

Hybrid overlay metrology for high order correction by using CDSEM

NASA Astrophysics Data System (ADS)

Leray, Philippe; Halder, Sandip; Lorusso, Gian; Baudemprez, Bart; Inoue, Osamu; Okagawa, Yutaka

2016-03-01

Overlay control has become one of the most critical issues for semiconductor manufacturing. Advanced lithographic scanners use high-order corrections or correction per exposure to reduce the residual overlay. It is not enough in traditional feedback of overlay measurement by using ADI wafer because overlay error depends on other process (etching process and film stress, etc.). It needs high accuracy overlay measurement by using AEI wafer. WIS (Wafer Induced Shift) is the main issue for optical overlay, IBO (Image Based Overlay) and DBO (Diffraction Based Overlay). We design dedicated SEM overlay targets for dual damascene process of N10 by i-ArF multi-patterning. The pattern is same as device-pattern locally. Optical overlay tools select segmented pattern to reduce the WIS. However segmentation has limit, especially the via-pattern, for keeping the sensitivity and accuracy. We evaluate difference between the viapattern and relaxed pitch gratings which are similar to optical overlay target at AEI. CDSEM can estimate asymmetry property of target from image of pattern edge. CDSEM can estimate asymmetry property of target from image of pattern edge. We will compare full map of SEM overlay to full map of optical overlay for high order correction ( correctables and residual fingerprints).

Automated characterisation of ultrasound images of ovarian tumours: the diagnostic accuracy of a support vector machine and image processing with a local binary pattern operator

PubMed Central

Khazendar, S.; Sayasneh, A.; Al-Assam, H.; Du, H.; Kaijser, J.; Ferrara, L.; Timmerman, D.; Jassim, S.; Bourne, T.

2015-01-01

Introduction: Preoperative characterisation of ovarian masses into benign or malignant is of paramount importance to optimise patient management. Objectives: In this study, we developed and validated a computerised model to characterise ovarian masses as benign or malignant. Materials and methods: Transvaginal 2D B mode static ultrasound images of 187 ovarian masses with known histological diagnosis were included. Images were first pre-processed and enhanced, and Local Binary Pattern Histograms were then extracted from 2 × 2 blocks of each image. A Support Vector Machine (SVM) was trained using stratified cross validation with randomised sampling. The process was repeated 15 times and in each round 100 images were randomly selected. Results: The SVM classified the original non-treated static images as benign or malignant masses with an average accuracy of 0.62 (95% CI: 0.59-0.65). This performance significantly improved to an average accuracy of 0.77 (95% CI: 0.75-0.79) when images were pre-processed, enhanced and treated with a Local Binary Pattern operator (mean difference 0.15: 95% 0.11-0.19, p < 0.0001, two-tailed t test). Conclusion: We have shown that an SVM can classify static 2D B mode ultrasound images of ovarian masses into benign and malignant categories. The accuracy improves if texture related LBP features extracted from the images are considered. PMID:25897367

A fast, robust pattern recognition asystem for low light level image registration and its application to retinal imaging

NASA Astrophysics Data System (ADS)

Wade, Alex Robert; Fitzke, Frederick W.

1998-08-01

We describe an image processing system which we have developed to align autofluorescence and high-magnification images taken with a laser scanning ophthalmoscope. The low signal to noise ratio of these images makes pattern recognition a non-trivial task. However, once n images are aligned and averaged, the noise levels drop by a factor of n and the image quality is improved. We include examples of autofluorescence images and images of the cone photoreceptor mosaic obtained using this system.

Visual pattern image sequence coding

NASA Technical Reports Server (NTRS)

Silsbee, Peter; Bovik, Alan C.; Chen, Dapang

1990-01-01

The visual pattern image coding (VPIC) configurable digital image-coding process is capable of coding with visual fidelity comparable to the best available techniques, at compressions which (at 30-40:1) exceed all other technologies. These capabilities are associated with unprecedented coding efficiencies; coding and decoding operations are entirely linear with respect to image size and entail a complexity that is 1-2 orders of magnitude faster than any previous high-compression technique. The visual pattern image sequence coding to which attention is presently given exploits all the advantages of the static VPIC in the reduction of information from an additional, temporal dimension, to achieve unprecedented image sequence coding performance.

Self-Organization of Spatio-Temporal Hierarchy via Learning of Dynamic Visual Image Patterns on Action Sequences

PubMed Central

Jung, Minju; Hwang, Jungsik; Tani, Jun

2015-01-01

It is well known that the visual cortex efficiently processes high-dimensional spatial information by using a hierarchical structure. Recently, computational models that were inspired by the spatial hierarchy of the visual cortex have shown remarkable performance in image recognition. Up to now, however, most biological and computational modeling studies have mainly focused on the spatial domain and do not discuss temporal domain processing of the visual cortex. Several studies on the visual cortex and other brain areas associated with motor control support that the brain also uses its hierarchical structure as a processing mechanism for temporal information. Based on the success of previous computational models using spatial hierarchy and temporal hierarchy observed in the brain, the current report introduces a novel neural network model for the recognition of dynamic visual image patterns based solely on the learning of exemplars. This model is characterized by the application of both spatial and temporal constraints on local neural activities, resulting in the self-organization of a spatio-temporal hierarchy necessary for the recognition of complex dynamic visual image patterns. The evaluation with the Weizmann dataset in recognition of a set of prototypical human movement patterns showed that the proposed model is significantly robust in recognizing dynamically occluded visual patterns compared to other baseline models. Furthermore, an evaluation test for the recognition of concatenated sequences of those prototypical movement patterns indicated that the model is endowed with a remarkable capability for the contextual recognition of long-range dynamic visual image patterns. PMID:26147887

Self-Organization of Spatio-Temporal Hierarchy via Learning of Dynamic Visual Image Patterns on Action Sequences.

PubMed

Jung, Minju; Hwang, Jungsik; Tani, Jun

2015-01-01

It is well known that the visual cortex efficiently processes high-dimensional spatial information by using a hierarchical structure. Recently, computational models that were inspired by the spatial hierarchy of the visual cortex have shown remarkable performance in image recognition. Up to now, however, most biological and computational modeling studies have mainly focused on the spatial domain and do not discuss temporal domain processing of the visual cortex. Several studies on the visual cortex and other brain areas associated with motor control support that the brain also uses its hierarchical structure as a processing mechanism for temporal information. Based on the success of previous computational models using spatial hierarchy and temporal hierarchy observed in the brain, the current report introduces a novel neural network model for the recognition of dynamic visual image patterns based solely on the learning of exemplars. This model is characterized by the application of both spatial and temporal constraints on local neural activities, resulting in the self-organization of a spatio-temporal hierarchy necessary for the recognition of complex dynamic visual image patterns. The evaluation with the Weizmann dataset in recognition of a set of prototypical human movement patterns showed that the proposed model is significantly robust in recognizing dynamically occluded visual patterns compared to other baseline models. Furthermore, an evaluation test for the recognition of concatenated sequences of those prototypical movement patterns indicated that the model is endowed with a remarkable capability for the contextual recognition of long-range dynamic visual image patterns.

Automated processing of shoeprint images based on the Fourier transform for use in forensic science.

PubMed

de Chazal, Philip; Flynn, John; Reilly, Richard B

2005-03-01

The development of a system for automatically sorting a database of shoeprint images based on the outsole pattern in response to a reference shoeprint image is presented. The database images are sorted so that those from the same pattern group as the reference shoeprint are likely to be at the start of the list. A database of 476 complete shoeprint images belonging to 140 pattern groups was established with each group containing two or more examples. A panel of human observers performed the grouping of the images into pattern categories. Tests of the system using the database showed that the first-ranked database image belongs to the same pattern category as the reference image 65 percent of the time and that a correct match appears within the first 5 percent of the sorted images 87 percent of the time. The system has translational and rotational invariance so that the spatial positioning of the reference shoeprint images does not have to correspond with the spatial positioning of the shoeprint images of the database. The performance of the system for matching partial-prints was also determined.

Bio-inspired approach to multistage image processing

NASA Astrophysics Data System (ADS)

Timchenko, Leonid I.; Pavlov, Sergii V.; Kokryatskaya, Natalia I.; Poplavska, Anna A.; Kobylyanska, Iryna M.; Burdenyuk, Iryna I.; Wójcik, Waldemar; Uvaysova, Svetlana; Orazbekov, Zhassulan; Kashaganova, Gulzhan

2017-08-01

Multistage integration of visual information in the brain allows people to respond quickly to most significant stimuli while preserving the ability to recognize small details in the image. Implementation of this principle in technical systems can lead to more efficient processing procedures. The multistage approach to image processing, described in this paper, comprises main types of cortical multistage convergence. One of these types occurs within each visual pathway and the other between the pathways. This approach maps input images into a flexible hierarchy which reflects the complexity of the image data. The procedures of temporal image decomposition and hierarchy formation are described in mathematical terms. The multistage system highlights spatial regularities, which are passed through a number of transformational levels to generate a coded representation of the image which encapsulates, in a computer manner, structure on different hierarchical levels in the image. At each processing stage a single output result is computed to allow a very quick response from the system. The result is represented as an activity pattern, which can be compared with previously computed patterns on the basis of the closest match.

Vicinal light inspection of translucent materials

DOEpatents

Burns, Geroge R [Albuquerque, NM; Yang, Pin [Albuquerque, NM

2010-01-19

The present invention includes methods and apparatus for inspecting vicinally illuminated non-patterned areas of translucent materials. An initial image of the material is received. A second image is received following a relative translation between the material being inspected and a device generating the images. Each vicinally illuminated image includes a portion having optimal illumination, that can be extracted and stored in a composite image of the non-patterned area. The composite image includes aligned portions of the extracted image portions, and provides a composite having optimal illumination over a non-patterned area of the material to be inspected. The composite image can be processed by enhancement and object detection algorithms, to determine the presence of, and characterize any inhomogeneities present in the material.

Convolution Comparison Pattern: An Efficient Local Image Descriptor for Fingerprint Liveness Detection

PubMed Central

Gottschlich, Carsten

2016-01-01

We present a new type of local image descriptor which yields binary patterns from small image patches. For the application to fingerprint liveness detection, we achieve rotation invariant image patches by taking the fingerprint segmentation and orientation field into account. We compute the discrete cosine transform (DCT) for these rotation invariant patches and attain binary patterns by comparing pairs of two DCT coefficients. These patterns are summarized into one or more histograms per image. Each histogram comprises the relative frequencies of pattern occurrences. Multiple histograms are concatenated and the resulting feature vector is used for image classification. We name this novel type of descriptor convolution comparison pattern (CCP). Experimental results show the usefulness of the proposed CCP descriptor for fingerprint liveness detection. CCP outperforms other local image descriptors such as LBP, LPQ and WLD on the LivDet 2013 benchmark. The CCP descriptor is a general type of local image descriptor which we expect to prove useful in areas beyond fingerprint liveness detection such as biological and medical image processing, texture recognition, face recognition and iris recognition, liveness detection for face and iris images, and machine vision for surface inspection and material classification. PMID:26844544

Fuzzy tree automata and syntactic pattern recognition.

PubMed

Lee, E T

1982-04-01

An approach of representing patterns by trees and processing these trees by fuzzy tree automata is described. Fuzzy tree automata are defined and investigated. The results include that the class of fuzzy root-to-frontier recognizable ¿-trees is closed under intersection, union, and complementation. Thus, the class of fuzzy root-to-frontier recognizable ¿-trees forms a Boolean algebra. Fuzzy tree automata are applied to processing fuzzy tree representation of patterns based on syntactic pattern recognition. The grade of acceptance is defined and investigated. Quantitative measures of ``approximate isosceles triangle,'' ``approximate elongated isosceles triangle,'' ``approximate rectangle,'' and ``approximate cross'' are defined and used in the illustrative examples of this approach. By using these quantitative measures, a house, a house with high roof, and a church are also presented as illustrative examples. In addition, three fuzzy tree automata are constructed which have the capability of processing the fuzzy tree representations of ``fuzzy houses,'' ``houses with high roofs,'' and ``fuzzy churches,'' respectively. The results may have useful applications in pattern recognition, image processing, artificial intelligence, pattern database design and processing, image science, and pictorial information systems.

PCB Fault Detection Using Image Processing

NASA Astrophysics Data System (ADS)

Nayak, Jithendra P. R.; Anitha, K.; Parameshachari, B. D., Dr.; Banu, Reshma, Dr.; Rashmi, P.

2017-08-01

The importance of the Printed Circuit Board inspection process has been magnified by requirements of the modern manufacturing environment where delivery of 100% defect free PCBs is the expectation. To meet such expectations, identifying various defects and their types becomes the first step. In this PCB inspection system the inspection algorithm mainly focuses on the defect detection using the natural images. Many practical issues like tilt of the images, bad light conditions, height at which images are taken etc. are to be considered to ensure good quality of the image which can then be used for defect detection. Printed circuit board (PCB) fabrication is a multidisciplinary process, and etching is the most critical part in the PCB manufacturing process. The main objective of Etching process is to remove the exposed unwanted copper other than the required circuit pattern. In order to minimize scrap caused by the wrongly etched PCB panel, inspection has to be done in early stage. However, all of the inspections are done after the etching process where any defective PCB found is no longer useful and is simply thrown away. Since etching process costs 0% of the entire PCB fabrication, it is uneconomical to simply discard the defective PCBs. In this paper a method to identify the defects in natural PCB images and associated practical issues are addressed using Software tools and some of the major types of single layer PCB defects are Pattern Cut, Pin hole, Pattern Short, Nick etc., Therefore the defects should be identified before the etching process so that the PCB would be reprocessed. In the present approach expected to improve the efficiency of the system in detecting the defects even in low quality images

Data processing device test apparatus and method therefor

DOEpatents

Wilcox, Richard Jacob; Mulig, Jason D.; Eppes, David; Bruce, Michael R.; Bruce, Victoria J.; Ring, Rosalinda M.; Cole, Jr., Edward I.; Tangyunyong, Paiboon; Hawkins, Charles F.; Louie, Arnold Y.

2003-04-08

A method and apparatus mechanism for testing data processing devices are implemented. The test mechanism isolates critical paths by correlating a scanning microscope image with a selected speed path failure. A trigger signal having a preselected value is generated at the start of each pattern vector. The sweep of the scanning microscope is controlled by a computer, which also receives and processes the image signals returned from the microscope. The value of the trigger signal is correlated with a set of pattern lines being driven on the DUT. The trigger is either asserted or negated depending the detection of a pattern line failure and the particular line that failed. In response to the detection of the particular speed path failure being characterized, and the trigger signal, the control computer overlays a mask on the image of the device under test (DUT). The overlaid image provides a visual correlation of the failure with the structural elements of the DUT at the level of resolution of the microscope itself.

Imaging energy landscapes with concentrated diffusing colloidal probes

NASA Astrophysics Data System (ADS)

Bahukudumbi, Pradipkumar; Bevan, Michael A.

2007-06-01

The ability to locally interrogate interactions between particles and energetically patterned surfaces provides essential information to design, control, and optimize template directed self-assembly processes. Although numerous techniques are capable of characterizing local physicochemical surface properties, no current method resolves interactions between colloids and patterned surfaces on the order of the thermal energy kT, which is the inherent energy scale of equilibrium self-assembly processes. Here, the authors describe video microscopy measurements and an inverse Monte Carlo analysis of diffusing colloidal probes as a means to image three dimensional free energy and potential energy landscapes due to physically patterned surfaces. In addition, they also develop a consistent analysis of self-diffusion in inhomogeneous fluids of concentrated diffusing probes on energy landscapes, which is important to the temporal imaging process and to self-assembly kinetics. Extension of the concepts developed in this work suggests a general strategy to image multidimensional and multiscale physical, chemical, and biological surfaces using a variety of diffusing probes (i.e., molecules, macromolecules, nanoparticles, and colloids).

Morphology filter bank for extracting nodular and linear patterns in medical images.

PubMed

Hashimoto, Ryutaro; Uchiyama, Yoshikazu; Uchimura, Keiichi; Koutaki, Gou; Inoue, Tomoki

2017-04-01

Using image processing to extract nodular or linear shadows is a key technique of computer-aided diagnosis schemes. This study proposes a new method for extracting nodular and linear patterns of various sizes in medical images. We have developed a morphology filter bank that creates multiresolution representations of an image. Analysis bank of this filter bank produces nodular and linear patterns at each resolution level. Synthesis bank can then be used to perfectly reconstruct the original image from these decomposed patterns. Our proposed method shows better performance based on a quantitative evaluation using a synthesized image compared with a conventional method based on a Hessian matrix, often used to enhance nodular and linear patterns. In addition, experiments show that our method can be applied to the followings: (1) microcalcifications of various sizes in mammograms can be extracted, (2) blood vessels of various sizes in retinal fundus images can be extracted, and (3) thoracic CT images can be reconstructed while removing normal vessels. Our proposed method is useful for extracting nodular and linear shadows or removing normal structures in medical images.

Color filter array pattern identification using variance of color difference image

NASA Astrophysics Data System (ADS)

Shin, Hyun Jun; Jeon, Jong Ju; Eom, Il Kyu

2017-07-01

A color filter array is placed on the image sensor of a digital camera to acquire color images. Each pixel uses only one color, since the image sensor can measure only one color per pixel. Therefore, empty pixels are filled using an interpolation process called demosaicing. The original and the interpolated pixels have different statistical characteristics. If the image is modified by manipulation or forgery, the color filter array pattern is altered. This pattern change can be a clue for image forgery detection. However, most forgery detection algorithms have the disadvantage of assuming the color filter array pattern. We present an identification method of the color filter array pattern. Initially, the local mean is eliminated to remove the background effect. Subsequently, the color difference block is constructed to emphasize the difference between the original pixel and the interpolated pixel. The variance measure of the color difference image is proposed as a means of estimating the color filter array configuration. The experimental results show that the proposed method is effective in identifying the color filter array pattern. Compared with conventional methods, our method provides superior performance.

Visual Communications and Image Processing

NASA Astrophysics Data System (ADS)

Hsing, T. Russell

1987-07-01

This special issue of Optical Engineering is concerned with visual communications and image processing. The increase in communication of visual information over the past several decades has resulted in many new image processing and visual communication systems being put into service. The growth of this field has been rapid in both commercial and military applications. The objective of this special issue is to intermix advent technology in visual communications and image processing with ideas generated from industry, universities, and users through both invited and contributed papers. The 15 papers of this issue are organized into four different categories: image compression and transmission, image enhancement, image analysis and pattern recognition, and image processing in medical applications.

Computer-based classification of bacteria species by analysis of their colonies Fresnel diffraction patterns

NASA Astrophysics Data System (ADS)

Suchwalko, Agnieszka; Buzalewicz, Igor; Podbielska, Halina

2012-01-01

In the presented paper the optical system with converging spherical wave illumination for classification of bacteria species, is proposed. It allows for compression of the observation space, observation of Fresnel patterns, diffraction pattern scaling and low level of optical aberrations, which are not possessed by other optical configurations. Obtained experimental results have shown that colonies of specific bacteria species generate unique diffraction signatures. Analysis of Fresnel diffraction patterns of bacteria colonies can be fast and reliable method for classification and recognition of bacteria species. To determine the unique features of bacteria colonies diffraction patterns the image processing analysis was proposed. Classification can be performed by analyzing the spatial structure of diffraction patterns, which can be characterized by set of concentric rings. The characteristics of such rings depends on the bacteria species. In the paper, the influence of basic features and ring partitioning number on the bacteria classification, is analyzed. It is demonstrated that Fresnel patterns can be used for classification of following species: Salmonella enteritidis, Staplyococcus aureus, Proteus mirabilis and Citrobacter freundii. Image processing is performed by free ImageJ software, for which a special macro with human interaction, was written. LDA classification, CV method, ANOVA and PCA visualizations preceded by image data extraction were conducted using the free software R.

Determination of Hydrodynamic Parameters on Two--Phase Flow Gas - Liquid in Pipes with Different Inclination Angles Using Image Processing Algorithm

NASA Astrophysics Data System (ADS)

Montoya, Gustavo; Valecillos, María; Romero, Carlos; Gonzáles, Dosinda

2009-11-01

In the present research a digital image processing-based automated algorithm was developed in order to determine the phase's height, hold up, and statistical distribution of the drop size in a two-phase system water-air using pipes with 0 , 10 , and 90 of inclination. Digital images were acquired with a high speed camera (up to 4500fps), using an equipment that consist of a system with three acrylic pipes with diameters of 1.905, 3.175, and 4.445 cm. Each pipe is arranged in two sections of 8 m of length. Various flow patterns were visualized for different superficial velocities of water and air. Finally, using the image processing program designed in Matlab/Simulink^, the captured images were processed to establish the parameters previously mentioned. The image processing algorithm is based in the frequency domain analysis of the source pictures, which allows to find the phase as the edge between the water and air, through a Sobel filter that extracts the high frequency components of the image. The drop size was found using the calculation of the Feret diameter. Three flow patterns were observed: Annular, ST, and ST&MI.

Patterned mask inspection technology with Projection Electron Microscope (PEM) technique for 11 nm half-pitch (hp) generation EUV masks

NASA Astrophysics Data System (ADS)

Hirano, Ryoichi; Iida, Susumu; Amano, Tsuyoshi; Watanabe, Hidehiro; Hatakeyama, Masahiro; Murakami, Takeshi; Yoshikawa, Shoji; Suematsu, Kenichi; Terao, Kenji

2015-07-01

High-sensitivity EUV mask pattern defect detection is one of the major issues in order to realize the device fabrication by using the EUV lithography. We have already designed a novel Projection Electron Microscope (PEM) optics that has been integrated into a new inspection system named EBEYE-V30 ("Model EBEYE" is an EBARA's model code), and which seems to be quite promising for 16 nm hp generation EUVL Patterned mask Inspection (PI). Defect inspection sensitivity was evaluated by capturing an electron image generated at the mask by focusing onto an image sensor. The progress of the novel PEM optics performance is not only about making an image sensor with higher resolution but also about doing a better image processing to enhance the defect signal. In this paper, we describe the experimental results of EUV patterned mask inspection using the above-mentioned system. The performance of the system is measured in terms of defect detectability for 11 nm hp generation EUV mask. To improve the inspection throughput for 11 nm hp generation defect detection, it would require a data processing rate of greater than 1.5 Giga- Pixel-Per-Second (GPPS) that would realize less than eight hours of inspection time including the step-and-scan motion associated with the process. The aims of the development program are to attain a higher throughput, and enhance the defect detection sensitivity by using an adequate pixel size with sophisticated image processing resulting in a higher processing rate.

Precise design-based defect characterization and root cause analysis

NASA Astrophysics Data System (ADS)

Xie, Qian; Venkatachalam, Panneerselvam; Lee, Julie; Chen, Zhijin; Zafar, Khurram

2017-03-01

As semiconductor manufacturing continues its march towards more advanced technology nodes, it becomes increasingly important to identify and characterize design weak points, which is typically done using a combination of inline inspection data and the physical layout (or design). However, the employed methodologies have been somewhat imprecise, relying greatly on statistical techniques to signal excursions. For example, defect location error that is inherent to inspection tools prevents them from reporting the true locations of defects. Therefore, common operations such as background-based binning that are designed to identify frequently failing patterns cannot reliably identify specific weak patterns. They can only identify an approximate set of possible weak patterns, but within these sets there are many perfectly good patterns. Additionally, characterizing the failure rate of a known weak pattern based on inline inspection data also has a lot of fuzziness due to coordinate uncertainty. SEM (Scanning Electron Microscope) Review attempts to come to the rescue by capturing high resolution images of the regions surrounding the reported defect locations, but SEM images are reviewed by human operators and the weak patterns revealed in those images must be manually identified and classified. Compounding the problem is the fact that a single Review SEM image may contain multiple defective patterns and several of those patterns might not appear defective to the human eye. In this paper we describe a significantly improved methodology that brings advanced computer image processing and design-overlay techniques to better address the challenges posed by today's leading technology nodes. Specifically, new software techniques allow the computer to analyze Review SEM images in detail, to overlay those images with reference design to detect every defect that might be present in all regions of interest within the overlaid reference design (including several classes of defects that human operators will typically miss), to obtain the exact defect location on design, to compare all defective patterns thus detected against a library of known patterns, and to classify all defective patterns as either new or known. By applying the computer to these tasks, we automate the entire process from defective pattern identification to pattern classification with high precision, and we perform this operation en masse during R & D, ramp, and volume production. By adopting the methodology, whenever a specific weak pattern is identified, we are able to run a series of characterization operations to ultimately arrive at the root cause. These characterization operations can include (a) searching all pre-existing Review SEM images for the presence of the specific weak pattern to determine whether there is any spatial (within die or within wafer) or temporal (within any particular date range, before or after a mask revision, etc.) correlation and (b) understanding the failure rate of the specific weak pattern to prioritize the urgency of the problem, (c) comparing the weak pattern against an OPC (Optical Procimity Correction) Verification report or a PWQ (Process Window Qualification)/FEM (Focus Exposure Matrix) result to assess the likelihood of it being a litho-sensitive pattern, etc. After resolving the specific weak pattern, we will categorize it as known pattern, and the engineer will move forward with discovering new weak patterns.

Quantification of differences between nailfold capillaroscopy images with a scleroderma pattern and normal pattern using measures of geometric and algorithmic complexity.

PubMed

Urwin, Samuel George; Griffiths, Bridget; Allen, John

2017-02-01

This study aimed to quantify and investigate differences in the geometric and algorithmic complexity of the microvasculature in nailfold capillaroscopy (NFC) images displaying a scleroderma pattern and those displaying a 'normal' pattern. 11 NFC images were qualitatively classified by a capillary specialist as indicative of 'clear microangiopathy' (CM), i.e. a scleroderma pattern, and 11 as 'not clear microangiopathy' (NCM), i.e. a 'normal' pattern. Pre-processing was performed, and fractal dimension (FD) and Kolmogorov complexity (KC) were calculated following image binarisation. FD and KC were compared between groups, and a k-means cluster analysis (n  =  2) on all images was performed, without prior knowledge of the group assigned to them (i.e. CM or NCM), using FD and KC as inputs. CM images had significantly reduced FD and KC compared to NCM images, and the cluster analysis displayed promising results that the quantitative classification of images into CM and NCM groups is possible using the mathematical measures of FD and KC. The analysis techniques used show promise for quantitative microvascular investigation in patients with systemic sclerosis.

Arithmetic of five-part of leukocytes based on image process

NASA Astrophysics Data System (ADS)

Li, Yian; Wang, Guoyou; Liu, Jianguo

2007-12-01

This paper apply computer image processing and pattern recognizition methods to solve the problem of auto classification and counting of leukocytes (white blood cell) in peripheral blood. In this paper a new leukocyte arithmetic of five-part based on image process and pattern recognizition is presented, which relized auto classify of leukocyte. The first aim is detect the leukocytes . A major requirement of the whole system is to classify these leukocytes to 5 classes. This arithmetic bases on notability mechanism of eyes, process image by sequence, divides up leukocytes and pick up characters. Using the prior kwonledge of cells and image shape information, this arithmetic divides up the probable shape of Leukocyte first by a new method based on Chamfer and then gets the detail characters. It can reduce the mistake judge rate and the calculation greatly. It also has the learning fuction. This paper also presented a new measurement of karyon's shape which can provide more accurate information. This algorithm has great application value in clinical blood test .

Document Image Parsing and Understanding using Neuromorphic Architecture

DTIC Science & Technology

2015-03-01

processing speed at different layers. In the pattern matching layer, the computing power of multicore processors is explored to reduce the processing...developed to reduce the processing speed at different layers. In the pattern matching layer, the computing power of multicore processors is explored... cortex where the complex data is reduced to abstract representations. The abstract representation is compared to stored patterns in massively parallel

Architecture of the parallel hierarchical network for fast image recognition

NASA Astrophysics Data System (ADS)

Timchenko, Leonid; Wójcik, Waldemar; Kokriatskaia, Natalia; Kutaev, Yuriy; Ivasyuk, Igor; Kotyra, Andrzej; Smailova, Saule

2016-09-01

Multistage integration of visual information in the brain allows humans to respond quickly to most significant stimuli while maintaining their ability to recognize small details in the image. Implementation of this principle in technical systems can lead to more efficient processing procedures. The multistage approach to image processing includes main types of cortical multistage convergence. The input images are mapped into a flexible hierarchy that reflects complexity of image data. Procedures of the temporal image decomposition and hierarchy formation are described in mathematical expressions. The multistage system highlights spatial regularities, which are passed through a number of transformational levels to generate a coded representation of the image that encapsulates a structure on different hierarchical levels in the image. At each processing stage a single output result is computed to allow a quick response of the system. The result is presented as an activity pattern, which can be compared with previously computed patterns on the basis of the closest match. With regard to the forecasting method, its idea lies in the following. In the results synchronization block, network-processed data arrive to the database where a sample of most correlated data is drawn using service parameters of the parallel-hierarchical network.

Can Geostatistical Models Represent Nature's Variability? An Analysis Using Flume Experiments

NASA Astrophysics Data System (ADS)

Scheidt, C.; Fernandes, A. M.; Paola, C.; Caers, J.

2015-12-01

The lack of understanding in the Earth's geological and physical processes governing sediment deposition render subsurface modeling subject to large uncertainty. Geostatistics is often used to model uncertainty because of its capability to stochastically generate spatially varying realizations of the subsurface. These methods can generate a range of realizations of a given pattern - but how representative are these of the full natural variability? And how can we identify the minimum set of images that represent this natural variability? Here we use this minimum set to define the geostatistical prior model: a set of training images that represent the range of patterns generated by autogenic variability in the sedimentary environment under study. The proper definition of the prior model is essential in capturing the variability of the depositional patterns. This work starts with a set of overhead images from an experimental basin that showed ongoing autogenic variability. We use the images to analyze the essential characteristics of this suite of patterns. In particular, our goal is to define a prior model (a minimal set of selected training images) such that geostatistical algorithms, when applied to this set, can reproduce the full measured variability. A necessary prerequisite is to define a measure of variability. In this study, we measure variability using a dissimilarity distance between the images. The distance indicates whether two snapshots contain similar depositional patterns. To reproduce the variability in the images, we apply an MPS algorithm to the set of selected snapshots of the sedimentary basin that serve as training images. The training images are chosen from among the initial set by using the distance measure to ensure that only dissimilar images are chosen. Preliminary investigations show that MPS can reproduce fairly accurately the natural variability of the experimental depositional system. Furthermore, the selected training images provide process information. They fall into three basic patterns: a channelized end member, a sheet flow end member, and one intermediate case. These represent the continuum between autogenic bypass or erosion, and net deposition.

Advanced plasma etch technologies for nanopatterning

NASA Astrophysics Data System (ADS)

Wise, Rich

2013-10-01

Advances in patterning techniques have enabled the extension of immersion lithography from 65/45 nm through 14/10 nm device technologies. A key to this increase in patterning capability has been innovation in the subsequent dry plasma etch processing steps. Multiple exposure techniques, such as litho-etch-litho-etch, sidewall image transfer, line/cut mask, and self-aligned structures, have been implemented to solution required device scaling. Advances in dry plasma etch process control across wafer uniformity and etch selectivity to both masking materials have enabled adoption of vertical devices and thin film scaling for increased device performance at a given pitch. Plasma etch processes, such as trilayer etches, aggressive critical dimension shrink techniques, and the extension of resist trim processes, have increased the attainable device dimensions at a given imaging capability. Precise control of the plasma etch parameters affecting across-design variation, defectivity, profile stability within wafer, within lot, and across tools has been successfully implemented to provide manufacturable patterning technology solutions. IBM has addressed these patterning challenges through an integrated total patterning solutions team to provide seamless and synergistic patterning processes to device and integration internal customers. We will discuss these challenges and the innovative plasma etch solutions pioneered by IBM and our alliance partners.

Advanced plasma etch technologies for nanopatterning

NASA Astrophysics Data System (ADS)

Wise, Rich

2012-03-01

Advances in patterning techniques have enabled the extension of immersion lithography from 65/45nm through 14/10nm device technologies. A key to this increase in patterning capability has been innovation in the subsequent dry plasma etch processing steps. Multiple exposure techniques such as litho-etch-litho-etch, sidewall image transfer, line/cut mask and self-aligned structures have been implemented to solution required device scaling. Advances in dry plasma etch process control, across wafer uniformity and etch selectivity to both masking materials and have enabled adoption of vertical devices and thin film scaling for increased device performance at a given pitch. Plasma etch processes such as trilayer etches, aggressive CD shrink techniques, and the extension of resist trim processes have increased the attainable device dimensions at a given imaging capability. Precise control of the plasma etch parameters affecting across design variation, defectivity, profile stability within wafer, within lot, and across tools have been successfully implemented to provide manufacturable patterning technology solutions. IBM has addressed these patterning challenges through an integrated Total Patterning Solutions team to provide seamless and synergistic patterning processes to device and integration internal customers. This paper will discuss these challenges and the innovative plasma etch solutions pioneered by IBM and our alliance partners.

Medical image classification using spatial adjacent histogram based on adaptive local binary patterns.

PubMed

Liu, Dong; Wang, Shengsheng; Huang, Dezhi; Deng, Gang; Zeng, Fantao; Chen, Huiling

2016-05-01

Medical image recognition is an important task in both computer vision and computational biology. In the field of medical image classification, representing an image based on local binary patterns (LBP) descriptor has become popular. However, most existing LBP-based methods encode the binary patterns in a fixed neighborhood radius and ignore the spatial relationships among local patterns. The ignoring of the spatial relationships in the LBP will cause a poor performance in the process of capturing discriminative features for complex samples, such as medical images obtained by microscope. To address this problem, in this paper we propose a novel method to improve local binary patterns by assigning an adaptive neighborhood radius for each pixel. Based on these adaptive local binary patterns, we further propose a spatial adjacent histogram strategy to encode the micro-structures for image representation. An extensive set of evaluations are performed on four medical datasets which show that the proposed method significantly improves standard LBP and compares favorably with several other prevailing approaches. Copyright © 2016 Elsevier Ltd. All rights reserved.

A median-Gaussian filtering framework for Moiré pattern noise removal from X-ray microscopy image.

PubMed

Wei, Zhouping; Wang, Jian; Nichol, Helen; Wiebe, Sheldon; Chapman, Dean

2012-02-01

Moiré pattern noise in Scanning Transmission X-ray Microscopy (STXM) imaging introduces significant errors in qualitative and quantitative image analysis. Due to the complex origin of the noise, it is difficult to avoid Moiré pattern noise during the image data acquisition stage. In this paper, we introduce a post-processing method for filtering Moiré pattern noise from STXM images. This method includes a semi-automatic detection of the spectral peaks in the Fourier amplitude spectrum by using a local median filter, and elimination of the spectral noise peaks using a Gaussian notch filter. The proposed median-Gaussian filtering framework shows good results for STXM images with the size of power of two, if such parameters as threshold, sizes of the median and Gaussian filters, and size of the low frequency window, have been properly selected. Copyright © 2011 Elsevier Ltd. All rights reserved.

Quantitative evaluation of high-resolution features in images of negatively stained Tobacco Mosaic Virus.

PubMed

Chang, C F; Williams, R C; Grano, D A; Downing, K H; Glaeser, R M

1983-01-01

This study investigates the causes of the apparent differences between the optical diffraction pattern of a micrograph of a Tobacco Mosaic Virus (TMV) particle, the optical diffraction pattern of a ten-fold photographically averaged image, and the computed diffraction pattern of the original micrograph. Peak intensities along the layer lines in the transform of the averaged image appear to be quite unlike those in the diffraction pattern of the original micrograph, and the diffraction intensities for the averaged image extend to unexpectedly high resolution. A carefully controlled, quantitative comparison reveals, however, that the optical diffraction pattern of the original micrograph and that of the ten-fold averaged image are essentially equivalent. Using computer-based image processing, we discovered that the peak intensities on the 6th layer line have values very similar in magnitude to the neighboring noise, in contrast to what was expected from the optical diffraction pattern of the original micrograph. This discrepancy was resolved by recording a series of optical diffraction patterns when the original micrograph was immersed in oil. These patterns revealed the presence of a substantial phase grating effect, which exaggerated the peak intensities on the 6th layer line, causing an erroneous impression that the high resolution features possessed a good signal-to-noise ratio. This study thus reveals some pitfalls and misleading results that can be encountered when using optical diffraction patterns to evaluate image quality.

Quantitative approach for optimizing e-beam condition of photoresist inspection and measurement

NASA Astrophysics Data System (ADS)

Lin, Chia-Jen; Teng, Chia-Hao; Cheng, Po-Chung; Sato, Yoshishige; Huang, Shang-Chieh; Chen, Chu-En; Maruyama, Kotaro; Yamazaki, Yuichiro

2018-03-01

Severe process margin in advanced technology node of semiconductor device is controlled by e-beam metrology system and e-beam inspection system with scanning electron microscopy (SEM) image. By using SEM, larger area image with higher image quality is required to collect massive amount of data for metrology and to detect defect in a large area for inspection. Although photoresist is the one of the critical process in semiconductor device manufacturing, observing photoresist pattern by SEM image is crucial and troublesome especially in the case of large image. The charging effect by e-beam irradiation on photoresist pattern causes deterioration of image quality, and it affect CD variation on metrology system and causes difficulties to continue defect inspection in a long time for a large area. In this study, we established a quantitative approach for optimizing e-beam condition with "Die to Database" algorithm of NGR3500 on photoresist pattern to minimize charging effect. And we enhanced the performance of measurement and inspection on photoresist pattern by using optimized e-beam condition. NGR3500 is the geometry verification system based on "Die to Database" algorithm which compares SEM image with design data [1]. By comparing SEM image and design data, key performance indicator (KPI) of SEM image such as "Sharpness", "S/N", "Gray level variation in FOV", "Image shift" can be retrieved. These KPIs were analyzed with different e-beam conditions which consist of "Landing Energy", "Probe Current", "Scanning Speed" and "Scanning Method", and the best e-beam condition could be achieved with maximum image quality, maximum scanning speed and minimum image shift. On this quantitative approach of optimizing e-beam condition, we could observe dependency of SEM condition on photoresist charging. By using optimized e-beam condition, measurement could be continued on photoresist pattern over 24 hours stably. KPIs of SEM image proved image quality during measurement and inspection was stabled enough.

Development of measurement system for gauge block interferometer

NASA Astrophysics Data System (ADS)

Chomkokard, S.; Jinuntuya, N.; Wongkokua, W.

2017-09-01

We developed a measurement system for collecting and analyzing the fringe pattern images from a gauge block interferometer. The system was based on Raspberry Pi which is an open source system with python programming and opencv image manipulation library. The images were recorded by the Raspberry Pi camera with five-megapixel capacity. The noise of images was suppressed for the best result in analyses. The low noise images were processed to find the edge of fringe patterns using the contour technique for the phase shift analyses. We tested our system with the phase shift patterns between a gauge block and a reference plate. The phase shift patterns were measured by a Twyman-Green type of interferometer using the He-Ne laser with the temperature controlled at 20.0 °C. The results of the measurement will be presented and discussed.

Advanced image based methods for structural integrity monitoring: Review and prospects

NASA Astrophysics Data System (ADS)

Farahani, Behzad V.; Sousa, Pedro José; Barros, Francisco; Tavares, Paulo J.; Moreira, Pedro M. G. P.

2018-02-01

There is a growing trend in engineering to develop methods for structural integrity monitoring and characterization of in-service mechanical behaviour of components. The fast growth in recent years of image processing techniques and image-based sensing for experimental mechanics, brought about a paradigm change in phenomena sensing. Hence, several widely applicable optical approaches are playing a significant role in support of experiment. The current review manuscript describes advanced image based methods for structural integrity monitoring, and focuses on methods such as Digital Image Correlation (DIC), Thermoelastic Stress Analysis (TSA), Electronic Speckle Pattern Interferometry (ESPI) and Speckle Pattern Shearing Interferometry (Shearography). These non-contact full-field techniques rely on intensive image processing methods to measure mechanical behaviour, and evolve even as reviews such as this are being written, which justifies a special effort to keep abreast of this progress.

Body image dissatisfaction and dietary patterns according to nutritional status in adolescents.

PubMed

Ribeiro-Silva, Rita de Cássia; Fiaccone, Rosemeire Leovigildo; Conceição-Machado, Maria Ester Pereira da; Ruiz, Ana Santos; Barreto, Maurício Lima; Santana, Mônica Leila Portela

There is a lack of data on the association between body self-perception and eating patterns in Brazil. Thus, this study aimed to explore the relationship between body image dissatisfaction and eating patterns by the anthropometric status in adolescents. A cross-sectional study of 1496 adolescents was conducted. The participants completed the Body Shape Questionnaire. Demographic, anthropometric, and socioeconomic data were collected, as well as information regarding the pubertal development and dietary intake. Logistic regression was performed to evaluate the associations of interest. Body image dissatisfaction was identified in 19.5% of the adolescents. Three dietary patterns were identified: (1) the Western pattern was composed of sweets and sugars, soft drinks, typical dishes, pastries, fast food, beef, milk, and dairy products; (2) the Traditional pattern was composed of oils, chicken, fish, eggs, processed meat products, cereals (rice, cassava flour, pasta, etc.), baked beans, and bread; and (3) the Restrictive pattern was composed of granola, roots, vegetables, and fruit. Among overweight/obese adolescents, the data indicated a negative association of slight body image dissatisfaction (OR: 0.240 [0.100; 0.576]) and moderate body image dissatisfaction (OR: 0.235 [0.086; 0.645]) with the Western dietary pattern. Additionally, in this group, there was a positive association between high body image dissatisfaction and the Restrictive pattern (OR: 2.794 [1.178; 6.630]). Amongst overweight/obese adolescents, those with slight and moderate body image dissatisfaction were less likely to follow a Western-like dietary pattern when compared with those satisfied with their body image. Additionally, in this group, adolescents with high body image dissatisfaction was more likely to follow a restrictive pattern. Copyright © 2017 Sociedade Brasileira de Pediatria. Published by Elsevier Editora Ltda. All rights reserved.

Analysis of microvascular perfusion with multi-dimensional complete ensemble empirical mode decomposition with adaptive noise algorithm: Processing of laser speckle contrast images recorded in healthy subjects, at rest and during acetylcholine stimulation.

PubMed

Humeau-Heurtier, Anne; Marche, Pauline; Dubois, Severine; Mahe, Guillaume

2015-01-01

Laser speckle contrast imaging (LSCI) is a full-field imaging modality to monitor microvascular blood flow. It is able to give images with high temporal and spatial resolutions. However, when the skin is studied, the interpretation of the bidimensional data may be difficult. This is why an averaging of the perfusion values in regions of interest is often performed and the result is followed in time, reducing the data to monodimensional time series. In order to avoid such a procedure (that leads to a loss of the spatial resolution), we propose to extract patterns from LSCI data and to compare these patterns for two physiological states in healthy subjects: at rest and at the peak of acetylcholine-induced perfusion peak. For this purpose, the recent multi-dimensional complete ensemble empirical mode decomposition with adaptive noise (MCEEMDAN) algorithm is applied to LSCI data. The results show that the intrinsic mode functions and residue given by MCEEMDAN show different patterns for the two physiological states. The images, as bidimensional data, can therefore be processed to reveal microvascular perfusion patterns, hidden in the images themselves. This work is therefore a feasibility study before analyzing data in patients with microvascular dysfunctions.

Efficient demodulation scheme for rolling-shutter-patterning of CMOS image sensor based visible light communications.

PubMed

Chen, Chia-Wei; Chow, Chi-Wai; Liu, Yang; Yeh, Chien-Hung

2017-10-02

Recently even the low-end mobile-phones are equipped with a high-resolution complementary-metal-oxide-semiconductor (CMOS) image sensor. This motivates using a CMOS image sensor for visible light communication (VLC). Here we propose and demonstrate an efficient demodulation scheme to synchronize and demodulate the rolling shutter pattern in image sensor based VLC. The implementation algorithm is discussed. The bit-error-rate (BER) performance and processing latency are evaluated and compared with other thresholding schemes.

Searching for patterns in remote sensing image databases using neural networks

NASA Technical Reports Server (NTRS)

Paola, Justin D.; Schowengerdt, Robert A.

1995-01-01

We have investigated a method, based on a successful neural network multispectral image classification system, of searching for single patterns in remote sensing databases. While defining the pattern to search for and the feature to be used for that search (spectral, spatial, temporal, etc.) is challenging, a more difficult task is selecting competing patterns to train against the desired pattern. Schemes for competing pattern selection, including random selection and human interpreted selection, are discussed in the context of an example detection of dense urban areas in Landsat Thematic Mapper imagery. When applying the search to multiple images, a simple normalization method can alleviate the problem of inconsistent image calibration. Another potential problem, that of highly compressed data, was found to have a minimal effect on the ability to detect the desired pattern. The neural network algorithm has been implemented using the PVM (Parallel Virtual Machine) library and nearly-optimal speedups have been obtained that help alleviate the long process of searching through imagery.

High-speed imaging using compressed sensing and wavelength-dependent scattering (Conference Presentation)

NASA Astrophysics Data System (ADS)

Shin, Jaewook; Bosworth, Bryan T.; Foster, Mark A.

2017-02-01

The process of multiple scattering has inherent characteristics that are attractive for high-speed imaging with high spatial resolution and a wide field-of-view. A coherent source passing through a multiple-scattering medium naturally generates speckle patterns with diffraction-limited features over an arbitrarily large field-of-view. In addition, the process of multiple scattering is deterministic allowing a given speckle pattern to be reliably reproduced with identical illumination conditions. Here, by exploiting wavelength dependent multiple scattering and compressed sensing, we develop a high-speed 2D time-stretch microscope. Highly chirped pulses from a 90-MHz mode-locked laser are sent through a 2D grating and a ground-glass diffuser to produce 2D speckle patterns that rapidly evolve with the instantaneous frequency of the chirped pulse. To image a scene, we first characterize the high-speed evolution of the generated speckle patterns. Subsequently we project the patterns onto the microscopic region of interest and collect the total light from the scene using a single high-speed photodetector. Thus the wavelength dependent speckle patterns serve as high-speed pseudorandom structured illumination of the scene. An image sequence is then recovered using the time-dependent signal received by the photodetector, the known speckle pattern evolution, and compressed sensing algorithms. Notably, the use of compressed sensing allows for reconstruction of a time-dependent scene using a highly sub-Nyquist number of measurements, which both increases the speed of the imager and reduces the amount of data that must be collected and stored. We will discuss our experimental demonstration of this approach and the theoretical limits on imaging speed.

Automated Recognition of 3D Features in GPIR Images

NASA Technical Reports Server (NTRS)

Park, Han; Stough, Timothy; Fijany, Amir

2007-01-01

A method of automated recognition of three-dimensional (3D) features in images generated by ground-penetrating imaging radar (GPIR) is undergoing development. GPIR 3D images can be analyzed to detect and identify such subsurface features as pipes and other utility conduits. Until now, much of the analysis of GPIR images has been performed manually by expert operators who must visually identify and track each feature. The present method is intended to satisfy a need for more efficient and accurate analysis by means of algorithms that can automatically identify and track subsurface features, with minimal supervision by human operators. In this method, data from multiple sources (for example, data on different features extracted by different algorithms) are fused together for identifying subsurface objects. The algorithms of this method can be classified in several different ways. In one classification, the algorithms fall into three classes: (1) image-processing algorithms, (2) feature- extraction algorithms, and (3) a multiaxis data-fusion/pattern-recognition algorithm that includes a combination of machine-learning, pattern-recognition, and object-linking algorithms. The image-processing class includes preprocessing algorithms for reducing noise and enhancing target features for pattern recognition. The feature-extraction algorithms operate on preprocessed data to extract such specific features in images as two-dimensional (2D) slices of a pipe. Then the multiaxis data-fusion/ pattern-recognition algorithm identifies, classifies, and reconstructs 3D objects from the extracted features. In this process, multiple 2D features extracted by use of different algorithms and representing views along different directions are used to identify and reconstruct 3D objects. In object linking, which is an essential part of this process, features identified in successive 2D slices and located within a threshold radius of identical features in adjacent slices are linked in a directed-graph data structure. Relative to past approaches, this multiaxis approach offers the advantages of more reliable detections, better discrimination of objects, and provision of redundant information, which can be helpful in filling gaps in feature recognition by one of the component algorithms. The image-processing class also includes postprocessing algorithms that enhance identified features to prepare them for further scrutiny by human analysts (see figure). Enhancement of images as a postprocessing step is a significant departure from traditional practice, in which enhancement of images is a preprocessing step.

Advanced microlens and color filter process technology for the high-efficiency CMOS and CCD image sensors

NASA Astrophysics Data System (ADS)

Fan, Yang-Tung; Peng, Chiou-Shian; Chu, Cheng-Yu

2000-12-01

New markets are emerging for digital electronic image device, especially in visual communications, PC camera, mobile/cell phone, security system, toys, vehicle image system and computer peripherals for document capture. To enable one-chip image system that image sensor is with a full digital interface, can make image capture devices in our daily lives. Adding a color filter to such image sensor in a pattern of mosaics pixel or wide stripes can make image more real and colorful. We can say 'color filter makes the life more colorful color filter is? Color filter means can filter image light source except the color with specific wavelength and transmittance that is same as color filter itself. Color filter process is coating and patterning green, red and blue (or cyan, magenta and yellow) mosaic resists onto matched pixel in image sensing array pixels. According to the signal caught from each pixel, we can figure out the environment image picture. Widely use of digital electronic camera and multimedia applications today makes the feature of color filter becoming bright. Although it has challenge but it is very worthy to develop the process of color filter. We provide the best service on shorter cycle time, excellent color quality, high and stable yield. The key issues of advanced color process have to be solved and implemented are planarization and micro-lens technology. Lost of key points of color filter process technology have to consider will also be described in this paper.

Gaussian pre-filtering for uncertainty minimization in digital image correlation using numerically-designed speckle patterns

NASA Astrophysics Data System (ADS)

Mazzoleni, Paolo; Matta, Fabio; Zappa, Emanuele; Sutton, Michael A.; Cigada, Alfredo

2015-03-01

This paper discusses the effect of pre-processing image blurring on the uncertainty of two-dimensional digital image correlation (DIC) measurements for the specific case of numerically-designed speckle patterns having particles with well-defined and consistent shape, size and spacing. Such patterns are more suitable for large measurement surfaces on large-scale specimens than traditional spray-painted random patterns without well-defined particles. The methodology consists of numerical simulations where Gaussian digital filters with varying standard deviation are applied to a reference speckle pattern. To simplify the pattern application process for large areas and increase contrast to reduce measurement uncertainty, the speckle shape, mean size and on-center spacing were selected to be representative of numerically-designed patterns that can be applied on large surfaces through different techniques (e.g., spray-painting through stencils). Such 'designer patterns' are characterized by well-defined regions of non-zero frequency content and non-zero peaks, and are fundamentally different from typical spray-painted patterns whose frequency content exhibits near-zero peaks. The effect of blurring filters is examined for constant, linear, quadratic and cubic displacement fields. Maximum strains between ±250 and ±20,000 με are simulated, thus covering a relevant range for structural materials subjected to service and ultimate stresses. The robustness of the simulation procedure is verified experimentally using a physical speckle pattern subjected to constant displacements. The stability of the relation between standard deviation of the Gaussian filter and measurement uncertainty is assessed for linear displacement fields at varying image noise levels, subset size, and frequency content of the speckle pattern. It is shown that bias error as well as measurement uncertainty are minimized through Gaussian pre-filtering. This finding does not apply to typical spray-painted patterns without well-defined particles, for which image blurring is only beneficial in reducing bias errors.

Data management in pattern recognition and image processing systems

NASA Technical Reports Server (NTRS)

Zobrist, A. L.; Bryant, N. A.

1976-01-01

Data management considerations are important to any system which handles large volumes of data or where the manipulation of data is technically sophisticated. A particular problem is the introduction of image-formatted files into the mainstream of data processing application. This report describes a comprehensive system for the manipulation of image, tabular, and graphical data sets which involve conversions between the various data types. A key characteristic is the use of image processing technology to accomplish data management tasks. Because of this, the term 'image-based information system' has been adopted.

X-ray mask and method for providing same

DOEpatents

Morales, Alfredo M [Pleasanton, CA; Skala, Dawn M [Fremont, CA

2004-09-28

The present invention describes a method for fabricating an x-ray mask tool which can achieve pattern features having lateral dimension of less than 1 micron. The process uses a thin photoresist and a standard lithographic mask to transfer an trace image pattern in the surface of a silicon wafer by exposing and developing the resist. The exposed portion of the silicon substrate is then anisotropically etched to provide an etched image of the trace image pattern consisting of a series of channels in the silicon having a high depth-to-width aspect ratio. These channels are then filled by depositing a metal such as gold to provide an inverse image of the trace image and thereby providing a robust x-ray mask tool.

X-ray mask and method for providing same

DOEpatents

Morales, Alfredo M.; Skala, Dawn M.

2002-01-01

The present invention describes a method for fabricating an x-ray mask tool which can achieve pattern features having lateral dimension of less than 1 micron. The process uses a thin photoresist and a standard lithographic mask to transfer an trace image pattern in the surface of a silicon wafer by exposing and developing the resist. The exposed portion of the silicon substrate is then anisotropically etched to provide an etched image of the trace image pattern consisting of a series of channels in the silicon having a high depth-to-width aspect ratio. These channels are then filled by depositing a metal such as gold to provide an inverse image of the trace image and thereby providing a robust x-ray mask tool.

Wood industrial application for quality control using image processing

NASA Astrophysics Data System (ADS)

Ferreira, M. J. O.; Neves, J. A. C.

1994-11-01

This paper describes an application of image processing for the furniture industry. It uses an input data, images acquired directly from wood planks where defects were previously marked by an operator. A set of image processing algorithms separates and codes each defect and detects a polygonal approach of the line representing them. For such a purpose we developed a pattern classification algorithm and a new technique of segmenting defects by carving the convex hull of the binary shape representing each isolated defect.

Image databases: Problems and perspectives

NASA Technical Reports Server (NTRS)

Gudivada, V. Naidu

1989-01-01

With the increasing number of computer graphics, image processing, and pattern recognition applications, economical storage, efficient representation and manipulation, and powerful and flexible query languages for retrieval of image data are of paramount importance. These and related issues pertinent to image data bases are examined.

SU-E-J-42: Motion Adaptive Image Filter for Low Dose X-Ray Fluoroscopy in the Real-Time Tumor-Tracking Radiotherapy System.

PubMed

Miyamoto, N; Ishikawa, M; Sutherland, K; Suzuki, R; Matsuura, T; Takao, S; Toramatsu, C; Nihongi, H; Shimizu, S; Onimaru, R; Umegaki, K; Shirato, H

2012-06-01

In the real-time tumor-tracking radiotherapy system, fiducial markers are detected by X-ray fluoroscopy. The fluoroscopic parameters should be optimized as low as possible in order to reduce unnecessary imaging dose. However, the fiducial markers could not be recognized due to effect of statistical noise in low dose imaging. Image processing is envisioned to be a solution to improve image quality and to maintain tracking accuracy. In this study, a recursive image filter adapted to target motion is proposed. A fluoroscopy system was used for the experiment. A spherical gold marker was used as a fiducial marker. About 450 fluoroscopic images of the marker were recorded. In order to mimic respiratory motion of the marker, the images were shifted sequentially. The tube voltage, current and exposure duration were fixed at 65 kV, 50 mA and 2.5 msec as low dose imaging condition, respectively. The tube current was 100 mA as high dose imaging. A pattern recognition score (PRS) ranging from 0 to 100 and image registration error were investigated by performing template pattern matching to each sequential image. The results with and without image processing were compared. In low dose imaging, theimage registration error and the PRS without the image processing were 2.15±1.21 pixel and 46.67±6.40, respectively. Those with the image processing were 1.48±0.82 pixel and 67.80±4.51, respectively. There was nosignificant difference in the image registration error and the PRS between the results of low dose imaging with the image processing and that of high dose imaging without the image processing. The results showed that the recursive filter was effective in order to maintain marker tracking stability and accuracy in low dose fluoroscopy. © 2012 American Association of Physicists in Medicine.

Computer Vision for Artificially Intelligent Robotic Systems

NASA Astrophysics Data System (ADS)

Ma, Chialo; Ma, Yung-Lung

1987-04-01

In this paper An Acoustic Imaging Recognition System (AIRS) will be introduced which is installed on an Intelligent Robotic System and can recognize different type of Hand tools' by Dynamic pattern recognition. The dynamic pattern recognition is approached by look up table method in this case, the method can save a lot of calculation time and it is practicable. The Acoustic Imaging Recognition System (AIRS) is consist of four parts -- position control unit, pulse-echo signal processing unit, pattern recognition unit and main control unit. The position control of AIRS can rotate an angle of ±5 degree Horizental and Vertical seperately, the purpose of rotation is to find the maximum reflection intensity area, from the distance, angles and intensity of the target we can decide the characteristic of this target, of course all the decision is target, of course all the decision is processed bye the main control unit. In Pulse-Echo Signal Process Unit, we ultilize the correlation method, to overcome the limitation of short burst of ultrasonic, because the Correlation system can transmit large time bandwidth signals and obtain their resolution and increased intensity through pulse compression in the correlation receiver. The output of correlator is sampled and transfer into digital data by u law coding method, and this data together with delay time T, angle information OH, eV will be sent into main control unit for further analysis. The recognition process in this paper, we use dynamic look up table method, in this method at first we shall set up serval recognition pattern table and then the new pattern scanned by Transducer array will be devided into serval stages and compare with the sampling table. The comparison is implemented by dynamic programing and Markovian process. All the hardware control signals, such as optimum delay time for correlator receiver, horizental and vertical rotation angle for transducer plate, are controlled by the Main Control Unit, the Main Control Unit also handles the pattern recognition process. The distance from the target to the transducer plate is limitted by the power and beam angle of transducer elements, in this AIRS Model, we use a narrow beam transducer and it's input voltage is 50V p-p. A RobOt equipped with AIRS can not only measure the distance from the target but also recognize a three dimensional image of target from the image lab of Robot memory. Indexitems, Accoustic System, Supersonic transducer, Dynamic programming, Look-up-table, Image process, pattern Recognition, Quad Tree, Quadappoach.

Improved Performance Characteristics For Indium Antimonide Photovoltaic Detector Arrays Using A FET-Switched Multiplexing Technique

NASA Astrophysics Data System (ADS)

Ma, Yung-Lung; Ma, Chialo

1987-03-01

In this paper An Acoustic Imaging Recognition System (AIRS) will be introduced which is installed on an Intelligent Robotic System and can recognize different type of Hand tools' by Dynamic pattern recognition. The dynamic pattern recognition is approached by look up table method in this case, the method can save a lot of calculation time and it is practicable. The Acoustic Imaging Recognition System (AIRS) is consist of four parts _ position control unit, pulse-echo signal processing unit, pattern recognition unit and main control unit. The position control of AIRS can rotate an angle of ±5 degree Horizental and Vertical seperately, the purpose of rotation is to find the maximum reflection intensity area, from the distance, angles and intensity of the target we can decide the characteristic of this target, of course all the decision is target, of course all the decision is processed by the main control unit. In Pulse-Echo Signal Process Unit, we utilize the correlation method, to overcome the limitation of short burst of ultrasonic, because the Correlation system can transmit large time bandwidth signals and obtain their resolution and increased intensity through pulse compression in the correlation receiver. The output of correlator is sampled and transfer into digital data by p law coding method, and this data together with delay time T, angle information eH, eV will be sent into main control unit for further analysis. The recognition process in this paper, we use dynamic look up table method, in this method at first we shall set up serval recognition pattern table and then the new pattern scanned by Transducer array will be devided into serval stages and compare with the sampling table. The comparison is implemented by dynamic programing and Markovian process. All the hardware control signals, such as optimum delay time for correlator receiver, horizental and vertical rotation angle for transducer plate, are controlled by the Main Control Unit, the Main Control Unit also handles the pattern recognition process. The distance from the target to the transducer plate is limitted by the power and beam angle of transducer elements, in this AIRS Models, we use a narrow beam transducer and it's input voltage is 50V p-p. A Robot equipped with AIRS can not only measure the distance from the target but also recognize a three dimensional image of target from the image lab of Robot memory. Indexitems, Accoustic System, Supersonic transducer, Dynamic programming, Look-up-table, Image process, pattern Recognition, Quad Tree, Quadappoach.

Analysis of Spatial Point Patterns in Nuclear Biology

PubMed Central

Weston, David J.; Adams, Niall M.; Russell, Richard A.; Stephens, David A.; Freemont, Paul S.

2012-01-01

There is considerable interest in cell biology in determining whether, and to what extent, the spatial arrangement of nuclear objects affects nuclear function. A common approach to address this issue involves analyzing a collection of images produced using some form of fluorescence microscopy. We assume that these images have been successfully pre-processed and a spatial point pattern representation of the objects of interest within the nuclear boundary is available. Typically in these scenarios, the number of objects per nucleus is low, which has consequences on the ability of standard analysis procedures to demonstrate the existence of spatial preference in the pattern. There are broadly two common approaches to look for structure in these spatial point patterns. First a spatial point pattern for each image is analyzed individually, or second a simple normalization is performed and the patterns are aggregated. In this paper we demonstrate using synthetic spatial point patterns drawn from predefined point processes how difficult it is to distinguish a pattern from complete spatial randomness using these techniques and hence how easy it is to miss interesting spatial preferences in the arrangement of nuclear objects. The impact of this problem is also illustrated on data related to the configuration of PML nuclear bodies in mammalian fibroblast cells. PMID:22615822

Personal Computer (PC) based image processing applied to fluid mechanics

NASA Technical Reports Server (NTRS)

Cho, Y.-C.; Mclachlan, B. G.

1987-01-01

A PC based image processing system was employed to determine the instantaneous velocity field of a two-dimensional unsteady flow. The flow was visualized using a suspension of seeding particles in water, and a laser sheet for illumination. With a finite time exposure, the particle motion was captured on a photograph as a pattern of streaks. The streak pattern was digitized and processed using various imaging operations, including contrast manipulation, noise cleaning, filtering, statistical differencing, and thresholding. Information concerning the velocity was extracted from the enhanced image by measuring the length and orientation of the individual streaks. The fluid velocities deduced from the randomly distributed particle streaks were interpolated to obtain velocities at uniform grid points. For the interpolation a simple convolution technique with an adaptive Gaussian window was used. The results are compared with a numerical prediction by a Navier-Stokes computation.

Study on the generation technology of Li brocade pattern mutant genes based on the AI and Java technology

NASA Astrophysics Data System (ADS)

Zhou, Yuping; Zhang, Qi

2018-04-01

In the information environment, digital and information processing to Li brocade patterns reveals an important means of Li ethnic style and inheriting the national culture. Adobe Illustrator CS3 and Java language were used in the paper to make "variation" processing to Li brocade patterns, and generate "Li brocade pattern mutant genes". The generation of pattern mutant genes includes color mutation, shape mutation, adding and missing transform, and twisted transform, etc. Research shows that Li brocade pattern mutant genes can be generated by using the Adobe Illustrator CS3 and the image processing tools of Java language edit, etc.

Skeletonization of gray-scale images by gray weighted distance transform

NASA Astrophysics Data System (ADS)

Qian, Kai; Cao, Siqi; Bhattacharya, Prabir

1997-07-01

In pattern recognition, thinning algorithms are often a useful tool to represent a digital pattern by means of a skeletonized image, consisting of a set of one-pixel-width lines that highlight the significant features interest in applying thinning directly to gray-scale images, motivated by the desire of processing images characterized by meaningful information distributed over different levels of gray intensity. In this paper, a new algorithm is presented which can skeletonize both black-white and gray pictures. This algorithm is based on the gray distance transformation and can be used to process any non-well uniformly distributed gray-scale picture and can preserve the topology of original picture. This process includes a preliminary phase of investigation in the 'hollows' in the gray-scale image; these hollows are considered not as topological constrains for the skeleton structure depending on their statistically significant depth. This algorithm can also be executed on a parallel machine as all the operations are executed in local. Some examples are discussed to illustrate the algorithm.

Pattern-Recognition Processor Using Holographic Photopolymer

NASA Technical Reports Server (NTRS)

Chao, Tien-Hsin; Cammack, Kevin

2006-01-01

proposed joint-transform optical correlator (JTOC) would be capable of operating as a real-time pattern-recognition processor. The key correlation-filter reading/writing medium of this JTOC would be an updateable holographic photopolymer. The high-resolution, high-speed characteristics of this photopolymer would enable pattern-recognition processing to occur at a speed three orders of magnitude greater than that of state-of-the-art digital pattern-recognition processors. There are many potential applications in biometric personal identification (e.g., using images of fingerprints and faces) and nondestructive industrial inspection. In order to appreciate the advantages of the proposed JTOC, it is necessary to understand the principle of operation of a conventional JTOC. In a conventional JTOC (shown in the upper part of the figure), a collimated laser beam passes through two side-by-side spatial light modulators (SLMs). One SLM displays a real-time input image to be recognized. The other SLM displays a reference image from a digital memory. A Fourier-transform lens is placed at its focal distance from the SLM plane, and a charge-coupled device (CCD) image detector is placed at the back focal plane of the lens for use as a square-law recorder. Processing takes place in two stages. In the first stage, the CCD records the interference pattern between the Fourier transforms of the input and reference images, and the pattern is then digitized and saved in a buffer memory. In the second stage, the reference SLM is turned off and the interference pattern is fed back to the input SLM. The interference pattern thus becomes Fourier-transformed, yielding at the CCD an image representing the joint-transform correlation between the input and reference images. This image contains a sharp correlation peak when the input and reference images are matched. The drawbacks of a conventional JTOC are the following: The CCD has low spatial resolution and is not an ideal square-law detector for the purpose of holographic recording of interference fringes. A typical state-of-the-art CCD has a pixel-pitch limited resolution of about 100 lines/mm. In contrast, the holographic photopolymer to be used in the proposed JTOC offers a resolution > 2,000 lines/mm. In addition to being disadvantageous in itself, the low resolution of the CCD causes overlap of a DC term and the desired correlation term in the output image. This overlap severely limits the correlation signal-to-noise ratio. The two-stage nature of the process limits the achievable throughput rate. A further limit is imposed by the low frame rate (typical video rates) of low- and medium-cost commercial CCDs.

An image analysis of TLC patterns for quality control of saffron based on soil salinity effect: A strategy for data (pre)-processing.

PubMed

Sereshti, Hassan; Poursorkh, Zahra; Aliakbarzadeh, Ghazaleh; Zarre, Shahin; Ataolahi, Sahar

2018-01-15

Quality of saffron, a valuable food additive, could considerably affect the consumers' health. In this work, a novel preprocessing strategy for image analysis of saffron thin layer chromatographic (TLC) patterns was introduced. This includes performing a series of image pre-processing techniques on TLC images such as compression, inversion, elimination of general baseline (using asymmetric least squares (AsLS)), removing spots shift and concavity (by correlation optimization warping (COW)), and finally conversion to RGB chromatograms. Subsequently, an unsupervised multivariate data analysis including principal component analysis (PCA) and k-means clustering was utilized to investigate the soil salinity effect, as a cultivation parameter, on saffron TLC patterns. This method was used as a rapid and simple technique to obtain the chemical fingerprints of saffron TLC images. Finally, the separated TLC spots were chemically identified using high-performance liquid chromatography-diode array detection (HPLC-DAD). Accordingly, the saffron quality from different areas of Iran was evaluated and classified. Copyright © 2017 Elsevier Ltd. All rights reserved.

Absolute Position Encoders With Vertical Image Binning

NASA Technical Reports Server (NTRS)

Leviton, Douglas B.

2005-01-01

Improved optoelectronic patternrecognition encoders that measure rotary and linear 1-dimensional positions at conversion rates (numbers of readings per unit time) exceeding 20 kHz have been invented. Heretofore, optoelectronic pattern-recognition absoluteposition encoders have been limited to conversion rates <15 Hz -- too low for emerging industrial applications in which conversion rates ranging from 1 kHz to as much as 100 kHz are required. The high conversion rates of the improved encoders are made possible, in part, by use of vertically compressible or binnable (as described below) scale patterns in combination with modified readout sequences of the image sensors [charge-coupled devices (CCDs)] used to read the scale patterns. The modified readout sequences and the processing of the images thus read out are amenable to implementation by use of modern, high-speed, ultra-compact microprocessors and digital signal processors or field-programmable gate arrays. This combination of improvements makes it possible to greatly increase conversion rates through substantial reductions in all three components of conversion time: exposure time, image-readout time, and image-processing time.

Computer-aided diagnosis of splenic enlargement using wave pattern of spleen in abdominal CT images

NASA Astrophysics Data System (ADS)

Seong, Won; Cho, June-Sik; Noh, Seung-Moo; Park, Jong Won

2006-03-01

It is known that the spleen accompanied by liver cirrhosis is hypertrophied or enlarged. We have examined a wave pattern at the left boundary of spleen on the abdominal CT images having liver cirrhosis, and found that they are different from those on the images having a normal liver. It is noticed that the abdominal CT images of patient with liver cirrhosis shows strong bending in the wave pattern. In the case of normal liver, the images may also have a wave pattern, but its bends are not strong. Therefore, the total waving area of the spleen with liver cirrhosis is found to be greater than that of the spleen with a normal liver. Moreover, we found that the waves of the spleen from the image with liver cirrhosis have the higher degree of circularity compared to the normal liver case. Based on the two observations above, we propose an automatic method to diagnose splenic enlargement by using the wave pattern of the spleen in abdominal CT images. The proposed automatic method improves the diagnostic performance compared with the conventional process based on the size of spleen.

Applying local binary patterns in image clustering problems

NASA Astrophysics Data System (ADS)

Skorokhod, Nikolai N.; Elizarov, Alexey I.

2017-11-01

Due to the fact that the cloudiness plays a critical role in the Earth radiative balance, the study of the distribution of different types of clouds and their movements is relevant. The main sources of such information are artificial satellites that provide data in the form of images. The most commonly used method of solving tasks of processing and classification of images of clouds is based on the description of texture features. The use of a set of local binary patterns is proposed to describe the texture image.

Automatic differentiation of melanoma and clark nevus skin lesions

NASA Astrophysics Data System (ADS)

LeAnder, R. W.; Kasture, A.; Pandey, A.; Umbaugh, S. E.

2007-03-01

Skin cancer is the most common form of cancer in the United States. Although melanoma accounts for just 11% of all types of skin cancer, it is responsible for most of the deaths, claiming more than 7910 lives annually. Melanoma is visually difficult for clinicians to differentiate from Clark nevus lesions which are benign. The application of pattern recognition techniques to these lesions may be useful as an educational tool for teaching physicians to differentiate lesions, as well as for contributing information about the essential optical characteristics that identify them. Purpose: This study sought to find the most effective features to extract from melanoma, melanoma in situ and Clark nevus lesions, and to find the most effective pattern-classification criteria and algorithms for differentiating those lesions, using the Computer Vision and Image Processing Tools (CVIPtools) software package. Methods: Due to changes in ambient lighting during the photographic process, color differences between images can occur. These differences were minimized by capturing dermoscopic images instead of photographic images. Differences in skin color between patients were minimized via image color normalization, by converting original color images to relative-color images. Relative-color images also helped minimize changes in color that occur due to changes in the photographic and digitization processes. Tumors in the relative-color images were segmented and morphologically filtered. Filtered, relative-color, tumor features were then extracted and various pattern-classification schemes were applied. Results: Experimentation resulted in four useful pattern classification methods, the best of which was an overall classification rate of 100% for melanoma and melanoma in situ (grouped) and 60% for Clark nevus. Conclusion: Melanoma and melanoma in situ have feature parameters and feature values that are similar enough to be considered one class of tumor that significantly differs from Clark nevus. Consequently, grouping melanoma and melanoma in situ together achieves the best results in classifying and automatically differentiating melanoma from Clark nevus lesions.

Intelligent Vision On The SM9O Mini-Computer Basis And Applications

NASA Astrophysics Data System (ADS)

Hawryszkiw, J.

1985-02-01

Distinction has to be made between image processing and vision Image processing finds its roots in the strong tradition of linear signal processing and promotes geometrical transform techniques, such as fi I tering , compression, and restoration. Its purpose is to transform an image for a human observer to easily extract from that image information significant for him. For example edges after a gradient operator, or a specific direction after a directional filtering operation. Image processing consists in fact in a set of local or global space-time transforms. The interpretation of the final image is done by the human observer. The purpose of vision is to extract the semantic content of the image. The machine can then understand that content, and run a process of decision, which turns into an action. Thus, intel I i gent vision depends on - Image processing - Pattern recognition - Artificial intel I igence

Registration of interferometric SAR images

NASA Technical Reports Server (NTRS)

Lin, Qian; Vesecky, John F.; Zebker, Howard A.

1992-01-01

Interferometric synthetic aperture radar (INSAR) is a new way of performing topography mapping. Among the factors critical to mapping accuracy is the registration of the complex SAR images from repeated orbits. A new algorithm for registering interferometric SAR images is presented. A new figure of merit, the average fluctuation function of the phase difference image, is proposed to evaluate the fringe pattern quality. The process of adjusting the registration parameters according to the fringe pattern quality is optimized through a downhill simplex minimization algorithm. The results of applying the proposed algorithm to register two pairs of Seasat SAR images with a short baseline (75 m) and a long baseline (500 m) are shown. It is found that the average fluctuation function is a very stable measure of fringe pattern quality allowing very accurate registration.

Methods and Materials for Selective Modification of Photopatterned Polymer Films.

DTIC Science & Technology

1999-06-28

reactivity templates (see below) formed by patterned irradiation of polymer films. In particular, the invention describes binding materials and processes ...image of the attached functional group) or that region of the polymer film left unexposed and unchanged during the aforementioned patterning process ...invention are accomplished by the structures and processes hereinafter 15 described. An aspect of the present invention is a process for modifying a

Investigation of computer-aided colonic crypt pattern analysis

NASA Astrophysics Data System (ADS)

Qi, Xin; Pan, Yinsheng; Sivak, Michael V., Jr.; Olowe, Kayode; Rollins, Andrew M.

2007-02-01

Colorectal cancer is the second leading cause of cancer-related death in the United States. Approximately 50% of these deaths could be prevented by earlier detection through screening. Magnification chromoendoscopy is a technique which utilizes tissue stains applied to the gastrointestinal mucosa and high-magnification endoscopy to better visualize and characterize lesions. Prior studies have shown that shapes of colonic crypts change with disease and show characteristic patterns. Current methods for assessing colonic crypt patterns are somewhat subjective and not standardized. Computerized algorithms could be used to standardize colonic crypt pattern assessment. We have imaged resected colonic mucosa in vitro (N = 70) using methylene blue dye and a surgical microscope to approximately simulate in vivo imaging with magnification chromoendoscopy. We have developed a method of computerized processing to analyze the crypt patterns in the images. The quantitative image analysis consists of three steps. First, the crypts within the region of interest of colonic tissue are semi-automatically segmented using watershed morphological processing. Second, crypt size and shape parameters are extracted from the segmented crypts. Third, each sample is assigned to a category according to the Kudo criteria. The computerized classification is validated by comparison with human classification using the Kudo classification criteria. The computerized colonic crypt pattern analysis algorithm will enable a study of in vivo magnification chromoendoscopy of colonic crypt pattern correlated with risk of colorectal cancer. This study will assess the feasibility of screening and surveillance of the colon using magnification chromoendoscopy.

A Practical Approach To Lift-Off

NASA Astrophysics Data System (ADS)

Jones, Susan K.; Chapman, Richard C.; Pavelchek, Edward K.

1987-08-01

Lift-off technology provides an alternate metal patterning technology to that of subtractive etching. In this raper, we describe an image reversal process which provides a practical means for reliably producing resist stencils which are required for successful lift-off in a 2.0 μm metal pitch CMOS process, as well as for experimental submicron processing. Experimental data and PROSIM simulations are presented to show the effects of patterning exposure dose, flood exposure dose, develop time, and focus parameters on resist linewidths as well as for control of resist retrograde (undercut) sidewall angles. Deposition and subsequent lift-off of Al/Cu alloys and sandwich metallizations is demonstrated. Because the image reversal process enables pattern definition at the top of the resist film, it is demonstrated that thicker resist films can be used to produce finer resolution of lift-off stencils over topography than would have been expected without resorting to multilayer resist structures.

Imaging of the meninges and the extra-axial spaces.

PubMed

Kirmi, Olga; Sheerin, Fintan; Patel, Neel

2009-12-01

The separate meningeal layers and extraaxial spaces are complex and can only be differentiated by pathologic processes on imaging. Differentiation of the location of such processes can be achieved using different imaging modalities. In this pictorial review we address the imaging techniques, enhancement and location patterns, and disease spread that will promote accurate localization of the pathology, thus improving accuracy of diagnosis. Typical and unusual magnetic resonance (MR), computed tomography (CT), and ultrasound imaging findings of many conditions affecting these layers and spaces are described.

New Subarray Readout Patterns for the ACS Wide Field Channel

NASA Astrophysics Data System (ADS)

Golimowski, D.; Anderson, J.; Arslanian, S.; Chiaberge, M.; Grogin, N.; Lim, Pey Lian; Lupie, O.; McMaster, M.; Reinhart, M.; Schiffer, F.; Serrano, B.; Van Marshall, M.; Welty, A.

2017-04-01

At the start of Cycle 24, the original CCD-readout timing patterns used to generate ACS Wide Field Channel (WFC) subarray images were replaced with new patterns adapted from the four-quadrant readout pattern used to generate full-frame WFC images. The primary motivation for this replacement was a substantial reduction of observatory and staff resources needed to support WFC subarray bias calibration, which became a new and challenging obligation after the installation of the ACS CCD Electronics Box Replacement during Servicing Mission 4. The new readout patterns also improve the overall efficiency of observing with WFC subarrays and enable the processing of subarray images through stages of the ACS data calibration pipeline (calacs) that were previously restricted to full-frame WFC images. The new readout patterns replace the original 512×512, 1024×1024, and 2048×2046-pixel subarrays with subarrays having 2048 columns and 512, 1024, and 2048 rows, respectively. Whereas the original square subarrays were limited to certain WFC quadrants, the new rectangular subarrays are available in all four quadrants. The underlying bias structure of the new subarrays now conforms with those of the corresponding regions of the full-frame image, which allows raw frames in all image formats to be calibrated using one contemporaneous full-frame "superbias" reference image. The original subarrays remain available for scientific use, but calibration of these image formats is no longer supported by STScI.

Thin layer imaging process for microlithography using radiation at strongly attenuated wavelengths

DOEpatents

Wheeler, David R.

2004-01-06

A method for patterning of resist surfaces which is particularly advantageous for systems having low photon flux and highly energetic, strongly attenuated radiation. A thin imaging layer is created with uniform silicon distribution in a bilayer format. An image is formed by exposing selected regions of the silylated imaging layer to radiation. The radiation incident upon the silyliated resist material results in acid generation which either catalyzes cleavage of Si--O bonds to produce moieties that are volatile enough to be driven off in a post exposure bake step or produces a resist material where the exposed portions of the imaging layer are soluble in a basic solution, thereby desilylating the exposed areas of the imaging layer. The process is self limiting due to the limited quantity of silyl groups within each region of the pattern. Following the post exposure bake step, an etching step, generally an oxygen plasma etch, removes the resist material from the de-silylated areas of the imaging layer.

Geometry Of Discrete Sets With Applications To Pattern Recognition

NASA Astrophysics Data System (ADS)

Sinha, Divyendu

1990-03-01

In this paper we present a new framework for discrete black and white images that employs only integer arithmetic. This framework is shown to retain the essential characteristics of the framework for Euclidean images. We propose two norms and based on them, the permissible geometric operations on images are defined. The basic invariants of our geometry are line images, structure of image and the corresponding local property of strong attachment of pixels. The permissible operations also preserve the 3x3 neighborhoods, area, and perpendicularity. The structure, patterns, and the inter-pattern gaps in a discrete image are shown to be conserved by the magnification and contraction process. Our notions of approximate congruence, similarity and symmetry are similar, in character, to the corresponding notions, for Euclidean images [1]. We mention two discrete pattern recognition algorithms that work purely with integers, and which fit into our framework. Their performance has been shown to be at par with the performance of traditional geometric schemes. Also, all the undesired effects of finite length registers in fixed point arithmetic that plague traditional algorithms, are non-existent in this family of algorithms.

Hyperspectral Imaging Using Flexible Endoscopy for Laryngeal Cancer Detection

PubMed Central

Regeling, Bianca; Thies, Boris; Gerstner, Andreas O. H.; Westermann, Stephan; Müller, Nina A.; Bendix, Jörg; Laffers, Wiebke

2016-01-01

Hyperspectral imaging (HSI) is increasingly gaining acceptance in the medical field. Up until now, HSI has been used in conjunction with rigid endoscopy to detect cancer in vivo. The logical next step is to pair HSI with flexible endoscopy, since it improves access to hard-to-reach areas. While the flexible endoscope’s fiber optic cables provide the advantage of flexibility, they also introduce an interfering honeycomb-like pattern onto images. Due to the substantial impact this pattern has on locating cancerous tissue, it must be removed before the HS data can be further processed. Thereby, the loss of information is to minimize avoiding the suppression of small-area variations of pixel values. We have developed a system that uses flexible endoscopy to record HS cubes of the larynx and designed a special filtering technique to remove the honeycomb-like pattern with minimal loss of information. We have confirmed its feasibility by comparing it to conventional filtering techniques using an objective metric and by applying unsupervised and supervised classifications to raw and pre-processed HS cubes. Compared to conventional techniques, our method successfully removes the honeycomb-like pattern and considerably improves classification performance, while preserving image details. PMID:27529255

Hyperspectral Imaging Using Flexible Endoscopy for Laryngeal Cancer Detection.

PubMed

Regeling, Bianca; Thies, Boris; Gerstner, Andreas O H; Westermann, Stephan; Müller, Nina A; Bendix, Jörg; Laffers, Wiebke

2016-08-13

Hyperspectral imaging (HSI) is increasingly gaining acceptance in the medical field. Up until now, HSI has been used in conjunction with rigid endoscopy to detect cancer in vivo. The logical next step is to pair HSI with flexible endoscopy, since it improves access to hard-to-reach areas. While the flexible endoscope's fiber optic cables provide the advantage of flexibility, they also introduce an interfering honeycomb-like pattern onto images. Due to the substantial impact this pattern has on locating cancerous tissue, it must be removed before the HS data can be further processed. Thereby, the loss of information is to minimize avoiding the suppression of small-area variations of pixel values. We have developed a system that uses flexible endoscopy to record HS cubes of the larynx and designed a special filtering technique to remove the honeycomb-like pattern with minimal loss of information. We have confirmed its feasibility by comparing it to conventional filtering techniques using an objective metric and by applying unsupervised and supervised classifications to raw and pre-processed HS cubes. Compared to conventional techniques, our method successfully removes the honeycomb-like pattern and considerably improves classification performance, while preserving image details.

Precision process calibration and CD predictions for low-k1 lithography

NASA Astrophysics Data System (ADS)

Chen, Ting; Park, Sangbong; Berger, Gabriel; Coskun, Tamer H.; de Vocht, Joep; Chen, Fung; Yu, Linda; Hsu, Stephen; van den Broeke, Doug; Socha, Robert; Park, Jungchul; Gronlund, Keith; Davis, Todd; Plachecki, Vince; Harris, Tom; Hansen, Steve; Lambson, Chuck

2005-06-01

Leading resist calibration for sub-0.3 k1 lithography demands accuracy <2nm for CD through pitch. An accurately calibrated resist process is the prerequisite for establishing production-worthy manufacturing under extreme low k1. From an integrated imaging point of view, the following key components must be simultaneously considered during the calibration - high numerical aperture (NA>0.8) imaging characteristics, customized illuminations (measured vs. modeled pupil profiles), resolution enhancement technology (RET) mask with OPC, reticle metrology, and resist thin film substrate. For imaging at NA approaching unity, polarized illumination can impact significantly the contrast formation in the resist film stack, and therefore it is an important factor to consider in the CD-based resist calibration. For aggressive DRAM memory core designs at k1<0.3, pattern-specific illumination optimization has proven to be critical for achieving the required imaging performance. Various optimization techniques from source profile optimization with fixed mask design to the combined source and mask optimization have been considered for customer designs and available imaging capabilities. For successful low-k1 process development, verification of the optimization results can only be made with a sufficiently tunable resist model that can predicate the wafer printing accurately under various optimized process settings. We have developed, for resist patterning under aggressive low-k1 conditions, a novel 3D diffusion model equipped with double-Gaussian convolution in each dimension. Resist calibration with the new diffusion model has demonstrated a fitness and CD predication accuracy that rival or outperform the traditional 3D physical resist models. In this work, we describe our empirical approach to achieving the nm-scale precision for advanced lithography process calibrations, using either measured 1D CD through-pitch or 2D memory core patterns. We show that for ArF imaging, the current resist development and diffusion modeling can readily achieve ~1-2nm max CD errors for common 1D through-pitch and aggressive 2D memory core resist patterns. Sensitivities of the calibrated models to various process parameters are analyzed, including the comparison between the measured and modeled (Gaussian or GRAIL) pupil profiles. We also report our preliminary calibration results under selected polarized illumination conditions.

High speed stereovision setup for position and motion estimation of fertilizer particles leaving a centrifugal spreader.

PubMed

Hijazi, Bilal; Cool, Simon; Vangeyte, Jürgen; Mertens, Koen C; Cointault, Frédéric; Paindavoine, Michel; Pieters, Jan G

2014-11-13

A 3D imaging technique using a high speed binocular stereovision system was developed in combination with corresponding image processing algorithms for accurate determination of the parameters of particles leaving the spinning disks of centrifugal fertilizer spreaders. Validation of the stereo-matching algorithm using a virtual 3D stereovision simulator indicated an error of less than 2 pixels for 90% of the particles. The setup was validated using the cylindrical spread pattern of an experimental spreader. A 2D correlation coefficient of 90% and a Relative Error of 27% was found between the experimental results and the (simulated) spread pattern obtained with the developed setup. In combination with a ballistic flight model, the developed image acquisition and processing algorithms can enable fast determination and evaluation of the spread pattern which can be used as a tool for spreader design and precise machine calibration.

The current and ideal state of anatomic pathology patient safety.

PubMed

Raab, Stephen Spencer

2014-01-01

An anatomic pathology diagnostic error may be secondary to a number of active and latent technical and/or cognitive components, which may occur anywhere along the total testing process in clinical and/or laboratory domains. For the pathologist interpretive steps of diagnosis, we examine Kahneman's framework of slow and fast thinking to explain different causes of error in precision (agreement) and in accuracy (truth). The pathologist cognitive diagnostic process involves image pattern recognition and a slow thinking error may be caused by the application of different rationally-constructed mental maps of image criteria/patterns by different pathologists. This type of error is partly related to a system failure in standardizing the application of these maps. A fast thinking error involves the flawed leap from image pattern to incorrect diagnosis. In the ideal state, anatomic pathology systems would target these cognitive error causes as well as the technical latent factors that lead to error.

Fast image processing with a microcomputer applied to speckle photography

NASA Astrophysics Data System (ADS)

Erbeck, R.

1985-11-01

An automated image recognition system is described for speckle photography investigations in fluid dynamics. The system is employed for characterizing the pattern of interference fringes obtained using speckle interferometry. A rotating ground glass serves as a screen on which laser light passing through a specklegraph plate, the flow and a compensation plate (CP) is shone to produce a compensated Young's pattern. The image produced on the ground glass is photographed by a video camera whose signal is digitized and processed through a microcomputer using a 6502 CPU chip. The normalized correlation function of the intensity is calculated in two directions of the recorded pattern to obtain the wavelength and the light deflection angle. The system has a capability of one picture every two seconds. Sample data are provided for a free jet of CO2 issuing into air in both laminar and turbulent form.

Unsupervised Neural Network Quantifies the Cost of Visual Information Processing.

PubMed

Orbán, Levente L; Chartier, Sylvain

2015-01-01

Untrained, "flower-naïve" bumblebees display behavioural preferences when presented with visual properties such as colour, symmetry, spatial frequency and others. Two unsupervised neural networks were implemented to understand the extent to which these models capture elements of bumblebees' unlearned visual preferences towards flower-like visual properties. The computational models, which are variants of Independent Component Analysis and Feature-Extracting Bidirectional Associative Memory, use images of test-patterns that are identical to ones used in behavioural studies. Each model works by decomposing images of floral patterns into meaningful underlying factors. We reconstruct the original floral image using the components and compare the quality of the reconstructed image to the original image. Independent Component Analysis matches behavioural results substantially better across several visual properties. These results are interpreted to support a hypothesis that the temporal and energetic costs of information processing by pollinators served as a selective pressure on floral displays: flowers adapted to pollinators' cognitive constraints.

Comparison of eye imaging pattern recognition using neural network

NASA Astrophysics Data System (ADS)

Bukhari, W. M.; Syed A., M.; Nasir, M. N. M.; Sulaima, M. F.; Yahaya, M. S.

2015-05-01

The beauty of eye recognition system that it is used in automatic identifying and verifies a human weather from digital images or video source. There are various behaviors of the eye such as the color of the iris, size of pupil and shape of the eye. This study represents the analysis, design and implementation of a system for recognition of eye imaging. All the eye images that had been captured from the webcam in RGB format must through several techniques before it can be input for the pattern and recognition processes. The result shows that the final value of weight and bias after complete training 6 eye images for one subject is memorized by the neural network system and be the reference value of the weight and bias for the testing part. The target classifies to 5 different types for 5 subjects. The eye images can recognize the subject based on the target that had been set earlier during the training process. When the values between new eye image and the eye image in the database are almost equal, it is considered the eye image is matched.

Basic research planning in mathematical pattern recognition and image analysis

NASA Technical Reports Server (NTRS)

Bryant, J.; Guseman, L. F., Jr.

1981-01-01

Fundamental problems encountered while attempting to develop automated techniques for applications of remote sensing are discussed under the following categories: (1) geometric and radiometric preprocessing; (2) spatial, spectral, temporal, syntactic, and ancillary digital image representation; (3) image partitioning, proportion estimation, and error models in object scene interference; (4) parallel processing and image data structures; and (5) continuing studies in polarization; computer architectures and parallel processing; and the applicability of "expert systems" to interactive analysis.

New techniques for fluorescence background rejection in microscopy and endoscopy

NASA Astrophysics Data System (ADS)

Ventalon, Cathie

2009-03-01

Confocal microscopy is a popular technique in the bioimaging community, mainly because it provides optical sectioning. However, its standard implementation requires 3-dimensional scanning of focused illumination throughout the sample. Efficient non-scanning alternatives have been implemented, among which the simple and well-established incoherent structured illumination microscopy (SIM) [1]. We recently proposed a similar technique, called Dynamic Speckle Illumination (DSI) microscopy, wherein the incoherent grid illumination pattern is replaced with a coherent speckle illumination pattern from a laser, taking advantage of the fact that speckle contrast is highly maintained in a scattering media, making the technique well adapted to tissue imaging [2]. DSI microscopy relies on the illumination of a sample with a sequence of dynamic speckle patterns and an image processing algorithm based only on an a priori knowledge of speckle statistics. The choice of this post-processing algorithm is crucial to obtain a good sectioning strength: in particular, we developed a novel post-processing algorithm based one wavelet pre-filtering of the raw images and obtained near-confocal fluorescence sectioning in a mouse brain labeled with GFP, with a good image quality maintained throughout a depth of ˜100 μm [3]. In the purpose of imaging fluorescent tissue at higher depth, we recently applied structured illumination to endoscopy. We used a similar set-up wherein the illumination pattern (a one-dimensional grid) is transported to the sample with an imaging fiber bundle with miniaturized objective and the fluorescence image is collected through the same bundle. Using a post-processing algorithm similar to the one previously described [3], we obtained high-quality images of a fluorescein-labeled rat colonic mucosa [4], establishing the potential of our endomicroscope for bioimaging applications. [4pt] Ref: [0pt] [1] M. A. A. Neil et al, Opt. Lett. 22, 1905 (1997) [0pt] [2] C. Ventalon et al, Opt. Lett. 30, 3350 (2005) [0pt] [3] C. Ventalon et al, Opt. Lett. 32, 1417 (2007) [0pt] [4] N. Bozinovic et al, Opt. Express 16, 8016 (2008)

Rotation and scale change invariant point pattern relaxation matching by the Hopfield neural network

NASA Astrophysics Data System (ADS)

Sang, Nong; Zhang, Tianxu

1997-12-01

Relaxation matching is one of the most relevant methods for image matching. The original relaxation matching technique using point patterns is sensitive to rotations and scale changes. We improve the original point pattern relaxation matching technique to be invariant to rotations and scale changes. A method that makes the Hopfield neural network perform this matching process is discussed. An advantage of this is that the relaxation matching process can be performed in real time with the neural network's massively parallel capability to process information. Experimental results with large simulated images demonstrate the effectiveness and feasibility of the method to perform point patten relaxation matching invariant to rotations and scale changes and the method to perform this matching by the Hopfield neural network. In addition, we show that the method presented can be tolerant to small random error.

Strategies for the Segmentation of Subcutaneous Vascular Patterns in Thermographic Images

NASA Astrophysics Data System (ADS)

Chan, Eric K. Y.; Pearce, John A.

1989-05-01

Computer-assisted segmentation of vascular patterns in thermographic images provides the clinician with graphic outlines of thermally significant subcutaneous blood vessels. Segmentation strategies compared here consist of image smoothing protocols followed by thresholding and zero-crossing edge detectors. Median prefiltering followed by the Frei-Chen algorithm gave the most reproducible results, with an execution time of 143 seconds for 256 X 256 images. The Laplacian of Gaussian operator was not suitable due to streak artifacts in the thermographic imaging system. This computerized process may be adopted in a fast paced clinical environment to aid in the diagnosis and assessment of peripheral circulatory diseases, Raynaud's Disease3, phlebitis, varicose veins, as well as diseases of the autonomic nervous system. The same methodology may be applied to enhance the appearance of abnormal breast vascular patterns, and hence serve as an adjunct to mammography in the diagnosis of breast cancer. The automatically segmented vascular patterns, which have a hand drawn appearance, may also be used as a data reduction precursor to higher level pattern analysis and classification tasks.

Further development of image processing algorithms to improve detectability of defects in Sonic IR NDE

NASA Astrophysics Data System (ADS)

Obeidat, Omar; Yu, Qiuye; Han, Xiaoyan

2017-02-01

Sonic Infrared imaging (SIR) technology is a relatively new NDE technique that has received significant acceptance in the NDE community. SIR NDE is a super-fast, wide range NDE method. The technology uses short pulses of ultrasonic excitation together with infrared imaging to detect defects in the structures under inspection. Defects become visible to the IR camera when the temperature in the crack vicinity increases due to various heating mechanisms in the specimen. Defect detection is highly affected by noise levels as well as mode patterns in the image. Mode patterns result from the superposition of sonic waves interfering within the specimen during the application of sound pulse. Mode patterns can be a serious concern, especially in composite structures. Mode patterns can either mimic real defects in the specimen, or alternatively, hide defects if they overlap. In last year's QNDE, we have presented algorithms to improve defects detectability in severe noise. In this paper, we will present our development of algorithms on defect extraction targeting specifically to mode patterns in SIR images.

Sensitivity to image recurrence across eye-movement-like image transitions through local serial inhibition in the retina

PubMed Central

Krishnamoorthy, Vidhyasankar; Weick, Michael; Gollisch, Tim

2017-01-01

Standard models of stimulus encoding in the retina postulate that image presentations activate neurons according to the increase of preferred contrast inside the receptive field. During natural vision, however, images do not arrive in isolation, but follow each other rapidly, separated by sudden gaze shifts. We here report that, contrary to standard models, specific ganglion cells in mouse retina are suppressed after a rapid image transition by changes in visual patterns across the transition, but respond with a distinct spike burst when the same pattern reappears. This sensitivity to image recurrence depends on opposing effects of glycinergic and GABAergic inhibition and can be explained by a circuit of local serial inhibition. Rapid image transitions thus trigger a mode of operation that differs from the processing of simpler stimuli and allows the retina to tag particular image parts or to detect transition types that lead to recurring stimulus patterns. DOI: http://dx.doi.org/10.7554/eLife.22431.001 PMID:28230526

GEMAS: Spatial pattern analysis of Ni by using digital image processing techniques on European agricultural soil data

NASA Astrophysics Data System (ADS)

Jordan, Gyozo; Petrik, Attila; De Vivo, Benedetto; Albanese, Stefano; Demetriades, Alecos; Sadeghi, Martiya

2017-04-01

Several studies have investigated the spatial distribution of chemical elements in topsoil (0-20 cm) within the framework of the EuroGeoSurveys Geochemistry Expert Group's 'Geochemical Mapping of Agricultural and Grazing Land Soil' project . Most of these studies used geostatistical analyses and interpolated concentration maps, Exploratory and Compositional Data and Analysis to identify anomalous patterns. The objective of our investigation is to demonstrate the use of digital image processing techniques for reproducible spatial pattern recognition and quantitative spatial feature characterisation. A single element (Ni) concentration in agricultural topsoil is used to perform the detailed spatial analysis, and to relate these features to possible underlying processes. In this study, simple univariate statistical methods were implemented first, and Tukey's inner-fence criterion was used to delineate statistical outliers. The linear and triangular irregular network (TIN) interpolation was used on the outlier-free Ni data points, which was resampled to a 10*10 km grid. Successive moving average smoothing was applied to generalise the TIN model and to suppress small- and at the same time enhance significant large-scale features of Nickel concentration spatial distribution patterns in European topsoil. The TIN map smoothed with a moving average filter revealed the spatial trends and patterns without losing much detail, and it was used as the input into digital image processing, such as local maxima and minima determination, digital cross sections, gradient magnitude and gradient direction calculation, second derivative profile curvature calculation, edge detection, local variability assessment, lineament density and directional variogram analyses. The detailed image processing analysis revealed several NE-SW, E-W and NW-SE oriented elongated features, which coincide with different spatial parameter classes and alignment with local maxima and minima. The NE-SW oriented linear pattern is the dominant feature to the south of the last glaciation limit. Some of these linear features are parallel to the suture zone of the Iapetus Ocean, while the others follow the Alpine and Carpathian Chains. The highest variability zones of Ni concentration in topsoil are located in the Alps and in the Balkans where mafic and ultramafic rocks outcrop. The predominant NE-SW oriented pattern is also captured by the strong anisotropy in the semi-variograms in this direction. A single major E-W oriented north-facing feature runs along the southern border of the last glaciation zone. This zone also coincides with a series of local maxima in Ni concentration along the glaciofluvial deposits. The NW-SE elongated spatial features are less dominant and are located in the Pyrenees and Scandinavia. This study demonstrates the efficiency of systematic image processing analysis in identifying and characterising spatial geochemical patterns that often remain uncovered by the usual visual map interpretation techniques.

Analysis of Variance in Statistical Image Processing

NASA Astrophysics Data System (ADS)

Kurz, Ludwik; Hafed Benteftifa, M.

1997-04-01

A key problem in practical image processing is the detection of specific features in a noisy image. Analysis of variance (ANOVA) techniques can be very effective in such situations, and this book gives a detailed account of the use of ANOVA in statistical image processing. The book begins by describing the statistical representation of images in the various ANOVA models. The authors present a number of computationally efficient algorithms and techniques to deal with such problems as line, edge, and object detection, as well as image restoration and enhancement. By describing the basic principles of these techniques, and showing their use in specific situations, the book will facilitate the design of new algorithms for particular applications. It will be of great interest to graduate students and engineers in the field of image processing and pattern recognition.

Digital shaded relief image of a carbonate platform (northern Great Bahama Bank): Scenery seen and unseen

NASA Astrophysics Data System (ADS)

Boss, Stephen K.

1996-11-01

A mosaic image of the northern Great Bahama Bank was created from separate gray-scale Landsat images using photo-editing and image analysis software that is commercially available for desktop computers. Measurements of pixel gray levels (relative scale from 0 to 255 referred to as digital number, DN) on the mosaic image were compared to bank-top bathymetry (determined from a network of single-channel, high-resolution seismic profiles), bottom type (coarse sand, sandy mud, barren rock, or reef determined from seismic profiles and diver observations), and vegetative cover (presence and/or absence and relative density of the marine angiosperm Thalassia testudinum determined from diver observations). Results of these analyses indicate that bank-top bathymetry is a primary control on observed pixel DN, bottom type is a secondary control on pixel DN, and vegetative cover is a tertiary influence on pixel DN. Consequently, processing of the gray-scale Landsat mosaic with a directional gradient edge-detection filter generated a physiographic shaded relief image resembling bank-top bathymetric patterns related to submerged physiographic features across the platform. The visibility of submerged karst landforms, Pleistocene eolianite ridges, islands, and possible paleo-drainage patterns created during sea-level lowstands is significantly enhanced on processed images relative to the original mosaic. Bank-margin ooid shoals, platform interior sand bodies, reef edifices, and bidirectional sand waves are features resulting from Holocene carbonate deposition that are also more clearly visible on the new physiographic images. Combined with observational data (single-channel, high-resolution seismic profiles, bottom observations by SCUBA divers, sediment and rock cores) across the northern Great Bahama Bank, these physiographic images facilitate comprehension of areal relations among antecedent platform topography, physical processes, and ensuing depositional patterns during sea-level rise.

Multi-texture local ternary pattern for face recognition

NASA Astrophysics Data System (ADS)

Essa, Almabrok; Asari, Vijayan

2017-05-01

In imagery and pattern analysis domain a variety of descriptors have been proposed and employed for different computer vision applications like face detection and recognition. Many of them are affected under different conditions during the image acquisition process such as variations in illumination and presence of noise, because they totally rely on the image intensity values to encode the image information. To overcome these problems, a novel technique named Multi-Texture Local Ternary Pattern (MTLTP) is proposed in this paper. MTLTP combines the edges and corners based on the local ternary pattern strategy to extract the local texture features of the input image. Then returns a spatial histogram feature vector which is the descriptor for each image that we use to recognize a human being. Experimental results using a k-nearest neighbors classifier (k-NN) on two publicly available datasets justify our algorithm for efficient face recognition in the presence of extreme variations of illumination/lighting environments and slight variation of pose conditions.

Line-edge roughness performance targets for EUV lithography

NASA Astrophysics Data System (ADS)

Brunner, Timothy A.; Chen, Xuemei; Gabor, Allen; Higgins, Craig; Sun, Lei; Mack, Chris A.

2017-03-01

Our paper will use stochastic simulations to explore how EUV pattern roughness can cause device failure through rare events, so-called "black swans". We examine the impact of stochastic noise on the yield of simple wiring patterns with 36nm pitch, corresponding to 7nm node logic, using a local Critical Dimension (CD)-based fail criteria Contact hole failures are examined in a similar way. For our nominal EUV process, local CD uniformity variation and local Pattern Placement Error variation was observed, but no pattern failures were seen in the modest (few thousand) number of features simulated. We degraded the image quality by incorporating Moving Standard Deviation (MSD) blurring to degrade the Image Log-Slope (ILS), and were able to find conditions where pattern failures were observed. We determined the Line Width Roughness (LWR) value as a function of the ILS. By use of an artificial "step function" image degraded by various MSD blur, we were able to extend the LWR vs ILS curve into regimes that might be available for future EUV imagery. As we decreased the image quality, we observed LWR grow and also began to see pattern failures. For high image quality, we saw CD distributions that were symmetrical and close to Gaussian in shape. Lower image quality caused CD distributions that were asymmetric, with "fat tails" on the low CD side (under-exposed) which were associated with pattern failures. Similar non-Gaussian CD distributions were associated with image conditions that caused missing contact holes, i.e. CD=0.

Recognition of pigment network pattern in dermoscopy images based on fuzzy classification of pixels.

PubMed

Garcia-Arroyo, Jose Luis; Garcia-Zapirain, Begonya

2018-01-01

One of the most relevant dermoscopic patterns is the pigment network. An innovative method of pattern recognition is presented for its detection in dermoscopy images. It consists of two steps. In the first one, by means of a supervised machine learning process and after performing the extraction of different colour and texture features, a fuzzy classification of pixels into the three categories present in the pattern's definition ("net", "hole" and "other") is carried out. This enables the three corresponding fuzzy sets to be created and, as a result, the three probability images that map them out are generated. In the second step, the pigment network pattern is characterised from a parameterisation process -derived from the system specification- and the subsequent extraction of different features calculated from the combinations of image masks extracted from the probability images, corresponding to the alpha-cuts obtained from the fuzzy sets. The method was tested on a database of 875 images -by far the largest used in the state of the art to detect pigment network- extracted from a public Atlas of Dermoscopy, obtaining AUC results of 0.912 and 88%% accuracy, with 90.71%% sensitivity and 83.44%% specificity. The main contribution of this method is the very design of the algorithm, highly innovative, which could also be used to deal with other pattern recognition problems of a similar nature. Other contributions are: 1. The good performance in discriminating between the pattern and the disturbing artefacts -which means that no prior preprocessing is required in this method- and between the pattern and other dermoscopic patterns; 2. It puts forward a new methodological approach for work of this kind, introducing the system specification as a required step prior to algorithm design and development, being this specification the basis for a required parameterisation -in the form of configurable parameters (with their value ranges) and set threshold values- of the algorithm and the subsequent conducting of the experiments. Copyright © 2017 The Authors. Published by Elsevier B.V. All rights reserved.

Content based image retrieval using local binary pattern operator and data mining techniques.

PubMed

Vatamanu, Oana Astrid; Frandeş, Mirela; Lungeanu, Diana; Mihalaş, Gheorghe-Ioan

2015-01-01

Content based image retrieval (CBIR) concerns the retrieval of similar images from image databases, using feature vectors extracted from images. These feature vectors globally define the visual content present in an image, defined by e.g., texture, colour, shape, and spatial relations between vectors. Herein, we propose the definition of feature vectors using the Local Binary Pattern (LBP) operator. A study was performed in order to determine the optimum LBP variant for the general definition of image feature vectors. The chosen LBP variant is then subsequently used to build an ultrasound image database, and a database with images obtained from Wireless Capsule Endoscopy. The image indexing process is optimized using data clustering techniques for images belonging to the same class. Finally, the proposed indexing method is compared to the classical indexing technique, which is nowadays widely used.

Implementation of sobel method to detect the seed rubber plant leaves

NASA Astrophysics Data System (ADS)

Suyanto; Munte, J.

2018-03-01

This research was conducted to develop a system that can identify and recognize the type of rubber tree based on the pattern of leaves of the plant. The steps research are started with the identification of the image data acquisition, image processing, image edge detection and identification method template matching. Edge detection is using Sobel edge detection. Pattern recognition would detect image as input and compared with other images in a database called templates. Experiments carried out in one phase, identification of the leaf edge, using a rubber plant leaf image 14 are superior and 5 for each type of test images (clones) of the plant. From the experimental results obtained by the recognition rate of 91.79%.

Automated image analysis for quantification of reactive oxygen species in plant leaves.

PubMed

Sekulska-Nalewajko, Joanna; Gocławski, Jarosław; Chojak-Koźniewska, Joanna; Kuźniak, Elżbieta

2016-10-15

The paper presents an image processing method for the quantitative assessment of ROS accumulation areas in leaves stained with DAB or NBT for H 2 O 2 and O 2 - detection, respectively. Three types of images determined by the combination of staining method and background color are considered. The method is based on the principle of supervised machine learning with manually labeled image patterns used for training. The method's algorithm is developed as a JavaScript macro in the public domain Fiji (ImageJ) environment. It allows to select the stained regions of ROS-mediated histochemical reactions, subsequently fractionated according to the weak, medium and intense staining intensity and thus ROS accumulation. It also evaluates total leaf blade area. The precision of ROS accumulation area detection is validated by the Dice Similarity Coefficient in the case of manual patterns. The proposed framework reduces the computation complexity, once prepared, requires less image processing expertise than the competitive methods and represents a routine quantitative imaging assay for a general histochemical image classification. Copyright © 2016 Elsevier Inc. All rights reserved.

Aberration-free superresolution imaging via binary speckle pattern encoding and processing

NASA Astrophysics Data System (ADS)

Ben-Eliezer, Eyal; Marom, Emanuel

2007-04-01

We present an approach that provides superresolution beyond the classical limit as well as image restoration in the presence of aberrations; in particular, the ability to obtain superresolution while extending the depth of field (DOF) simultaneously is tested experimentally. It is based on an approach, recently proposed, shown to increase the resolution significantly for in-focus images by speckle encoding and decoding. In our approach, an object multiplied by a fine binary speckle pattern may be located anywhere along an extended DOF region. Since the exact magnification is not known in the presence of defocus aberration, the acquired low-resolution image is electronically processed via a parallel-branch decoding scheme, where in each branch the image is multiplied by the same high-resolution synchronized time-varying binary speckle but with different magnification. Finally, a hard-decision algorithm chooses the branch that provides the highest-resolution output image, thus achieving insensitivity to aberrations as well as DOF variations. Simulation as well as experimental results are presented, exhibiting significant resolution improvement factors.

Deformation-induced speckle-pattern evolution and feasibility of correlational speckle tracking in optical coherence elastography.

PubMed

Zaitsev, Vladimir Y; Matveyev, Alexandr L; Matveev, Lev A; Gelikonov, Grigory V; Gelikonov, Valentin M; Vitkin, Alex

2015-07-01

Feasibility of speckle tracking in optical coherence tomography (OCT) based on digital image correlation (DIC) is discussed in the context of elastography problems. Specifics of applying DIC methods to OCT, compared to processing of photographic images in mechanical engineering applications, are emphasized and main complications are pointed out. Analytical arguments are augmented by accurate numerical simulations of OCT speckle patterns. In contrast to DIC processing for displacement and strain estimation in photographic images, the accuracy of correlational speckle tracking in deformed OCT images is strongly affected by the coherent nature of speckles, for which strain-induced complications of speckle “blinking” and “boiling” are typical. The tracking accuracy is further compromised by the usually more pronounced pixelated structure of OCT scans compared with digital photographic images in classical DIC applications. Processing of complex-valued OCT data (comprising both amplitude and phase) compared to intensity-only scans mitigates these deleterious effects to some degree. Criteria of the attainable speckle tracking accuracy and its dependence on the key OCT system parameters are established.

High resolution and image processing of otoconia matrix

NASA Technical Reports Server (NTRS)

Fermin, C. D.

1993-01-01

This study was designed to investigate patterns of fibrils organization in histochemically stained otoconia. Transmission electron microscope and video imaging were used. These data indicate that otoconia of the chick (Gallus domesticus) inner ear may have central cores in vivo. The data also show that the ultrastructural organization of fibrils fixed with aldehydes and histochemical stains follows trajectories that conform to the hexagonal shape of otoconia. These changes in direction may contribute to the formation of a central core. The existence of central cores is important for the in vivo buoyancy of otoconia. Packing of fibrils is tighter after phosphotungstic acid (PTA) stained otoconia than with other histochemical stains, which usually produce looser packing of fibrils and seemingly larger central core. TEM of tilted and untilted material showed that turning of fibrils occurs at the points where the face angles of otoconia form and where central cores exist. Video image processing of the images allowed reconstructing a template which, if assumed to repeat and change trajectories, would fit the pattern of fibrils seen in fixed otoconia. Since it is highly unlikely that aldehyde primary fixation or PTA stain caused such drastic change in the direction of fibrils, the template derived from these results may closely approximate patterns of otoconia fibrils packing in vivo. However, if the above is correct, the perfect crystallographic diffraction pattern of unfixed otoconia do not correspond to patterns of fixed fibrils.

A motion-compensated image filter for low-dose fluoroscopy in a real-time tumor-tracking radiotherapy system

PubMed Central

Miyamoto, Naoki; Ishikawa, Masayori; Sutherland, Kenneth; Suzuki, Ryusuke; Matsuura, Taeko; Toramatsu, Chie; Takao, Seishin; Nihongi, Hideaki; Shimizu, Shinichi; Umegaki, Kikuo; Shirato, Hiroki

2015-01-01

In the real-time tumor-tracking radiotherapy system, a surrogate fiducial marker inserted in or near the tumor is detected by fluoroscopy to realize respiratory-gated radiotherapy. The imaging dose caused by fluoroscopy should be minimized. In this work, an image processing technique is proposed for tracing a moving marker in low-dose imaging. The proposed tracking technique is a combination of a motion-compensated recursive filter and template pattern matching. The proposed image filter can reduce motion artifacts resulting from the recursive process based on the determination of the region of interest for the next frame according to the current marker position in the fluoroscopic images. The effectiveness of the proposed technique and the expected clinical benefit were examined by phantom experimental studies with actual tumor trajectories generated from clinical patient data. It was demonstrated that the marker motion could be traced in low-dose imaging by applying the proposed algorithm with acceptable registration error and high pattern recognition score in all trajectories, although some trajectories were not able to be tracked with the conventional spatial filters or without image filters. The positional accuracy is expected to be kept within ±2 mm. The total computation time required to determine the marker position is a few milliseconds. The proposed image processing technique is applicable for imaging dose reduction. PMID:25129556

Laser-Beam-Alignment Controller

NASA Technical Reports Server (NTRS)

Krasowski, M. J.; Dickens, D. E.

1995-01-01

In laser-beam-alignment controller, images from video camera compared to reference patterns by fuzzy-logic pattern comparator. Results processed by fuzzy-logic microcontroller, which sends control signals to motor driver adjusting lens and pinhole in spatial filter.

Proceedings of the NASA/MPRIA Workshop: Pattern Recognition

NASA Technical Reports Server (NTRS)

Guseman, L. F., Jr.

1983-01-01

Outlines of talks presented at the workshop conducted at Texas A & M University on February 3 and 4, 1983 are presented. Emphasis was given to the application of Mathematics to image processing and pattern recognition.

Edge detection and localization with edge pattern analysis and inflection characterization

NASA Astrophysics Data System (ADS)

Jiang, Bo

2012-05-01

In general edges are considered to be abrupt changes or discontinuities in two dimensional image signal intensity distributions. The accuracy of front-end edge detection methods in image processing impacts the eventual success of higher level pattern analysis downstream. To generalize edge detectors designed from a simple ideal step function model to real distortions in natural images, research on one dimensional edge pattern analysis to improve the accuracy of edge detection and localization proposes an edge detection algorithm, which is composed by three basic edge patterns, such as ramp, impulse, and step. After mathematical analysis, general rules for edge representation based upon the classification of edge types into three categories-ramp, impulse, and step (RIS) are developed to reduce detection and localization errors, especially reducing "double edge" effect that is one important drawback to the derivative method. But, when applying one dimensional edge pattern in two dimensional image processing, a new issue is naturally raised that the edge detector should correct marking inflections or junctions of edges. Research on human visual perception of objects and information theory pointed out that a pattern lexicon of "inflection micro-patterns" has larger information than a straight line. Also, research on scene perception gave an idea that contours have larger information are more important factor to determine the success of scene categorization. Therefore, inflections or junctions are extremely useful features, whose accurate description and reconstruction are significant in solving correspondence problems in computer vision. Therefore, aside from adoption of edge pattern analysis, inflection or junction characterization is also utilized to extend traditional derivative edge detection algorithm. Experiments were conducted to test my propositions about edge detection and localization accuracy improvements. The results support the idea that these edge detection method improvements are effective in enhancing the accuracy of edge detection and localization.

Semi-automatic mapping for identifying complex geobodies in seismic images

NASA Astrophysics Data System (ADS)

Domínguez-C, Raymundo; Romero-Salcedo, Manuel; Velasquillo-Martínez, Luis G.; Shemeretov, Leonid

2017-03-01

Seismic images are composed of positive and negative seismic wave traces with different amplitudes (Robein 2010 Seismic Imaging: A Review of the Techniques, their Principles, Merits and Limitations (Houten: EAGE)). The association of these amplitudes together with a color palette forms complex visual patterns. The color intensity of such patterns is directly related to impedance contrasts: the higher the contrast, the higher the color intensity. Generally speaking, low impedance contrasts are depicted with low tone colors, creating zones with different patterns whose features are not evident for a 3D automated mapping option available on commercial software. In this work, a workflow for a semi-automatic mapping of seismic images focused on those areas with low-intensity colored zones that may be associated with geobodies of petroleum interest is proposed. The CIE L*A*B* color space was used to perform the seismic image processing, which helped find small but significant differences between pixel tones. This process generated binary masks that bound color regions to low-intensity colors. The three-dimensional-mask projection allowed the construction of 3D structures for such zones (geobodies). The proposed method was applied to a set of digital images from a seismic cube and tested on four representative study cases. The obtained results are encouraging because interesting geobodies are obtained with a minimum of information.

Digital Images and Human Vision

NASA Technical Reports Server (NTRS)

Watson, Andrew B.; Null, Cynthia H. (Technical Monitor)

1997-01-01

Processing of digital images destined for visual consumption raises many interesting questions regarding human visual sensitivity. This talk will survey some of these questions, including some that have been answered and some that have not. There will be an emphasis upon visual masking, and a distinction will be drawn between masking due to contrast gain control processes, and due to processes such as hypothesis testing, pattern recognition, and visual search.

New approach to gallbladder ultrasonic images analysis and lesions recognition.

PubMed

Bodzioch, Sławomir; Ogiela, Marek R

2009-03-01

This paper presents a new approach to gallbladder ultrasonic image processing and analysis towards detection of disease symptoms on processed images. First, in this paper, there is presented a new method of filtering gallbladder contours from USG images. A major stage in this filtration is to segment and section off areas occupied by the said organ. In most cases this procedure is based on filtration that plays a key role in the process of diagnosing pathological changes. Unfortunately ultrasound images present among the most troublesome methods of analysis owing to the echogenic inconsistency of structures under observation. This paper provides for an inventive algorithm for the holistic extraction of gallbladder image contours. The algorithm is based on rank filtration, as well as on the analysis of histogram sections on tested organs. The second part concerns detecting lesion symptoms of the gallbladder. Automating a process of diagnosis always comes down to developing algorithms used to analyze the object of such diagnosis and verify the occurrence of symptoms related to given affection. Usually the final stage is to make a diagnosis based on the detected symptoms. This last stage can be carried out through either dedicated expert systems or more classic pattern analysis approach like using rules to determine illness basing on detected symptoms. This paper discusses the pattern analysis algorithms for gallbladder image interpretation towards classification of the most frequent illness symptoms of this organ.

Faxed document image restoration method based on local pixel patterns

NASA Astrophysics Data System (ADS)

Akiyama, Teruo; Miyamoto, Nobuo; Oguro, Masami; Ogura, Kenji

1998-04-01

A method for restoring degraded faxed document images using the patterns of pixels that construct small areas in a document is proposed. The method effectively restores faxed images that contain the halftone textures and/or density salt-and-pepper noise that degrade OCR system performance. The halftone image restoration process, white-centered 3 X 3 pixels, in which black-and-white pixels alternate, are identified first using the distribution of the pixel values as halftone textures, and then the white center pixels are inverted to black. To remove high-density salt- and-pepper noise, it is assumed that the degradation is caused by ill-balanced bias and inappropriate thresholding of the sensor output which results in the addition of random noise. Restored image can be estimated using an approximation that uses the inverse operation of the assumed original process. In order to process degraded faxed images, the algorithms mentioned above are combined. An experiment is conducted using 24 especially poor quality examples selected from data sets that exemplify what practical fax- based OCR systems cannot handle. The maximum recovery rate in terms of mean square error was 98.8 percent.

A new way of measuring wiggling pattern in SADP for 3D NAND technology

NASA Astrophysics Data System (ADS)

Mi, Jian; Chen, Ziqi; Tu, Li Ming; Mao, Xiaoming; Liu, Gong Cai; Kawada, Hiroki

2018-03-01

A new metrology method of quantitatively measuring wiggling patterns in a Self-Aligned Double Patterning (SADP) process for 2D NAND technology has been developed with a CD-SEM metrology program on images from a Review-SEM system. The metrology program provided accurate modeling of various wiggling patterns. The Review-SEM system provided a-few-micrometer-wide Field of View (FOV), which exceeds precision-guaranteed FOV of a conventional CD-SEM. The result has been effectively verified by visual inspection on vertically compressed images compared with Wiggling Index from this new method. A best-known method (BKM) system has been developed with connected HW and SW to automatically measure wiggling patterns.

Fringe pattern demodulation using the one-dimensional continuous wavelet transform: field-programmable gate array implementation.

PubMed

Abid, Abdulbasit

2013-03-01

This paper presents a thorough discussion of the proposed field-programmable gate array (FPGA) implementation for fringe pattern demodulation using the one-dimensional continuous wavelet transform (1D-CWT) algorithm. This algorithm is also known as wavelet transform profilometry. Initially, the 1D-CWT is programmed using the C programming language and compiled into VHDL using the ImpulseC tool. This VHDL code is implemented on the Altera Cyclone IV GX EP4CGX150DF31C7 FPGA. A fringe pattern image with a size of 512×512 pixels is presented to the FPGA, which processes the image using the 1D-CWT algorithm. The FPGA requires approximately 100 ms to process the image and produce a wrapped phase map. For performance comparison purposes, the 1D-CWT algorithm is programmed using the C language. The C code is then compiled using the Intel compiler version 13.0. The compiled code is run on a Dell Precision state-of-the-art workstation. The time required to process the fringe pattern image is approximately 1 s. In order to further reduce the execution time, the 1D-CWT is reprogramed using Intel Integrated Primitive Performance (IPP) Library Version 7.1. The execution time was reduced to approximately 650 ms. This confirms that at least sixfold speedup was gained using FPGA implementation over a state-of-the-art workstation that executes heavily optimized implementation of the 1D-CWT algorithm.

Medium-throughput processing of whole mount in situ hybridisation experiments into gene expression domains.

PubMed

Crombach, Anton; Cicin-Sain, Damjan; Wotton, Karl R; Jaeger, Johannes

2012-01-01

Understanding the function and evolution of developmental regulatory networks requires the characterisation and quantification of spatio-temporal gene expression patterns across a range of systems and species. However, most high-throughput methods to measure the dynamics of gene expression do not preserve the detailed spatial information needed in this context. For this reason, quantification methods based on image bioinformatics have become increasingly important over the past few years. Most available approaches in this field either focus on the detailed and accurate quantification of a small set of gene expression patterns, or attempt high-throughput analysis of spatial expression through binary pattern extraction and large-scale analysis of the resulting datasets. Here we present a robust, "medium-throughput" pipeline to process in situ hybridisation patterns from embryos of different species of flies. It bridges the gap between high-resolution, and high-throughput image processing methods, enabling us to quantify graded expression patterns along the antero-posterior axis of the embryo in an efficient and straightforward manner. Our method is based on a robust enzymatic (colorimetric) in situ hybridisation protocol and rapid data acquisition through wide-field microscopy. Data processing consists of image segmentation, profile extraction, and determination of expression domain boundary positions using a spline approximation. It results in sets of measured boundaries sorted by gene and developmental time point, which are analysed in terms of expression variability or spatio-temporal dynamics. Our method yields integrated time series of spatial gene expression, which can be used to reverse-engineer developmental gene regulatory networks across species. It is easily adaptable to other processes and species, enabling the in silico reconstitution of gene regulatory networks in a wide range of developmental contexts.

Use of thermal inertia determined by HCMM to predict nocturnal cold prone areas in Florida

NASA Technical Reports Server (NTRS)

Allen, L. H., Jr. (Principal Investigator); Chen, E.; Martsolf, J. D.; Jones, P. H.

1981-01-01

The HCMM transparency scenes for the available winter of 1978-1979 were evaluated; scenes were identified on processed magnetic tapes; other remote sensing information was identified; and a soil heat flux model with variable-depth thermal profile was developed. The Image 100 system was used to compare HCMM and GOES transparent images of surface thermal patterns. Excellent correspondence of patterns was found, with HCMM giving the greater resolution. One image shows details of thermal patterns in Florida that are attributable to difference in near surface water contents. The wide range of surface temperatures attributable to surface thermal inertia that exist in the relatively flat Florida topography is demonstrated.

Single-expose patterning development for EUV lithography

NASA Astrophysics Data System (ADS)

De Silva, Anuja; Petrillo, Karen; Meli, Luciana; Shearer, Jeffrey C.; Beique, Genevieve; Sun, Lei; Seshadri, Indira; Oh, Taehwan; Han, Seulgi; Saulnier, Nicole; Lee, Joe; Arnold, John C.; Hamieh, Bassem; Felix, Nelson M.; Furukawa, Tsuyoshi; Singh, Lovejeet; Ayothi, Ramakrishnan

2017-03-01

Initial readiness of EUV (extreme ultraviolet) patterning was demonstrated in 2016 with IBM Alliance's 7nm device technology. The focus has now shifted to driving the 'effective' k1 factor and enabling the second generation of EUV patterning. With the substantial cost of EUV exposure there is significant interest in extending the capability to do single exposure patterning with EUV. To enable this, emphasis must be placed on the aspect ratios, adhesion, defectivity reduction, etch selectivity, and imaging control of the whole patterning process. Innovations in resist materials and processes must be included to realize the full entitlement of EUV lithography at 0.33NA. In addition, enhancements in the patterning process to enable good defectivity, lithographic process window, and post etch pattern fidelity are also required. Through this work, the fundamental material challenges in driving down the effective k1 factor will be highlighted.

Soil transference patterns on bras: Image processing and laboratory dragging experiments.

PubMed

Murray, Kathleen R; Fitzpatrick, Robert W; Bottrill, Ralph S; Berry, Ron; Kobus, Hilton

2016-01-01

In a recent Australian homicide, trace soil on the victim's clothing suggested she was initially attacked in her front yard and not the park where her body was buried. However the important issue that emerged during the trial was how soil was transferred to her clothing. This became the catalyst for designing a range of soil transference experiments (STEs) to study, recognise and classify soil patterns transferred onto fabric when a body is dragged across a soil surface. Soil deposits of interest in this murder were on the victim's bra and this paper reports the results of anthropogenic soil transfer to bra-cups and straps caused by dragging. Transfer patterns were recorded by digital photography and photomicroscopy. Eight soil transfer patterns on fabric, specific to dragging as the transfer method, appeared consistently throughout the STEs. The distinctive soil patterns were largely dependent on a wide range of soil features that were measured and identified for each soil tested using X-ray Diffraction and Non-Dispersive Infra-Red analysis. Digital photographs of soil transfer patterns on fabric were analysed using image processing software to provide a soil object-oriented classification of all soil objects with a diameter of 2 pixels and above transferred. Although soil transfer patterns were easily identifiable by naked-eye alone, image processing software provided objective numerical data to support this traditional (but subjective) interpretation. Image software soil colour analysis assigned a range of Munsell colours to identify and compare trace soil on fabric to other trace soil evidence from the same location; without requiring a spectrophotometer. Trace soil from the same location was identified by linking soils with similar dominant and sub-dominant Munsell colour peaks. Image processing numerical data on the quantity of soil transferred to fabric, enabled a relationship to be discovered between soil type, clay mineralogy (smectite), particle size and soil moisture content that would not have been possible otherwise. Soil type (e.g. Anthropogenic, gravelly sandy loam soil or Natural, organic-rich soil), clay mineralogy (smectite) and soil moisture content were the greatest influencing factors in all the dragging soil transference tests (both naked eye and measured properties) to explain the eight categories of soil transference patterns recorded. This study was intended to develop a method for dragging soil transference laboratory experiments and create a baseline of preliminary soil type/property knowledge. Results confirm the need to better understand soil behaviour and properties of clothing fabrics by further testing of a wider range of soil types and clay mineral properties. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

Concentric Crater Fill

NASA Image and Video Library

2003-01-24

The bizarre patterns on the floor of this crater in Nilosyrtis Mensae imaged by NASA Mars Odyssey defy an easy explanation. It is possible that some form of periglacial process combined with the vaporization of ground ice to form these patterns.

Dark-field imaging based on post-processed electron backscatter diffraction patterns of bulk crystalline materials in a scanning electron microscope.

PubMed

Brodusch, Nicolas; Demers, Hendrix; Gauvin, Raynald

2015-01-01

Dark-field (DF) images were acquired in the scanning electron microscope with an offline procedure based on electron backscatter diffraction (EBSD) patterns (EBSPs). These EBSD-DF images were generated by selecting a particular reflection on the electron backscatter diffraction pattern and by reporting the intensity of one or several pixels around this point at each pixel of the EBSD-DF image. Unlike previous studies, the diffraction information of the sample is the basis of the final image contrast with a pixel scale resolution at the EBSP providing DF imaging in the scanning electron microscope. The offline facility of this technique permits the selection of any diffraction condition available in the diffraction pattern and displaying the corresponding image. The high number of diffraction-based images available allows a better monitoring of deformation structures compared to electron channeling contrast imaging (ECCI) which is generally limited to a few images of the same area. This technique was applied to steel and iron specimens and showed its high capability in describing more rigorously the deformation structures around micro-hardness indents. Due to the offline relation between the reference EBSP and the EBSD-DF images, this new technique will undoubtedly greatly improve our knowledge of deformation mechanism and help to improve our understanding of the ECCI contrast mechanisms. Copyright © 2014 Elsevier B.V. All rights reserved.

Computer vision for microscopy diagnosis of malaria.

PubMed

Tek, F Boray; Dempster, Andrew G; Kale, Izzet

2009-07-13

This paper reviews computer vision and image analysis studies aiming at automated diagnosis or screening of malaria infection in microscope images of thin blood film smears. Existing works interpret the diagnosis problem differently or propose partial solutions to the problem. A critique of these works is furnished. In addition, a general pattern recognition framework to perform diagnosis, which includes image acquisition, pre-processing, segmentation, and pattern classification components, is described. The open problems are addressed and a perspective of the future work for realization of automated microscopy diagnosis of malaria is provided.

Hyperspectral image classification based on local binary patterns and PCANet

NASA Astrophysics Data System (ADS)

Yang, Huizhen; Gao, Feng; Dong, Junyu; Yang, Yang

2018-04-01

Hyperspectral image classification has been well acknowledged as one of the challenging tasks of hyperspectral data processing. In this paper, we propose a novel hyperspectral image classification framework based on local binary pattern (LBP) features and PCANet. In the proposed method, linear prediction error (LPE) is first employed to select a subset of informative bands, and LBP is utilized to extract texture features. Then, spectral and texture features are stacked into a high dimensional vectors. Next, the extracted features of a specified position are transformed to a 2-D image. The obtained images of all pixels are fed into PCANet for classification. Experimental results on real hyperspectral dataset demonstrate the effectiveness of the proposed method.

Error Estimation Techniques to Refine Overlapping Aerial Image Mosaic Processes via Detected Parameters

ERIC Educational Resources Information Center

Bond, William Glenn

2012-01-01

In this paper, I propose to demonstrate a means of error estimation preprocessing in the assembly of overlapping aerial image mosaics. The mosaic program automatically assembles several hundred aerial images from a data set by aligning them, via image registration using a pattern search method, onto a GIS grid. The method presented first locates…

High-Performance 3D Image Processing Architectures for Image-Guided Interventions

DTIC Science & Technology

2008-01-01

Parallel architectures and algorithms for image understanding. Boston: Academic Press, 1991. [99] A. Bruhn, T. Jakob, M. Fischer, T. Kohlberger , J...Symposium on Pattern Recognition, vol. 2449(pp. 290-297, 2002. [100] A. Bruhn, T. Jakob, M. Fischer, T. Kohlberger , J. Weickert, U. Bruning, and C

Digital and optical shape representation and pattern recognition; Proceedings of the Meeting, Orlando, FL, Apr. 4-6, 1988

NASA Technical Reports Server (NTRS)

Juday, Richard D. (Editor)

1988-01-01

The present conference discusses topics in pattern-recognition correlator architectures, digital stereo systems, geometric image transformations and their applications, topics in pattern recognition, filter algorithms, object detection and classification, shape representation techniques, and model-based object recognition methods. Attention is given to edge-enhancement preprocessing using liquid crystal TVs, massively-parallel optical data base management, three-dimensional sensing with polar exponential sensor arrays, the optical processing of imaging spectrometer data, hybrid associative memories and metric data models, the representation of shape primitives in neural networks, and the Monte Carlo estimation of moment invariants for pattern recognition.

Fluctuations of the transcription factor ATML1 generate the pattern of giant cells in the Arabidopsis sepal

PubMed Central

Meyer, Heather M; Teles, José; Formosa-Jordan, Pau; Refahi, Yassin; San-Bento, Rita; Ingram, Gwyneth; Jönsson, Henrik; Locke, James C W; Roeder, Adrienne H K

2017-01-01

Multicellular development produces patterns of specialized cell types. Yet, it is often unclear how individual cells within a field of identical cells initiate the patterning process. Using live imaging, quantitative image analyses and modeling, we show that during Arabidopsis thaliana sepal development, fluctuations in the concentration of the transcription factor ATML1 pattern a field of identical epidermal cells to differentiate into giant cells interspersed between smaller cells. We find that ATML1 is expressed in all epidermal cells. However, its level fluctuates in each of these cells. If ATML1 levels surpass a threshold during the G2 phase of the cell cycle, the cell will likely enter a state of endoreduplication and become giant. Otherwise, the cell divides. Our results demonstrate a fluctuation-driven patterning mechanism for how cell fate decisions can be initiated through a random yet tightly regulated process. DOI: http://dx.doi.org/10.7554/eLife.19131.001 PMID:28145865

Brain Activation during Semantic Processing in Autism Spectrum Disorders via Functional Magnetic Resonance Imaging

ERIC Educational Resources Information Center

Harris, Gordon J.; Chabris, Christopher F.; Clark, Jill; Urban, Trinity; Aharon, Itzhak; Steele, Shelley; McGrath, Lauren; Condouris, Karen; Tager-Flusberg, Helen

2006-01-01

Language and communication deficits are core features of autism spectrum disorders (ASD), even in high-functioning adults with ASD. This study investigated brain activation patterns using functional magnetic resonance imaging in right-handed adult males with ASD and a control group, matched on age, handedness, and verbal IQ. Semantic processing in…

Anterior EEG asymmetries and opponent process theory.

PubMed

Kline, John P; Blackhart, Ginette C; Williams, William C

2007-03-01

The opponent process theory of emotion [Solomon, R.L., and Corbit, J.D. (1974). An opponent-process theory of motivation: I. Temporal dynamics of affect. Psychological Review, 81, 119-143.] predicts a temporary reversal of emotional valence during the recovery from emotional stimulation. We hypothesized that this affective contrast would be apparent in asymmetrical activity patterns in the frontal lobes, and would be more apparent for left frontally active individuals. The present study tested this prediction by examining EEG asymmetries during and after blocked presentations of aversive pictures selected from the International Affective Picture System (IAPS). 12 neutral images, 12 aversive images, and 24 neutral images were presented in blocks. Participants who were right frontally active at baseline did not show changes in EEG asymmetry while viewing aversive slides or after cessation. Participants left frontally active at baseline, however, exhibited greater relative left frontal activity after aversive stimulation than before stimulation. Asymmetrical activity patterns in the frontal lobes may relate to affect regulatory processes, including contrasting opponent after-reactions to aversive stimuli.

Artificial Neural Networks for Processing Graphs with Application to Image Understanding: A Survey

NASA Astrophysics Data System (ADS)

Bianchini, Monica; Scarselli, Franco

In graphical pattern recognition, each data is represented as an arrangement of elements, that encodes both the properties of each element and the relations among them. Hence, patterns are modelled as labelled graphs where, in general, labels can be attached to both nodes and edges. Artificial neural networks able to process graphs are a powerful tool for addressing a great variety of real-world problems, where the information is naturally organized in entities and relationships among entities and, in fact, they have been widely used in computer vision, f.i. in logo recognition, in similarity retrieval, and for object detection. In this chapter, we propose a survey of neural network models able to process structured information, with a particular focus on those architectures tailored to address image understanding applications. Starting from the original recursive model (RNNs), we subsequently present different ways to represent images - by trees, forests of trees, multiresolution trees, directed acyclic graphs with labelled edges, general graphs - and, correspondingly, neural network architectures appropriate to process such structures.

The new analysis method of PWQ in the DRAM pattern

NASA Astrophysics Data System (ADS)

Han, Daehan; Chang, Jinman; Kim, Taeheon; Lee, Kyusun; Kim, Yonghyeon; Kang, Jinyoung; Hong, Aeran; Choi, Bumjin; Lee, Joosung; Kim, Hyoung Jun; Lee, Kweonjae; Hong, Hyoungsun; Jin, Gyoyoung

2016-03-01

In a sub 2Xnm node process, the feedback of pattern weak points is more and more significant. Therefore, it is very important to extract the systemic defect in Double Patterning Technology(DPT), however, it is impossible to predict exact systemic defect at the recent photo simulation tool.[1] Therefore, the method of Process Window Qualification (PWQ) is very serious and essential these days. Conventional PWQ methods are die to die image comparison by using an e-beam or bright field machine. Results are evaluated by the person, who reviews the images, in some cases. However, conventional die to die comparison method has critical problem. If reference die and comparison die have same problem, such as both of dies have pattern problems, the issue patterns are not detected by current defect detecting approach. Aside from the inspection accuracy, reviewing the wafer requires much effort and time to justify the genuine issue patterns. Therefore, our company adopts die to data based matching PWQ method that is using NGR machine. The main features of the NGR are as follows. First, die to data based matching, second High speed, finally massive data were used for evaluation of pattern inspection.[2] Even though our die to data based matching PWQ method measures the mass data, our margin decision process is based on image shape. Therefore, it has some significant problems. First, because of the long analysis time, the developing period of new device is increased. Moreover, because of the limitation of resources, it may not examine the full chip area. Consequently, the result of PWQ weak points cannot represent the all the possible defects. Finally, since the PWQ margin is not decided by the mathematical value, to make the solid definition of killing defect is impossible. To overcome these problems, we introduce a statistical values base process window qualification method that increases the accuracy of process margin and reduces the review time. Therefore, it is possible to see the genuine margin of the critical pattern issue which we cannot see on our conventional PWQ inspection; hence we can enhance the accuracy of PWQ margin.

Contrasting landform perception with varied radar illumination geometries and at simulated resolutions of Venera and Magellan

NASA Technical Reports Server (NTRS)

Ford, J. P.; Arvidson, R. E.

1989-01-01

The high sensitivity of imaging radars to slope at moderate to low incidence angles enhances the perception of linear topography on images. It reveals broad spatial patterns that are essential to landform mapping and interpretation. As radar responses are strongly directional, the ability to discriminate linear features on images varies with their orientation. Landforms that appear prominent on images where they are transverse to the illumination may be obscure to indistinguishable on images where they are parallel to it. Landform detection is also influenced by the spatial resolution in radar images. Seasat radar images of the Gran Desierto Dunes complex, Sonora, Mexico; the Appalachian Valley and Ridge Province; and accreted terranes in eastern interior Alaska were processed to simulate both Venera 15 and 16 images (1000 to 3000 km resolution) and image data expected from the Magellan mission (120 to 300 m resolution. The Gran Desierto Dunes are not discernable in the Venera simulation, whereas the higher resolution Magellan simulation shows dominant dune patterns produced from differential erosion of the rocks. The Magellan simulation also shows that fluvial processes have dominated erosion and exposure of the folds.

Single-pixel imaging by Hadamard transform and its application for hyperspectral imaging

NASA Astrophysics Data System (ADS)

Mizutani, Yasuhiro; Shibuya, Kyuki; Taguchi, Hiroki; Iwata, Tetsuo; Takaya, Yasuhiro; Yasui, Takeshi

2016-10-01

In this paper, we report on comparisons of single-pixel imagings using Hadamard Transform (HT) and the ghost imaging (GI) in the view point of the visibility under weak light conditions. For comparing the two methods, we have discussed about qualities of images based on experimental results and numerical analysis. To detect images by the TH method, we have illuminated the Hadamard-pattern mask and calculated by orthogonal transform. On the other hand, the GH method can detect images by illuminating random patterns and a correlation measurement. For comparing two methods under weak light intensity, we have controlled illuminated intensities of a DMD projector about 0.1 in signal-to-noise ratio. Though a process speed of the HT image was faster then an image via the GI, the GI method has an advantage of detection under weak light condition. An essential difference between the HT and the GI method is discussed about reconstruction process. Finally, we also show a typical application of the single-pixel imaging such as hyperspectral images by using dual-optical frequency combs. An optical setup consists of two fiber lasers, spatial light modulated for generating patten illumination, and a single pixel detector. We are successful to detect hyperspectrul images in a range from 1545 to 1555 nm at 0.01nm resolution.

Personal computer (PC) based image processing applied to fluid mechanics research

NASA Technical Reports Server (NTRS)

Cho, Y.-C.; Mclachlan, B. G.

1987-01-01

A PC based image processing system was employed to determine the instantaneous velocity field of a two-dimensional unsteady flow. The flow was visualized using a suspension of seeding particles in water, and a laser sheet for illumination. With a finite time exposure, the particle motion was captured on a photograph as a pattern of streaks. The streak pattern was digitized and processsed using various imaging operations, including contrast manipulation, noise cleaning, filtering, statistical differencing, and thresholding. Information concerning the velocity was extracted from the enhanced image by measuring the length and orientation of the individual streaks. The fluid velocities deduced from the randomly distributed particle streaks were interpolated to obtain velocities at uniform grid points. For the interpolation a simple convolution technique with an adaptive Gaussian window was used. The results are compared with a numerical prediction by a Navier-Stokes commputation.

Why care about linear hair growth rates (LHGR)? a study using in vivo imaging and computer assisted image analysis after manual processing (CAIAMP) in unaffected male controls and men with male pattern hair loss (MPHL).

PubMed

Van Neste, Dominique

2014-01-01

The words "hair growth" frequently encompass many aspects other than just growth. Report on a validation method for precise non-invasive measurement of thickness together with linear hair growth rates of individual hair fibres. To verify the possible correlation between thickness and linear growth rate of scalp hair in male pattern hair loss as compared with healthy male controls. To document the process of validation of hair growth measurement from in vivo image capturing and manual processing, followed by computer assisted image analysis. We analysed 179 paired images obtained with the contrast-enhanced-phototrichogram method with exogen collection (CE-PTG-EC) in 13 healthy male controls and in 87 men with male pattern hair loss (MPHL). There was a global positive correlation between thickness and growth rate (ANOVA; p<0.0001) and a statistically significantly (ANOVA; p<0.0005) slower growth rate in MPHL as compared with equally thick hairs from controls. Finally, the growth rate recorded in the more severe patterns was significantly (ANOVA; P ≤ 0.001) reduced compared with equally thick hair from less severely affected MPHL or controls subjects. Reduced growth rate, together with thinning and shortening of the anagen phase duration in MPHL might contribute together to the global impression of decreased hair volume on the top of the head. Amongst other structural and functional parameters characterizing hair follicle regression, linear hair growth rate warrants further investigation, as it may be relevant in terms of self-perception of hair coverage, quantitative diagnosis and prognostic factor of the therapeutic response.

Multiple spiral patterns in the transitional disk of HD 100546

NASA Astrophysics Data System (ADS)

Boccaletti, A.; Pantin, E.; Lagrange, A.-M.; Augereau, J.-C.; Meheut, H.; Quanz, S. P.

2013-12-01

Context. Protoplanetary disks around young stars harbor many structures related to planetary formation. Of particular interest, spiral patterns were discovered among several of these disks and are expected to be the sign of gravitational instabilities leading to giant planet formation or gravitational perturbations caused by already existing planets. In this context, the star HD 100546 presents some specific characteristics with a complex gaseous and dusty disk that includes spirals, as well as a possible planet in formation. Aims: The objective of this study is to analyze high-contrast and high angular resolution images of this emblematic system to shed light on critical steps in planet formation. Methods: We retrieved archival images obtained at Gemini in the near IR (Ks band) with the instrument NICI and processed the data using an advanced high contrast imaging technique that takes advantage of the angular differential imaging. Results: These new images reveal the spiral pattern previously identified with Hubble Space Telescope (HST) with an unprecedented resolution, while the large-scale structure of the disk is mostly cancelled by the data processing. The single pattern to the southeast in HST images is now resolved into a multi-armed spiral pattern. Using two models of a gravitational perturber orbiting in a gaseous disk, we attempted to constrain the characteristics of this perturber, assuming that each spiral is independent, and drew qualitative conclusions. The non-detection of the northeast spiral pattern observed in HST allows putting a lower limit on the intensity ratio between the two sides of the disk, which if interpreted as forward scattering, yields a larger anisotropic scattering than is derived in the visible. Also, we find that the spirals are likely to be spatially resolved with a thickness of about 5-10 AU. Finally, we did not detect the candidate planet in formation recently discovered in the Lp band, with a mass upper limit of 16-18 MJ. Based on data retrieved from the Gemini archive.

Automated phenotype pattern recognition of zebrafish for high-throughput screening.

PubMed

Schutera, Mark; Dickmeis, Thomas; Mione, Marina; Peravali, Ravindra; Marcato, Daniel; Reischl, Markus; Mikut, Ralf; Pylatiuk, Christian

2016-07-03

Over the last years, the zebrafish (Danio rerio) has become a key model organism in genetic and chemical screenings. A growing number of experiments and an expanding interest in zebrafish research makes it increasingly essential to automatize the distribution of embryos and larvae into standard microtiter plates or other sample holders for screening, often according to phenotypical features. Until now, such sorting processes have been carried out by manually handling the larvae and manual feature detection. Here, a prototype platform for image acquisition together with a classification software is presented. Zebrafish embryos and larvae and their features such as pigmentation are detected automatically from the image. Zebrafish of 4 different phenotypes can be classified through pattern recognition at 72 h post fertilization (hpf), allowing the software to classify an embryo into 2 distinct phenotypic classes: wild-type versus variant. The zebrafish phenotypes are classified with an accuracy of 79-99% without any user interaction. A description of the prototype platform and of the algorithms for image processing and pattern recognition is presented.

Spatial noise in microdisplays for near-to-eye applications

NASA Astrophysics Data System (ADS)

Hastings, Arthur R., Jr.; Draper, Russell S.; Wood, Michael V.; Fellowes, David A.

2011-06-01

Spatial noise in imaging systems has been characterized and its impact on image quality metrics has been addressed primarily with respect to the introduction of this noise at the sensor component. However, sensor fixed pattern noise is not the only source of fixed pattern noise in an imaging system. Display fixed pattern noise cannot be easily mitigated in processing and, therefore, must be addressed. In this paper, a thorough examination of the amount and the effect of display fixed pattern noise is presented. The specific manifestation of display fixed pattern noise is dependent upon the display technology. Utilizing a calibrated camera, US Army RDECOM CERDEC NVESD has developed a microdisplay (μdisplay) spatial noise data collection capability. Noise and signal power spectra were used to characterize the display signal to noise ratio (SNR) as a function of spatial frequency analogous to the minimum resolvable temperature difference (MRTD) of a thermal sensor. The goal of this study is to establish a measurement technique to characterize μdisplay limiting performance to assist in proper imaging system specification.

How to design a horizontal patient-focused hospital.

PubMed

Murphy, E C; Ruflin, P

1993-05-01

Work Imaging is an executive information system for analyzing the cost effectiveness and efficiency of work processes and structures in health care. Advanced Work Imaging relational database technology allows managers and employees to take a sample work activities profile organization-wide. This is married to financial and organizational data to produce images of work within and across all functions, departments, and levels. The images are benchmarked against best practice data to provide insight on the quality and cost efficiency of work practice patterns, from individual roles to departmental skill mix to organization-wide service processes.

Color pictorial serpentine halftone for secure embedded data

NASA Astrophysics Data System (ADS)

Curry, Douglas N.

1998-04-01

This paper introduces a new rotatable glyph shape for trusted printing applications that has excellent image rendering, data storage and counterfeit deterrence properties. Referred to as a serpentine because it tiles into a meandering line screen, it can produce high quality images independent of its ability to embed data. The hafltone cell is constructed with hyperbolic curves to enhance its dynamic range, and generates low distortion because of rotational tone invariance with its neighbors. An extension to the process allows the data to be formatted into human readable text patterns, viewable with a magnifying glass, and therefore not requiring input scanning. The resultant embedded halftone patterns can be recognized as simple numbers (0 - 9) or alphanumerics (a - z). The pattern intensity can be offset from the surrounding image field intensity, producing a watermarking effect. We have been able to embed words such as 'original' or license numbers into the background halftone pattern of images which can be readily observed in the original image, and which conveniently disappear upon copying. We have also embedded data blocks with self-clocking codes and error correction data which are machine-readable. Finally, we have successfully printed full color images with both the embedded data and text, simulating a trusted printing application.

Image-based spectroscopy for environmental monitoring

NASA Astrophysics Data System (ADS)

Bachmakov, Eduard; Molina, Carolyn; Wynne, Rosalind

2014-03-01

An image-processing algorithm for use with a nano-featured spectrometer chemical agent detection configuration is presented. The spectrometer chip acquired from Nano-Optic DevicesTM can reduce the size of the spectrometer down to a coin. The nanospectrometer chip was aligned with a 635nm laser source, objective lenses, and a CCD camera. The images from a nanospectrometer chip were collected and compared to reference spectra. Random background noise contributions were isolated and removed from the diffraction pattern image analysis via a threshold filter. Results are provided for the image-based detection of the diffraction pattern produced by the nanospectrometer. The featured PCF spectrometer has the potential to measure optical absorption spectra in order to detect trace amounts of contaminants. MATLAB tools allow for implementation of intelligent, automatic detection of the relevant sub-patterns in the diffraction patterns and subsequent extraction of the parameters using region-detection algorithms such as the generalized Hough transform, which detects specific shapes within the image. This transform is a method for detecting curves by exploiting the duality between points on a curve and parameters of that curve. By employing this imageprocessing technique, future sensor systems will benefit from new applications such as unsupervised environmental monitoring of air or water quality.

The application of a unique flow modeling technique to complex combustion systems

NASA Astrophysics Data System (ADS)

Waslo, J.; Hasegawa, T.; Hilt, M. B.

1986-06-01

This paper describes the application of a unique three-dimensional water flow modeling technique to the study of complex fluid flow patterns within an advanced gas turbine combustor. The visualization technique uses light scattering, coupled with real-time image processing, to determine flow fields. Additional image processing is used to make concentration measurements within the combustor.

Corner-point criterion for assessing nonlinear image processing imagers

NASA Astrophysics Data System (ADS)

Landeau, Stéphane; Pigois, Laurent; Foing, Jean-Paul; Deshors, Gilles; Swiathy, Greggory

2017-10-01

Range performance modeling of optronics imagers attempts to characterize the ability to resolve details in the image. Today, digital image processing is systematically used in conjunction with the optoelectronic system to correct its defects or to exploit tiny detection signals to increase performance. In order to characterize these processing having adaptive and non-linear properties, it becomes necessary to stimulate the imagers with test patterns whose properties are similar to the actual scene image ones, in terms of dynamic range, contours, texture and singular points. This paper presents an approach based on a Corner-Point (CP) resolution criterion, derived from the Probability of Correct Resolution (PCR) of binary fractal patterns. The fundamental principle lies in the respectful perception of the CP direction of one pixel minority value among the majority value of a 2×2 pixels block. The evaluation procedure considers the actual image as its multi-resolution CP transformation, taking the role of Ground Truth (GT). After a spatial registration between the degraded image and the original one, the degradation is statistically measured by comparing the GT with the degraded image CP transformation, in terms of localized PCR at the region of interest. The paper defines this CP criterion and presents the developed evaluation techniques, such as the measurement of the number of CP resolved on the target, the transformation CP and its inverse transform that make it possible to reconstruct an image of the perceived CPs. Then, this criterion is compared with the standard Johnson criterion, in the case of a linear blur and noise degradation. The evaluation of an imaging system integrating an image display and a visual perception is considered, by proposing an analysis scheme combining two methods: a CP measurement for the highly non-linear part (imaging) with real signature test target and conventional methods for the more linear part (displaying). The application to color imaging is proposed, with a discussion about the choice of the working color space depending on the type of image enhancement processing used.

Detection of cracks on concrete surfaces by hyperspectral image processing

NASA Astrophysics Data System (ADS)

Santos, Bruno O.; Valença, Jonatas; Júlio, Eduardo

2017-06-01

All large infrastructures worldwide must have a suitable monitoring and maintenance plan, aiming to evaluate their behaviour and predict timely interventions. In the particular case of concrete infrastructures, the detection and characterization of crack patterns is a major indicator of their structural response. In this scope, methods based on image processing have been applied and presented. Usually, methods focus on image binarization followed by applications of mathematical morphology to identify cracks on concrete surface. In most cases, publications are focused on restricted areas of concrete surfaces and in a single crack. On-site, the methods and algorithms have to deal with several factors that interfere with the results, namely dirt and biological colonization. Thus, the automation of a procedure for on-site characterization of crack patterns is of great interest. This advance may result in an effective tool to support maintenance strategies and interventions planning. This paper presents a research based on the analysis and processing of hyper-spectral images for detection and classification of cracks on concrete structures. The objective of the study is to evaluate the applicability of several wavelengths of the electromagnetic spectrum for classification of cracks in concrete surfaces. An image survey considering highly discretized wavelengths between 425 nm and 950 nm was performed on concrete specimens, with bandwidths of 25 nm. The concrete specimens were produced with a crack pattern induced by applying a load with displacement control. The tests were conducted to simulate usual on-site drawbacks. In this context, the surface of the specimen was subjected to biological colonization (leaves and moss). To evaluate the results and enhance crack patterns a clustering method, namely k-means algorithm, is being applied. The research conducted allows to define the suitability of using clustering k-means algorithm combined with hyper-spectral images highly discretized for crack detection on concrete surfaces, considering cracking combined with the most usual concrete anomalies, namely biological colonization.

Early differential processing of material images: Evidence from ERP classification.

PubMed

Wiebel, Christiane B; Valsecchi, Matteo; Gegenfurtner, Karl R

2014-06-24

Investigating the temporal dynamics of natural image processing using event-related potentials (ERPs) has a long tradition in object recognition research. In a classical Go-NoGo task two characteristic effects have been emphasized: an early task independent category effect and a later task-dependent target effect. Here, we set out to use this well-established Go-NoGo paradigm to study the time course of material categorization. Material perception has gained more and more interest over the years as its importance in natural viewing conditions has been ignored for a long time. In addition to analyzing standard ERPs, we conducted a single trial ERP pattern analysis. To validate this procedure, we also measured ERPs in two object categories (people and animals). Our linear classification procedure was able to largely capture the overall pattern of results from the canonical analysis of the ERPs and even extend it. We replicate the known target effect (differential Go-NoGo potential at frontal sites) for the material images. Furthermore, we observe task-independent differential activity between the two material categories as early as 140 ms after stimulus onset. Using our linear classification approach, we show that material categories can be differentiated consistently based on the ERP pattern in single trials around 100 ms after stimulus onset, independent of the target-related status. This strengthens the idea of early differential visual processing of material categories independent of the task, probably due to differences in low-level image properties and suggests pattern classification of ERP topographies as a strong instrument for investigating electrophysiological brain activity. © 2014 ARVO.

Image-based automatic recognition of larvae

NASA Astrophysics Data System (ADS)

Sang, Ru; Yu, Guiying; Fan, Weijun; Guo, Tiantai

2010-08-01

As the main objects, imagoes have been researched in quarantine pest recognition in these days. However, pests in their larval stage are latent, and the larvae spread abroad much easily with the circulation of agricultural and forest products. It is presented in this paper that, as the new research objects, larvae are recognized by means of machine vision, image processing and pattern recognition. More visional information is reserved and the recognition rate is improved as color image segmentation is applied to images of larvae. Along with the characteristics of affine invariance, perspective invariance and brightness invariance, scale invariant feature transform (SIFT) is adopted for the feature extraction. The neural network algorithm is utilized for pattern recognition, and the automatic identification of larvae images is successfully achieved with satisfactory results.

Incoherent optical generalized Hough transform: pattern recognition and feature extraction applications

NASA Astrophysics Data System (ADS)

Fernández, Ariel; Ferrari, José A.

2017-05-01

Pattern recognition and feature extraction are image processing applications of great interest in defect inspection and robot vision among others. In comparison to purely digital methods, the attractiveness of optical processors for pattern recognition lies in their highly parallel operation and real-time processing capability. This work presents an optical implementation of the generalized Hough transform (GHT), a well-established technique for recognition of geometrical features in binary images. Detection of a geometric feature under the GHT is accomplished by mapping the original image to an accumulator space; the large computational requirements for this mapping make the optical implementation an attractive alternative to digital-only methods. We explore an optical setup where the transformation is obtained, and the size and orientation parameters can be controlled, allowing for dynamic scale and orientation-variant pattern recognition. A compact system for the above purposes results from the use of an electrically tunable lens for scale control and a pupil mask implemented on a high-contrast spatial light modulator for orientation/shape variation of the template. Real-time can also be achieved. In addition, by thresholding of the GHT and optically inverse transforming, the previously detected features of interest can be extracted.

Generation of Customizable Micro-wavy Pattern through Grayscale Direct Image Lithography

PubMed Central

He, Ran; Wang, Shunqiang; Andrews, Geoffrey; Shi, Wentao; Liu, Yaling

2016-01-01

With the increasing amount of research work in surface studies, a more effective method of producing patterned microstructures is highly desired due to the geometric limitations and complex fabricating process of current techniques. This paper presents an efficient and cost-effective method to generate customizable micro-wavy pattern using direct image lithography. This method utilizes a grayscale Gaussian distribution effect to model inaccuracies inherent in the polymerization process, which are normally regarded as trivial matters or errors. The measured surface profiles and the mathematical prediction show a good agreement, demonstrating the ability of this method to generate wavy patterns with precisely controlled features. An accurate pattern can be generated with customizable parameters (wavelength, amplitude, wave shape, pattern profile, and overall dimension). This mask-free photolithography approach provides a rapid fabrication method that is capable of generating complex and non-uniform 3D wavy patterns with the wavelength ranging from 12 μm to 2100 μm and an amplitude-to-wavelength ratio as large as 300%. Microfluidic devices with pure wavy and wavy-herringbone patterns suitable for capture of circulating tumor cells are made as a demonstrative application. A completely customized microfluidic device with wavy patterns can be created within a few hours without access to clean room or commercial photolithography equipment. PMID:26902520

Proceedings of the 1987 IEEE international conference on systems, man, and cybernetics. Volume 1

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

Not Available

1987-01-01

This book contains the proceedings of the IEE international conference on systems Man, and cybernetics. Topics include the following: robotics; knowledge base simulation; software systems, image and pattern recognition; neural networks; and image processing.

Visual based laser speckle pattern recognition method for structural health monitoring

NASA Astrophysics Data System (ADS)

Park, Kyeongtaek; Torbol, Marco

2017-04-01

This study performed the system identification of a target structure by analyzing the laser speckle pattern taken by a camera. The laser speckle pattern is generated by the diffuse reflection of the laser beam on a rough surface of the target structure. The camera, equipped with a red filter, records the scattered speckle particles of the laser light in real time and the raw speckle image of the pixel data is fed to the graphic processing unit (GPU) in the system. The algorithm for laser speckle contrast analysis (LASCA) computes: the laser speckle contrast images and the laser speckle flow images. The k-mean clustering algorithm is used to classify the pixels in each frame and the clusters' centroids, which function as virtual sensors, track the displacement between different frames in time domain. The fast Fourier transform (FFT) and the frequency domain decomposition (FDD) compute the modal properties of the structure: natural frequencies and damping ratios. This study takes advantage of the large scale computational capability of GPU. The algorithm is written in Compute Unifies Device Architecture (CUDA C) that allows the processing of speckle images in real time.

Enhanced visualization of abnormalities in digital-mammographic images

NASA Astrophysics Data System (ADS)

Young, Susan S.; Moore, William E.

2002-05-01

This paper describes two new presentation methods that are intended to improve the ability of radiologists to visualize abnormalities in mammograms by enhancing the appearance of the breast parenchyma pattern relative to the fatty-tissue surroundings. The first method, referred to as mountain- view, is obtained via multiscale edge decomposition through filter banks. The image is displayed in a multiscale edge domain that causes the image to have a topographic-like appearance. The second method displays the image in the intensity domain and is referred to as contrast-enhancement presentation. The input image is first passed through a decomposition filter bank to produce a filtered output (Id). The image at the lowest resolution is processed using a LUT (look-up table) to produce a tone scaled image (I'). The LUT is designed to optimally map the code value range corresponding to the parenchyma pattern in the mammographic image into the dynamic range of the output medium. The algorithm uses a contrast weight control mechanism to produce the desired weight factors to enhance the edge information corresponding to the parenchyma pattern. The output image is formed using a reconstruction filter bank through I' and enhanced Id.

An embedded face-classification system for infrared images on an FPGA

NASA Astrophysics Data System (ADS)

Soto, Javier E.; Figueroa, Miguel

2014-10-01

We present a face-classification architecture for long-wave infrared (IR) images implemented on a Field Programmable Gate Array (FPGA). The circuit is fast, compact and low power, can recognize faces in real time and be embedded in a larger image-processing and computer vision system operating locally on an IR camera. The algorithm uses Local Binary Patterns (LBP) to perform feature extraction on each IR image. First, each pixel in the image is represented as an LBP pattern that encodes the similarity between the pixel and its neighbors. Uniform LBP codes are then used to reduce the number of patterns to 59 while preserving more than 90% of the information contained in the original LBP representation. Then, the image is divided into 64 non-overlapping regions, and each region is represented as a 59-bin histogram of patterns. Finally, the algorithm concatenates all 64 regions to create a 3,776-bin spatially enhanced histogram. We reduce the dimensionality of this histogram using Linear Discriminant Analysis (LDA), which improves clustering and enables us to store an entire database of 53 subjects on-chip. During classification, the circuit applies LBP and LDA to each incoming IR image in real time, and compares the resulting feature vector to each pattern stored in the local database using the Manhattan distance. We implemented the circuit on a Xilinx Artix-7 XC7A100T FPGA and tested it with the UCHThermalFace database, which consists of 28 81 x 150-pixel images of 53 subjects in indoor and outdoor conditions. The circuit achieves a 98.6% hit ratio, trained with 16 images and tested with 12 images of each subject in the database. Using a 100 MHz clock, the circuit classifies 8,230 images per second, and consumes only 309mW.

Demosaicking for full motion video 9-band SWIR sensor

NASA Astrophysics Data System (ADS)

Kanaev, Andrey V.; Rawhouser, Marjorie; Kutteruf, Mary R.; Yetzbacher, Michael K.; DePrenger, Michael J.; Novak, Kyle M.; Miller, Corey A.; Miller, Christopher W.

2014-05-01

Short wave infrared (SWIR) spectral imaging systems are vital for Intelligence, Surveillance, and Reconnaissance (ISR) applications because of their abilities to autonomously detect targets and classify materials. Typically the spectral imagers are incapable of providing Full Motion Video (FMV) because of their reliance on line scanning. We enable FMV capability for a SWIR multi-spectral camera by creating a repeating pattern of 3x3 spectral filters on a staring focal plane array (FPA). In this paper we present the imagery from an FMV SWIR camera with nine discrete bands and discuss image processing algorithms necessary for its operation. The main task of image processing in this case is demosaicking of the spectral bands i.e. reconstructing full spectral images with original FPA resolution from spatially subsampled and incomplete spectral data acquired with the choice of filter array pattern. To the best of author's knowledge, the demosaicking algorithms for nine or more equally sampled bands have not been reported before. Moreover all existing algorithms developed for demosaicking visible color filter arrays with less than nine colors assume either certain relationship between the visible colors, which are not valid for SWIR imaging, or presence of one color band with higher sampling rate compared to the rest of the bands, which does not conform to our spectral filter pattern. We will discuss and present results for two novel approaches to demosaicking: interpolation using multi-band edge information and application of multi-frame super-resolution to a single frame resolution enhancement of multi-spectral spatially multiplexed images.

Comparison of glomerular activity patterns by fMRI and wide-field calcium imaging: implications for principles underlying odor mapping

PubMed Central

Sanganahalli, Basavaraju G.; Rebello, Michelle R.; Herman, Peter; Papademetris, Xenophon; Shepherd, Gordon M.; Verhagen, Justus V.; Hyder, Fahmeed

2015-01-01

Functional imaging signals arise from distinct metabolic and hemodynamic events at the neuropil, but how these processes are influenced by pre- and post-synaptic activities need to be understood for quantitative interpretation of stimulus-evoked mapping data. The olfactory bulb (OB) glomeruli, spherical neuropil regions with well-defined neuronal circuitry, can provide insights into this issue. Optical calcium-sensitive fluorescent dye imaging (OICa2+) reflects dynamics of pre-synaptic input to glomeruli, whereas high-resolution functional magnetic resonance imaging (fMRI) using deoxyhemoglobin contrast reveals neuropil function within the glomerular layer where both pre- and post-synaptic activities contribute. We imaged odor-specific activity patterns of the dorsal OB in the same anesthetized rats with fMRI and OICa2+ and then co-registered the respective maps to compare patterns in the same space. Maps by each modality were very reproducible as trial-to-trial patterns for a given odor, overlapping by ~80%. Maps evoked by ethyl butyrate and methyl valerate for a given modality overlapped by ~80%, suggesting activation of similar dorsal glomerular networks by these odors. Comparison of maps generated by both methods for a given odor showed ~70% overlap, indicating similar odor-specific maps by each method. These results suggest that odor-specific glomerular patterns by high-resolution fMRI primarily tracks pre-synaptic input to the OB. Thus combining OICa2+ and fMRI lays the framework for studies of OB processing over a range of spatiotemporal scales, where OICa2+ can feature the fast dynamics of dorsal glomerular clusters and fMRI can map the entire glomerular sheet in the OB. PMID:26631819

PCI bus content-addressable-memory (CAM) implementation on FPGA for pattern recognition/image retrieval in a distributed environment

NASA Astrophysics Data System (ADS)

Megherbi, Dalila B.; Yan, Yin; Tanmay, Parikh; Khoury, Jed; Woods, C. L.

2004-11-01

Recently surveillance and Automatic Target Recognition (ATR) applications are increasing as the cost of computing power needed to process the massive amount of information continues to fall. This computing power has been made possible partly by the latest advances in FPGAs and SOPCs. In particular, to design and implement state-of-the-Art electro-optical imaging systems to provide advanced surveillance capabilities, there is a need to integrate several technologies (e.g. telescope, precise optics, cameras, image/compute vision algorithms, which can be geographically distributed or sharing distributed resources) into a programmable system and DSP systems. Additionally, pattern recognition techniques and fast information retrieval, are often important components of intelligent systems. The aim of this work is using embedded FPGA as a fast, configurable and synthesizable search engine in fast image pattern recognition/retrieval in a distributed hardware/software co-design environment. In particular, we propose and show a low cost Content Addressable Memory (CAM)-based distributed embedded FPGA hardware architecture solution with real time recognition capabilities and computing for pattern look-up, pattern recognition, and image retrieval. We show how the distributed CAM-based architecture offers a performance advantage of an order-of-magnitude over RAM-based architecture (Random Access Memory) search for implementing high speed pattern recognition for image retrieval. The methods of designing, implementing, and analyzing the proposed CAM based embedded architecture are described here. Other SOPC solutions/design issues are covered. Finally, experimental results, hardware verification, and performance evaluations using both the Xilinx Virtex-II and the Altera Apex20k are provided to show the potential and power of the proposed method for low cost reconfigurable fast image pattern recognition/retrieval at the hardware/software co-design level.

Advances in Measurement of Skin Friction in Airflow

NASA Technical Reports Server (NTRS)

Brown, James L.; Naughton, Jonathan W.

2006-01-01

The surface interferometric skin-friction (SISF) measurement system is an instrument for determining the distribution of surface shear stress (skin friction) on a wind-tunnel model. The SISF system utilizes the established oil-film interference method, along with advanced image-data-processing techniques and mathematical models that express the relationship between interferograms and skin friction, to determine the distribution of skin friction over an observed region of the surface of a model during a single wind-tunnel test. In the oil-film interference method, a wind-tunnel model is coated with a thin film of oil of known viscosity and is illuminated with quasi-monochromatic, collimated light, typically from a mercury lamp. The light reflected from the outer surface of the oil film interferes with the light reflected from the oil-covered surface of the model. In the present version of the oil-film interference method, a camera captures an image of the illuminated model and the image in the camera is modulated by the interference pattern. The interference pattern depends on the oil-thickness distribution on the observed surface, and this distribution can be extracted through analysis of the image acquired by the camera. The oil-film technique is augmented by a tracer technique for observing the streamline pattern. To make the streamlines visible, small dots of fluorescentchalk/oil mixture are placed on the model just before a test. During the test, the chalk particles are embedded in the oil flow and produce chalk streaks that mark the streamlines. The instantaneous rate of thinning of the oil film at a given position on the surface of the model can be expressed as a function of the instantaneous thickness, the skin-friction distribution on the surface, and the streamline pattern on the surface; the functional relationship is expressed by a mathematical model that is nonlinear in the oil-film thickness and is known simply as the thin-oil-film equation. From the image data acquired as described, the time-dependent oil-thickness distribution and streamline pattern are extracted and by inversion of the thin-oil-film equation it is then possible to determine the skin-friction distribution. In addition to a quasi-monochromatic light source, the SISF system includes a beam splitter and two video cameras equipped with filters for observing the same area on a model in different wavelength ranges, plus a frame grabber and a computer for digitizing the video images and processing the image data. One video camera acquires the interference pattern in a narrow wavelength range of the quasi-monochromatic source. The other video camera acquires the streamline image of fluorescence from the chalk in a nearby but wider wavelength range. The interference- pattern and fluorescence images are digitized, and the resulting data are processed by an algorithm that inverts the thin-oil-film equation to find the skin-friction distribution.

Increasing the space-time product of super-resolution structured illumination microscopy by means of two-pattern illumination

NASA Astrophysics Data System (ADS)

Inochkin, F. M.; Pozzi, P.; Bezzubik, V. V.; Belashenkov, N. R.

2017-06-01

Superresolution image reconstruction method based on the structured illumination microscopy (SIM) principle with reduced and simplified pattern set is presented. The method described needs only 2 sinusoidal patterns shifted by half a period for each spatial direction of reconstruction, instead of the minimum of 3 for the previously known methods. The method is based on estimating redundant frequency components in the acquired set of modulated images. Digital processing is based on linear operations. When applied to several spatial orientations, the image set can be further reduced to a single pattern for each spatial orientation, complemented by a single non-modulated image for all the orientations. By utilizing this method for the case of two spatial orientations, the total input image set is reduced up to 3 images, providing up to 2-fold improvement in data acquisition time compared to the conventional 3-pattern SIM method. Using the simplified pattern design, the field of view can be doubled with the same number of spatial light modulator raster elements, resulting in a total 4-fold increase in the space-time product. The method requires precise knowledge of the optical transfer function (OTF). The key limitation is the thickness of object layer that scatters or emits light, which requires to be sufficiently small relatively to the lens depth of field. Numerical simulations and experimental results are presented. Experimental results are obtained on the SIM setup with the spatial light modulator based on the 1920x1080 digital micromirror device.

Comparison of binary mask defect printability analysis using virtual stepper system and aerial image microscope system

NASA Astrophysics Data System (ADS)

Phan, Khoi A.; Spence, Chris A.; Dakshina-Murthy, S.; Bala, Vidya; Williams, Alvina M.; Strener, Steve; Eandi, Richard D.; Li, Junling; Karklin, Linard

1999-12-01

As advanced process technologies in the wafer fabs push the patterning processes toward lower k1 factor for sub-wavelength resolution printing, reticles are required to use optical proximity correction (OPC) and phase-shifted mask (PSM) for resolution enhancement. For OPC/PSM mask technology, defect printability is one of the major concerns. Current reticle inspection tools available on the market sometimes are not capable of consistently differentiating between an OPC feature and a true random defect. Due to the process complexity and high cost associated with the making of OPC/PSM reticles, it is important for both mask shops and lithography engineers to understand the impact of different defect types and sizes to the printability. Aerial Image Measurement System (AIMS) has been used in the mask shops for a number of years for reticle applications such as aerial image simulation and transmission measurement of repaired defects. The Virtual Stepper System (VSS) provides an alternative method to do defect printability simulation and analysis using reticle images captured by an optical inspection or review system. In this paper, pre- programmed defects and repairs from a Defect Sensitivity Monitor (DSM) reticle with 200 nm minimum features (at 1x) will be studied for printability. The simulated resist lines by AIMS and VSS are both compared to SEM images of resist wafers qualitatively and quantitatively using CD verification.Process window comparison between unrepaired and repaired defects for both good and bad repair cases will be shown. The effect of mask repairs to resist pattern images for the binary mask case will be discussed. AIMS simulation was done at the International Sematech, Virtual stepper simulation at Zygo and resist wafers were processed at AMD-Submicron Development Center using a DUV lithographic process for 0.18 micrometer Logic process technology.

MassImager: A software for interactive and in-depth analysis of mass spectrometry imaging data.

PubMed

He, Jiuming; Huang, Luojiao; Tian, Runtao; Li, Tiegang; Sun, Chenglong; Song, Xiaowei; Lv, Yiwei; Luo, Zhigang; Li, Xin; Abliz, Zeper

2018-07-26

Mass spectrometry imaging (MSI) has become a powerful tool to probe molecule events in biological tissue. However, it is a widely held viewpoint that one of the biggest challenges is an easy-to-use data processing software for discovering the underlying biological information from complicated and huge MSI dataset. Here, a user-friendly and full-featured MSI software including three subsystems, Solution, Visualization and Intelligence, named MassImager, is developed focusing on interactive visualization, in-situ biomarker discovery and artificial intelligent pathological diagnosis. Simplified data preprocessing and high-throughput MSI data exchange, serialization jointly guarantee the quick reconstruction of ion image and rapid analysis of dozens of gigabytes datasets. It also offers diverse self-defined operations for visual processing, including multiple ion visualization, multiple channel superposition, image normalization, visual resolution enhancement and image filter. Regions-of-interest analysis can be performed precisely through the interactive visualization between the ion images and mass spectra, also the overlaid optical image guide, to directly find out the region-specific biomarkers. Moreover, automatic pattern recognition can be achieved immediately upon the supervised or unsupervised multivariate statistical modeling. Clear discrimination between cancer tissue and adjacent tissue within a MSI dataset can be seen in the generated pattern image, which shows great potential in visually in-situ biomarker discovery and artificial intelligent pathological diagnosis of cancer. All the features are integrated together in MassImager to provide a deep MSI processing solution at the in-situ metabolomics level for biomarker discovery and future clinical pathological diagnosis. Copyright © 2018 The Authors. Published by Elsevier B.V. All rights reserved.

Single-shot three-dimensional reconstruction based on structured light line pattern

NASA Astrophysics Data System (ADS)

Wang, ZhenZhou; Yang, YongMing

2018-07-01

Reconstruction of the object by single-shot is of great importance in many applications, in which the object is moving or its shape is non-rigid and changes irregularly. In this paper, we propose a single-shot structured light 3D imaging technique that calculates the phase map from the distorted line pattern. This technique makes use of the image processing techniques to segment and cluster the projected structured light line pattern from one single captured image. The coordinates of the clustered lines are extracted to form a low-resolution phase matrix which is then transformed to full-resolution phase map by spline interpolation. The 3D shape of the object is computed from the full-resolution phase map and the 2D camera coordinates. Experimental results show that the proposed method was able to reconstruct the three-dimensional shape of the object robustly from one single image.

Utilizing remote sensing of thematic mapper data to improve our understanding of estuarine processes and their influence on the productivity of estuarine-dependent fisheries

NASA Technical Reports Server (NTRS)

Browder, Joan A.; May, L. Nelson, Jr.; Rosenthal, Alan; Baumann, Robert H.; Gosselink, James G.

1987-01-01

A stochastic spatial computer model addressing coastal resource problems in Lousiana is being refined and validated using thematic mapper (TM) imagery. The TM images of brackish marsh sites were processed and data were tabulated on spatial parameters from TM images of the salt marsh sites. The Fisheries Image Processing Systems (FIPS) was used to analyze the TM scene. Activities were concentrated on improving the structure of the model and developing a structure and methodology for calibrating the model with spatial-pattern data from the TM imagery.

High-resolution imaging of the supercritical antisolvent process

NASA Astrophysics Data System (ADS)

Bell, Philip W.; Stephens, Amendi P.; Roberts, Christopher B.; Duke, Steve R.

2005-06-01

A high-magnification and high-resolution imaging technique was developed for the supercritical fluid antisolvent (SAS) precipitation process. Visualizations of the jet injection, flow patterns, droplets, and particles were obtained in a high-pressure vessel for polylactic acid and budesonide precipitation in supercritical CO2. The results show two regimes for particle production: one where turbulent mixing occurs in gas-like plumes, and another where distinct droplets were observed in the injection. Images are presented to demonstrate the capabilities of the method for examining particle formation theories and for understanding the underlying fluid mechanics, thermodynamics, and mass transport in the SAS process.

Similarity analysis between quantum images

NASA Astrophysics Data System (ADS)

Zhou, Ri-Gui; Liu, XingAo; Zhu, Changming; Wei, Lai; Zhang, Xiafen; Ian, Hou

2018-06-01

Similarity analyses between quantum images are so essential in quantum image processing that it provides fundamental research for the other fields, such as quantum image matching, quantum pattern recognition. In this paper, a quantum scheme based on a novel quantum image representation and quantum amplitude amplification algorithm is proposed. At the end of the paper, three examples and simulation experiments show that the measurement result must be 0 when two images are same, and the measurement result has high probability of being 1 when two images are different.

Fabrication Process for Large Size Mold and Alignment Method for Nanoimprint System

NASA Astrophysics Data System (ADS)

Ishibashi, Kentaro; Kokubo, Mitsunori; Goto, Hiroshi; Mizuno, Jun; Shoji, Shuichi

Nanoimprint technology is considered one of the mass production methods of the display for cellular phone or notebook computer, with Anti-Reflection Structures (ARS) pattern and so on. In this case, the large size mold with nanometer order pattern is very important. Then, we describe the fabrication process for large size mold, and the alignment method for UV nanoimprint system. We developed the original mold fabrication process using nanoimprint method and etching techniques. In 66 × 45 mm2 area, 200nm period seamless patterns were formed using this process. And, we constructed original alignment system that consists of the CCD-camera system, X-Y-θ table, method of moiré fringe, and image processing system, because the accuracy of pattern connection depends on the alignment method. This alignment system accuracy was within 20nm.

Machine vision inspection of lace using a neural network

NASA Astrophysics Data System (ADS)

Sanby, Christopher; Norton-Wayne, Leonard

1995-03-01

Lace is particularly difficult to inspect using machine vision since it comprises a fine and complex pattern of threads which must be verified, on line and in real time. Small distortions in the pattern are unavoidable. This paper describes instrumentation for inspecting lace actually on the knitting machine. A CCD linescan camera synchronized to machine motions grabs an image of the lace. Differences between this lace image and a perfect prototype image are detected by comparison methods, thresholding techniques, and finally, a neural network (to distinguish real defects from false alarms). Though produced originally in a laboratory on SUN Sparc work-stations, the processing has subsequently been implemented on a 50 Mhz 486 PC-look-alike. Successful operation has been demonstrated in a factory, but over a restricted width. Full width coverage awaits provision of faster processing.

Imaging whole Escherichia coli bacteria by using single-particle x-ray diffraction

NASA Astrophysics Data System (ADS)

Miao, Jianwei; Hodgson, Keith O.; Ishikawa, Tetsuya; Larabell, Carolyn A.; Legros, Mark A.; Nishino, Yoshinori

2003-01-01

We report the first experimental recording, to our knowledge, of the diffraction pattern from intact Escherichia coli bacteria using coherent x-rays with a wavelength of 2 Å. By using the oversampling phasing method, a real space image at a resolution of 30 nm was directly reconstructed from the diffraction pattern. An R factor used for characterizing the quality of the reconstruction was in the range of 5%, which demonstrated the reliability of the reconstruction process. The distribution of proteins inside the bacteria labeled with manganese oxide has been identified and this distribution confirmed by fluorescence microscopy images. Compared with lens-based microscopy, this diffraction-based imaging approach can examine thicker samples, such as whole cultured cells, in three dimensions with resolution limited only by radiation damage. Looking forward, the successful recording and reconstruction of diffraction patterns from biological samples reported here represent an important step toward the potential of imaging single biomolecules at near-atomic resolution by combining single-particle diffraction with x-ray free electron lasers.

Optimization of illuminating system to detect optical properties inside a finger

NASA Astrophysics Data System (ADS)

Sano, Emiko; Shikai, Masahiro; Shiratsuki, Akihide; Maeda, Takuji; Matsushita, Masahito; Sasakawa, Koichi

2007-01-01

Biometrics performs personal authentication using individual bodily features including fingerprints, faces, etc. These technologies have been studied and developed for many years. In particular, fingerprint authentication has evolved over many years, and fingerprinting is currently one of world's most established biometric authentication techniques. Not long ago this technique was only used for personal identification in criminal investigations and high-security facilities. In recent years, however, various biometric authentication techniques have appeared in everyday applications. Even though providing great convenience, they have also produced a number of technical issues concerning operation. Generally, fingerprint authentication is comprised of a number of component technologies: (1) sensing technology for detecting the fingerprint pattern; (2) image processing technology for converting the captured pattern into feature data that can be used for verification; (3) verification technology for comparing the feature data with a reference and determining whether it matches. Current fingerprint authentication issues, revealed in research results, originate with fingerprint sensing technology. Sensing methods for detecting a person's fingerprint pattern for image processing are particularly important because they impact overall fingerprint authentication performance. The following are the current problems concerning sensing methods that occur in some cases: Some fingers whose fingerprints used to be difficult to detect by conventional sensors. Fingerprint patterns are easily affected by the finger's surface condition, such noise as discontinuities and thin spots can appear in fingerprint patterns obtained from wrinkled finger, sweaty finger, and so on. To address these problems, we proposed a novel fingerprint sensor based on new scientific knowledge. A characteristic of this new method is that obtained fingerprint patterns are not easily affected by the finger's surface condition because it detects the fingerprint pattern inside the finger using transmitted light. We examined optimization of illumination system of this novel fingerprint sensor to detect contrasty fingerprint pattern from wide area and to improve image processing at (2).

Temporal pattern of acoustic imaging noise asymmetrically modulates activation in the auditory cortex.

PubMed

Ranaweera, Ruwan D; Kwon, Minseok; Hu, Shuowen; Tamer, Gregory G; Luh, Wen-Ming; Talavage, Thomas M

2016-01-01

This study investigated the hemisphere-specific effects of the temporal pattern of imaging related acoustic noise on auditory cortex activation. Hemodynamic responses (HDRs) to five temporal patterns of imaging noise corresponding to noise generated by unique combinations of imaging volume and effective repetition time (TR), were obtained using a stroboscopic event-related paradigm with extra-long (≥27.5 s) TR to minimize inter-acquisition effects. In addition to confirmation that fMRI responses in auditory cortex do not behave in a linear manner, temporal patterns of imaging noise were found to modulate both the shape and spatial extent of hemodynamic responses, with classically non-auditory areas exhibiting responses to longer duration noise conditions. Hemispheric analysis revealed the right primary auditory cortex to be more sensitive than the left to the presence of imaging related acoustic noise. Right primary auditory cortex responses were significantly larger during all the conditions. This asymmetry of response to imaging related acoustic noise could lead to different baseline activation levels during acquisition schemes using short TR, inducing an observed asymmetry in the responses to an intended acoustic stimulus through limitations of dynamic range, rather than due to differences in neuronal processing of the stimulus. These results emphasize the importance of accounting for the temporal pattern of the acoustic noise when comparing findings across different fMRI studies, especially those involving acoustic stimulation. Copyright © 2015 Elsevier B.V. All rights reserved.

Cognitive approaches for patterns analysis and security applications

NASA Astrophysics Data System (ADS)

Ogiela, Marek R.; Ogiela, Lidia

2017-08-01

In this paper will be presented new opportunities for developing innovative solutions for semantic pattern classification and visual cryptography, which will base on cognitive and bio-inspired approaches. Such techniques can be used for evaluation of the meaning of analyzed patterns or encrypted information, and allow to involve such meaning into the classification task or encryption process. It also allows using some crypto-biometric solutions to extend personalized cryptography methodologies based on visual pattern analysis. In particular application of cognitive information systems for semantic analysis of different patterns will be presented, and also a novel application of such systems for visual secret sharing will be described. Visual shares for divided information can be created based on threshold procedure, which may be dependent on personal abilities to recognize some image details visible on divided images.

A pipeline for comprehensive and automated processing of electron diffraction data in IPLT.

PubMed

Schenk, Andreas D; Philippsen, Ansgar; Engel, Andreas; Walz, Thomas

2013-05-01

Electron crystallography of two-dimensional crystals allows the structural study of membrane proteins in their native environment, the lipid bilayer. Determining the structure of a membrane protein at near-atomic resolution by electron crystallography remains, however, a very labor-intense and time-consuming task. To simplify and accelerate the data processing aspect of electron crystallography, we implemented a pipeline for the processing of electron diffraction data using the Image Processing Library and Toolbox (IPLT), which provides a modular, flexible, integrated, and extendable cross-platform, open-source framework for image processing. The diffraction data processing pipeline is organized as several independent modules implemented in Python. The modules can be accessed either from a graphical user interface or through a command line interface, thus meeting the needs of both novice and expert users. The low-level image processing algorithms are implemented in C++ to achieve optimal processing performance, and their interface is exported to Python using a wrapper. For enhanced performance, the Python processing modules are complemented with a central data managing facility that provides a caching infrastructure. The validity of our data processing algorithms was verified by processing a set of aquaporin-0 diffraction patterns with the IPLT pipeline and comparing the resulting merged data set with that obtained by processing the same diffraction patterns with the classical set of MRC programs. Copyright © 2013 Elsevier Inc. All rights reserved.

A pipeline for comprehensive and automated processing of electron diffraction data in IPLT

PubMed Central

Schenk, Andreas D.; Philippsen, Ansgar; Engel, Andreas; Walz, Thomas

2013-01-01

Electron crystallography of two-dimensional crystals allows the structural study of membrane proteins in their native environment, the lipid bilayer. Determining the structure of a membrane protein at near-atomic resolution by electron crystallography remains, however, a very labor-intense and time-consuming task. To simplify and accelerate the data processing aspect of electron crystallography, we implemented a pipeline for the processing of electron diffraction data using the Image Processing Library & Toolbox (IPLT), which provides a modular, flexible, integrated, and extendable cross-platform, open-source framework for image processing. The diffraction data processing pipeline is organized as several independent modules implemented in Python. The modules can be accessed either from a graphical user interface or through a command line interface, thus meeting the needs of both novice and expert users. The low-level image processing algorithms are implemented in C++ to achieve optimal processing performance, and their interface is exported to Python using a wrapper. For enhanced performance, the Python processing modules are complemented with a central data managing facility that provides a caching infrastructure. The validity of our data processing algorithms was verified by processing a set of aquaporin-0 diffraction patterns with the IPLT pipeline and comparing the resulting merged data set with that obtained by processing the same diffraction patterns with the classical set of MRC programs. PMID:23500887

Noise reduction and image enhancement using a hardware implementation of artificial neural networks

NASA Astrophysics Data System (ADS)

David, Robert; Williams, Erin; de Tremiolles, Ghislain; Tannhof, Pascal

1999-03-01

In this paper, we present a neural based solution developed for noise reduction and image enhancement using the ZISC, an IBM hardware processor which implements the Restricted Coulomb Energy algorithm and the K-Nearest Neighbor algorithm. Artificial neural networks present the advantages of processing time reduction in comparison with classical models, adaptability, and the weighted property of pattern learning. The goal of the developed application is image enhancement in order to restore old movies (noise reduction, focus correction, etc.), to improve digital television images, or to treat images which require adaptive processing (medical images, spatial images, special effects, etc.). Image results show a quantitative improvement over the noisy image as well as the efficiency of this system. Further enhancements are being examined to improve the output of the system.

A digital ISO expansion technique for digital cameras

NASA Astrophysics Data System (ADS)

Yoo, Youngjin; Lee, Kangeui; Choe, Wonhee; Park, SungChan; Lee, Seong-Deok; Kim, Chang-Yong

2010-01-01

Market's demands of digital cameras for higher sensitivity capability under low-light conditions are remarkably increasing nowadays. The digital camera market is now a tough race for providing higher ISO capability. In this paper, we explore an approach for increasing maximum ISO capability of digital cameras without changing any structure of an image sensor or CFA. Our method is directly applied to the raw Bayer pattern CFA image to avoid non-linearity characteristics and noise amplification which are usually deteriorated after ISP (Image Signal Processor) of digital cameras. The proposed method fuses multiple short exposed images which are noisy, but less blurred. Our approach is designed to avoid the ghost artifact caused by hand-shaking and object motion. In order to achieve a desired ISO image quality, both low frequency chromatic noise and fine-grain noise that usually appear in high ISO images are removed and then we modify the different layers which are created by a two-scale non-linear decomposition of an image. Once our approach is performed on an input Bayer pattern CFA image, the resultant Bayer image is further processed by ISP to obtain a fully processed RGB image. The performance of our proposed approach is evaluated by comparing SNR (Signal to Noise Ratio), MTF50 (Modulation Transfer Function), color error ~E*ab and visual quality with reference images whose exposure times are properly extended into a variety of target sensitivity.

Self-aligning and compressed autosophy video databases

NASA Astrophysics Data System (ADS)

Holtz, Klaus E.

1993-04-01

Autosophy, an emerging new science, explains `self-assembling structures,' such as crystals or living trees, in mathematical terms. This research provides a new mathematical theory of `learning' and a new `information theory' which permits the growing of self-assembling data network in a computer memory similar to the growing of `data crystals' or `data trees' without data processing or programming. Autosophy databases are educated very much like a human child to organize their own internal data storage. Input patterns, such as written questions or images, are converted to points in a mathematical omni dimensional hyperspace. The input patterns are then associated with output patterns, such as written answers or images. Omni dimensional information storage will result in enormous data compression because each pattern fragment is only stored once. Pattern recognition in the text or image files is greatly simplified by the peculiar omni dimensional storage method. Video databases will absorb input images from a TV camera and associate them with textual information. The `black box' operations are totally self-aligning where the input data will determine their own hyperspace storage locations. Self-aligning autosophy databases may lead to a new generation of brain-like devices.

Data processing software suite SITENNO for coherent X-ray diffraction imaging using the X-ray free-electron laser SACLA.

PubMed

Sekiguchi, Yuki; Oroguchi, Tomotaka; Takayama, Yuki; Nakasako, Masayoshi

2014-05-01

Coherent X-ray diffraction imaging is a promising technique for visualizing the structures of non-crystalline particles with dimensions of micrometers to sub-micrometers. Recently, X-ray free-electron laser sources have enabled efficient experiments in the `diffraction before destruction' scheme. Diffraction experiments have been conducted at SPring-8 Angstrom Compact free-electron LAser (SACLA) using the custom-made diffraction apparatus KOTOBUKI-1 and two multiport CCD detectors. In the experiments, ten thousands of single-shot diffraction patterns can be collected within several hours. Then, diffraction patterns with significant levels of intensity suitable for structural analysis must be found, direct-beam positions in diffraction patterns determined, diffraction patterns from the two CCD detectors merged, and phase-retrieval calculations for structural analyses performed. A software suite named SITENNO has been developed to semi-automatically apply the four-step processing to a huge number of diffraction data. Here, details of the algorithm used in the suite are described and the performance for approximately 9000 diffraction patterns collected from cuboid-shaped copper oxide particles reported. Using the SITENNO suite, it is possible to conduct experiments with data processing immediately after the data collection, and to characterize the size distribution and internal structures of the non-crystalline particles.

Data processing software suite SITENNO for coherent X-ray diffraction imaging using the X-ray free-electron laser SACLA

PubMed Central

Sekiguchi, Yuki; Oroguchi, Tomotaka; Takayama, Yuki; Nakasako, Masayoshi

2014-01-01

Coherent X-ray diffraction imaging is a promising technique for visualizing the structures of non-crystalline particles with dimensions of micrometers to sub-micrometers. Recently, X-ray free-electron laser sources have enabled efficient experiments in the ‘diffraction before destruction’ scheme. Diffraction experiments have been conducted at SPring-8 Angstrom Compact free-electron LAser (SACLA) using the custom-made diffraction apparatus KOTOBUKI-1 and two multiport CCD detectors. In the experiments, ten thousands of single-shot diffraction patterns can be collected within several hours. Then, diffraction patterns with significant levels of intensity suitable for structural analysis must be found, direct-beam positions in diffraction patterns determined, diffraction patterns from the two CCD detectors merged, and phase-retrieval calculations for structural analyses performed. A software suite named SITENNO has been developed to semi-automatically apply the four-step processing to a huge number of diffraction data. Here, details of the algorithm used in the suite are described and the performance for approximately 9000 diffraction patterns collected from cuboid-shaped copper oxide particles reported. Using the SITENNO suite, it is possible to conduct experiments with data processing immediately after the data collection, and to characterize the size distribution and internal structures of the non-crystalline particles. PMID:24763651

Quantifying Human Visible Color Variation from High Definition Digital Images of Orb Web Spiders.

PubMed

Tapia-McClung, Horacio; Ajuria Ibarra, Helena; Rao, Dinesh

2016-01-01

Digital processing and analysis of high resolution images of 30 individuals of the orb web spider Verrucosa arenata were performed to extract and quantify human visible colors present on the dorsal abdomen of this species. Color extraction was performed with minimal user intervention using an unsupervised algorithm to determine groups of colors on each individual spider, which was then analyzed in order to quantify and classify the colors obtained, both spatially and using energy and entropy measures of the digital images. Analysis shows that the colors cover a small region of the visible spectrum, are not spatially homogeneously distributed over the patterns and from an entropic point of view, colors that cover a smaller region on the whole pattern carry more information than colors covering a larger region. This study demonstrates the use of processing tools to create automatic systems to extract valuable information from digital images that are precise, efficient and helpful for the understanding of the underlying biology.

Quantifying Human Visible Color Variation from High Definition Digital Images of Orb Web Spiders

PubMed Central

Ajuria Ibarra, Helena; Rao, Dinesh

2016-01-01

Digital processing and analysis of high resolution images of 30 individuals of the orb web spider Verrucosa arenata were performed to extract and quantify human visible colors present on the dorsal abdomen of this species. Color extraction was performed with minimal user intervention using an unsupervised algorithm to determine groups of colors on each individual spider, which was then analyzed in order to quantify and classify the colors obtained, both spatially and using energy and entropy measures of the digital images. Analysis shows that the colors cover a small region of the visible spectrum, are not spatially homogeneously distributed over the patterns and from an entropic point of view, colors that cover a smaller region on the whole pattern carry more information than colors covering a larger region. This study demonstrates the use of processing tools to create automatic systems to extract valuable information from digital images that are precise, efficient and helpful for the understanding of the underlying biology. PMID:27902724

Network based approaches reveal clustering in protein point patterns

NASA Astrophysics Data System (ADS)

Parker, Joshua; Barr, Valarie; Aldridge, Joshua; Samelson, Lawrence E.; Losert, Wolfgang

2014-03-01

Recent advances in super-resolution imaging have allowed for the sub-diffraction measurement of the spatial location of proteins on the surfaces of T-cells. The challenge is to connect these complex point patterns to the internal processes and interactions, both protein-protein and protein-membrane. We begin analyzing these patterns by forming a geometric network amongst the proteins and looking at network measures, such the degree distribution. This allows us to compare experimentally observed patterns to models. Specifically, we find that the experimental patterns differ from heterogeneous Poisson processes, highlighting an internal clustering structure. Further work will be to compare our results to simulated protein-protein interactions to determine clustering mechanisms.

Automated Coronal Loop Identification Using Digital Image Processing Techniques

NASA Technical Reports Server (NTRS)

Lee, Jong K.; Gary, G. Allen; Newman, Timothy S.

2003-01-01

The results of a master thesis project on a study of computer algorithms for automatic identification of optical-thin, 3-dimensional solar coronal loop centers from extreme ultraviolet and X-ray 2-dimensional images will be presented. These center splines are proxies of associated magnetic field lines. The project is pattern recognition problems in which there are no unique shapes or edges and in which photon and detector noise heavily influence the images. The study explores extraction techniques using: (1) linear feature recognition of local patterns (related to the inertia-tensor concept), (2) parametric space via the Hough transform, and (3) topological adaptive contours (snakes) that constrains curvature and continuity as possible candidates for digital loop detection schemes. We have developed synthesized images for the coronal loops to test the various loop identification algorithms. Since the topology of these solar features is dominated by the magnetic field structure, a first-order magnetic field approximation using multiple dipoles provides a priori information in the identification process. Results from both synthesized and solar images will be presented.

Detecting defective electrical components in heterogeneous infra-red images by spatial control charts

NASA Astrophysics Data System (ADS)

Jamshidieini, Bahman; Fazaee, Reza

2016-05-01

Distribution network components connect machines and other loads to electrical sources. If resistance or current of any component is more than specified range, its temperature may exceed the operational limit which can cause major problems. Therefore, these defects should be found and eliminated according to their severity. Although infra-red cameras have been used for inspection of electrical components, maintenance prioritization of distribution cubicles is mostly based on personal perception and lack of training data prevents engineers from developing image processing methods. New research on the spatial control chart encouraged us to use statistical approaches instead of the pattern recognition for the image processing. In the present study, a new scanning pattern which can tolerate heavy autocorrelation among adjacent pixels within infra-red image was developed and for the first time combination of kernel smoothing, spatial control charts and local robust regression were used for finding defects within heterogeneous infra-red images of old distribution cubicles. This method does not need training data and this advantage is crucially important when the training data is not available.

Electron imaging with an EBSD detector.

PubMed

Wright, Stuart I; Nowell, Matthew M; de Kloe, René; Camus, Patrick; Rampton, Travis

2015-01-01

Electron Backscatter Diffraction (EBSD) has proven to be a useful tool for characterizing the crystallographic orientation aspects of microstructures at length scales ranging from tens of nanometers to millimeters in the scanning electron microscope (SEM). With the advent of high-speed digital cameras for EBSD use, it has become practical to use the EBSD detector as an imaging device similar to a backscatter (or forward-scatter) detector. Using the EBSD detector in this manner enables images exhibiting topographic, atomic density and orientation contrast to be obtained at rates similar to slow scanning in the conventional SEM manner. The high-speed acquisition is achieved through extreme binning of the camera-enough to result in a 5 × 5 pixel pattern. At such high binning, the captured patterns are not suitable for indexing. However, no indexing is required for using the detector as an imaging device. Rather, a 5 × 5 array of images is formed by essentially using each pixel in the 5 × 5 pixel pattern as an individual scattered electron detector. The images can also be formed at traditional EBSD scanning rates by recording the image data during a scan or can also be formed through post-processing of patterns recorded at each point in the scan. Such images lend themselves to correlative analysis of image data with the usual orientation data provided by and with chemical data obtained simultaneously via X-Ray Energy Dispersive Spectroscopy (XEDS). Copyright © 2014 The Authors. Published by Elsevier B.V. All rights reserved.

Improving depth estimation from a plenoptic camera by patterned illumination

NASA Astrophysics Data System (ADS)

Marshall, Richard J.; Meah, Chris J.; Turola, Massimo; Claridge, Ela; Robinson, Alex; Bongs, Kai; Gruppetta, Steve; Styles, Iain B.

2015-05-01

Plenoptic (light-field) imaging is a technique that allows a simple CCD-based imaging device to acquire both spatially and angularly resolved information about the "light-field" from a scene. It requires a microlens array to be placed between the objective lens and the sensor of the imaging device1 and the images under each microlens (which typically span many pixels) can be computationally post-processed to shift perspective, digital refocus, extend the depth of field, manipulate the aperture synthetically and generate a depth map from a single image. Some of these capabilities are rigid functions that do not depend upon the scene and work by manipulating and combining a well-defined set of pixels in the raw image. However, depth mapping requires specific features in the scene to be identified and registered between consecutive microimages. This process requires that the image has sufficient features for the registration, and in the absence of such features the algorithms become less reliable and incorrect depths are generated. The aim of this study is to investigate the generation of depth-maps from light-field images of scenes with insufficient features for accurate registration, using projected patterns to impose a texture on the scene that provides sufficient landmarks for the registration methods.

Automatic DNA Diagnosis for 1D Gel Electrophoresis Images using Bio-image Processing Technique.

PubMed

Intarapanich, Apichart; Kaewkamnerd, Saowaluck; Shaw, Philip J; Ukosakit, Kittipat; Tragoonrung, Somvong; Tongsima, Sissades

2015-01-01

DNA gel electrophoresis is a molecular biology technique for separating different sizes of DNA fragments. Applications of DNA gel electrophoresis include DNA fingerprinting (genetic diagnosis), size estimation of DNA, and DNA separation for Southern blotting. Accurate interpretation of DNA banding patterns from electrophoretic images can be laborious and error prone when a large number of bands are interrogated manually. Although many bio-imaging techniques have been proposed, none of them can fully automate the typing of DNA owing to the complexities of migration patterns typically obtained. We developed an image-processing tool that automatically calls genotypes from DNA gel electrophoresis images. The image processing workflow comprises three main steps: 1) lane segmentation, 2) extraction of DNA bands and 3) band genotyping classification. The tool was originally intended to facilitate large-scale genotyping analysis of sugarcane cultivars. We tested the proposed tool on 10 gel images (433 cultivars) obtained from polyacrylamide gel electrophoresis (PAGE) of PCR amplicons for detecting intron length polymorphisms (ILP) on one locus of the sugarcanes. These gel images demonstrated many challenges in automated lane/band segmentation in image processing including lane distortion, band deformity, high degree of noise in the background, and bands that are very close together (doublets). Using the proposed bio-imaging workflow, lanes and DNA bands contained within are properly segmented, even for adjacent bands with aberrant migration that cannot be separated by conventional techniques. The software, called GELect, automatically performs genotype calling on each lane by comparing with an all-banding reference, which was created by clustering the existing bands into the non-redundant set of reference bands. The automated genotype calling results were verified by independent manual typing by molecular biologists. This work presents an automated genotyping tool from DNA gel electrophoresis images, called GELect, which was written in Java and made available through the imageJ framework. With a novel automated image processing workflow, the tool can accurately segment lanes from a gel matrix, intelligently extract distorted and even doublet bands that are difficult to identify by existing image processing tools. Consequently, genotyping from DNA gel electrophoresis can be performed automatically allowing users to efficiently conduct large scale DNA fingerprinting via DNA gel electrophoresis. The software is freely available from http://www.biotec.or.th/gi/tools/gelect.

Autism from the Inside

ERIC Educational Resources Information Center

Grandin, Temple

2007-01-01

Temple Grandin, a university professor and award-winning livestock designer with autism, describes how thinking, for her, means processing a series of photorealistic mental images. Thinking in pictures, according to Grandin, is the only possible mode of thinking for many autistic people: Others think with sound patterns, visual patterns, or long…

Estimation of the Scatterer Distribution of the Cirrhotic Liver using Ultrasonic Image

NASA Astrophysics Data System (ADS)

Yamaguchi, Tadashi; Hachiya, Hiroyuki

1998-05-01

In the B-mode image of the liver obtained by an ultrasonic imaging system, the speckled pattern changes with the progression of the disease such as liver cirrhosis.In this paper we present the statistical characteristics of the echo envelope of the liver, and the technique to extract information of the scatterer distribution from the normal and cirrhotic liver images using constant false alarm rate (CFAR) processing.We analyze the relationship between the extracted scatterer distribution and the stage of liver cirrhosis. The ratio of the area in which the amplitude of the processing signal is more than the threshold to the entire processed image area is related quantitatively to the stage of liver cirrhosis.It is found that the proposed technique is valid for the quantitative diagnosis of liver cirrhosis.

Documentation of procedures for textural/spatial pattern recognition techniques

NASA Technical Reports Server (NTRS)

Haralick, R. M.; Bryant, W. F.

1976-01-01

A C-130 aircraft was flown over the Sam Houston National Forest on March 21, 1973 at 10,000 feet altitude to collect multispectral scanner (MSS) data. Existing textural and spatial automatic processing techniques were used to classify the MSS imagery into specified timber categories. Several classification experiments were performed on this data using features selected from the spectral bands and a textural transform band. The results indicate that (1) spatial post-processing a classified image can cut the classification error to 1/2 or 1/3 of its initial value, (2) spatial post-processing the classified image using combined spectral and textural features produces a resulting image with less error than post-processing a classified image using only spectral features and (3) classification without spatial post processing using the combined spectral textural features tends to produce about the same error rate as a classification without spatial post processing using only spectral features.

Hotspot detection using image pattern recognition based on higher-order local auto-correlation

NASA Astrophysics Data System (ADS)

Maeda, Shimon; Matsunawa, Tetsuaki; Ogawa, Ryuji; Ichikawa, Hirotaka; Takahata, Kazuhiro; Miyairi, Masahiro; Kotani, Toshiya; Nojima, Shigeki; Tanaka, Satoshi; Nakagawa, Kei; Saito, Tamaki; Mimotogi, Shoji; Inoue, Soichi; Nosato, Hirokazu; Sakanashi, Hidenori; Kobayashi, Takumi; Murakawa, Masahiro; Higuchi, Tetsuya; Takahashi, Eiichi; Otsu, Nobuyuki

2011-04-01

Below 40nm design node, systematic variation due to lithography must be taken into consideration during the early stage of design. So far, litho-aware design using lithography simulation models has been widely applied to assure that designs are printed on silicon without any error. However, the lithography simulation approach is very time consuming, and under time-to-market pressure, repetitive redesign by this approach may result in the missing of the market window. This paper proposes a fast hotspot detection support method by flexible and intelligent vision system image pattern recognition based on Higher-Order Local Autocorrelation. Our method learns the geometrical properties of the given design data without any defects as normal patterns, and automatically detects the design patterns with hotspots from the test data as abnormal patterns. The Higher-Order Local Autocorrelation method can extract features from the graphic image of design pattern, and computational cost of the extraction is constant regardless of the number of design pattern polygons. This approach can reduce turnaround time (TAT) dramatically only on 1CPU, compared with the conventional simulation-based approach, and by distributed processing, this has proven to deliver linear scalability with each additional CPU.

The applicability of FORMOSAT-2 images to coastal waters/bodies classification

NASA Astrophysics Data System (ADS)

Teodoro, Ana; Duarte, Lia; Silva, Pedro

2015-10-01

FORMOSAT-2, launched in May 2004, is a Taiwanese satellite developed by the National Space Organization (NSPO) of Taiwan. The Remote Sensing Instrument (RSI) is a high spatial- resolution optical sensor onboard FORMOSAT-2 with a 2 m spatial resolution in the panchromatic (PAN) band and a 8 m spatial resolution in four multispectral (MS) bands from the visible to near-infrared region. The RSI images acquired during the daytime can be used for land cover/use studies, natural and forestry resources, disaster prevention and rescue works. The main objectives of this work were to investigate the application of FORMOSAT-2 data in order to: (1) identify beach patterns; (2) correctly extract a sand spit boundary. Different pixel-based and object-based classification algorithms were applied to four FORMOSAT-2 scenes and the results were compared with the results already obtained in previous works. Analyzing the results obtained, is possible to conclude that the FORMOSAT-2 data are adequate to the correct identification of beach patterns and to an accurately extraction of the sand spit boundary (Douro river estuary, Porto, Portugal). The results obtained were compared with the results already achieved with IKONOS-2 images. In conclusion, this research has demonstrated that the FORMOSAT-2 data and image processing techniques employed are an effective methodology to identify beach patterns and to correctly extract sand spit boundaries. In the future more FORMOSAT-2 images will be processed and will be consider the use of pan sharped images and data mining algorithms.

Generalization of the photo process window and its application to OPC test pattern design

NASA Astrophysics Data System (ADS)

Eisenmann, Hans; Peter, Kai; Strojwas, Andrzej J.

2003-07-01

From the early development phase up to the production phase, test pattern play a key role for microlithography. The requirement for test pattern is to represent the design well and to cover the space of all process conditions, e.g. to investigate the full process window and all other process parameters. This paper shows that the current state-of-the-art test pattern do not address these requirements sufficiently and makes suggestions for a better selection of test pattern. We present a new methodology to analyze an existing layout (e.g. logic library, test pattern or full chip) for critical layout situations which does not need precise process data. We call this method "process space decomposition", because it is aimed at decomposing the process impact to a layout feature into a sum of single independent contributions, the dimensions of the process space. This is a generalization of the classical process window, which examines defocus and exposure dependency of given test pattern, e.g. CD value of dense and isolated lines. In our process space we additionally define the dimensions resist effects, etch effects, mask error and misalignment, which describe the deviation of the printed silicon pattern from its target. We further extend it by the pattern space using a product based layout (library, full chip or synthetic test pattern). The criticality of pattern is defined by their deviation due to aerial image, their sensitivity to the respective dimension or several combinations of these. By exploring the process space for a given design, the method allows to find the most critical patterns independent of specific process parameters. The paper provides examples for different applications of the method: (1) selection of design oriented test pattern for lithography development (2) test pattern reduction in process characterization (3) verification/optimization of printability and performance of post processing procedures (like OPC) (4) creation of a sensitive process monitor.

GTG banding pattern on human metaphase chromosomes revealed by high resolution atomic-force microscopy.

PubMed

Thalhammer, S; Koehler, U; Stark, R W; Heckl, W M

2001-06-01

Surface topography of human metaphase chromosomes following GTG banding was examined using high resolution atomic force microscopy (AFM). Although using a completely different imaging mechanism, which is based on the mechanical interaction of a probe tip with the chromosome, the observed banding pattern is comparable to results from light microscopy and a karyotype of the AFM imaged metaphase spread can be generated. The AFM imaging process was performed on a normal 2n = 46, XX karyotype and on a 2n = 46, XY, t(2;15)(q23;q15) karyotype as an example of a translocation of chromosomal bands.

Deinterlacing using modular neural network

NASA Astrophysics Data System (ADS)

Woo, Dong H.; Eom, Il K.; Kim, Yoo S.

2004-05-01

Deinterlacing is the conversion process from the interlaced scan to progressive one. While many previous algorithms that are based on weighted-sum cause blurring in edge region, deinterlacing using neural network can reduce the blurring through recovering of high frequency component by learning process, and is found robust to noise. In proposed algorithm, input image is divided into edge and smooth region, and then, to each region, one neural network is assigned. Through this process, each neural network learns only patterns that are similar, therefore it makes learning more effective and estimation more accurate. But even within each region, there are various patterns such as long edge and texture in edge region. To solve this problem, modular neural network is proposed. In proposed modular neural network, two modules are combined in output node. One is for low frequency feature of local area of input image, and the other is for high frequency feature. With this structure, each modular neural network can learn different patterns with compensating for drawback of counterpart. Therefore it can adapt to various patterns within each region effectively. In simulation, the proposed algorithm shows better performance compared with conventional deinterlacing methods and single neural network method.

General method of pattern classification using the two-domain theory

NASA Technical Reports Server (NTRS)

Rorvig, Mark E. (Inventor)

1993-01-01

Human beings judge patterns (such as images) by complex mental processes, some of which may not be known, while computing machines extract features. By representing the human judgements with simple measurements and reducing them and the machine extracted features to a common metric space and fitting them by regression, the judgements of human experts rendered on a sample of patterns may be imposed on a pattern population to provide automatic classification.

General method of pattern classification using the two-domain theory

NASA Technical Reports Server (NTRS)

Rorvig, Mark E. (Inventor)

1990-01-01

Human beings judge patterns (such as images) by complex mental processes, some of which may not be known, while computing machines extract features. By representing the human judgements with simple measurements and reducing them and the machine extracted features to a common metric space and fitting them by regression, the judgements of human experts rendered on a sample of patterns may be imposed on a pattern population to provide automatic classification.

Wavelet-Based Signal and Image Processing for Target Recognition

NASA Astrophysics Data System (ADS)

Sherlock, Barry G.

2002-11-01

The PI visited NSWC Dahlgren, VA, for six weeks in May-June 2002 and collaborated with scientists in the G33 TEAMS facility, and with Marilyn Rudzinsky of T44 Technology and Photonic Systems Branch. During this visit the PI also presented six educational seminars to NSWC scientists on various aspects of signal processing. Several items from the grant proposal were completed, including (1) wavelet-based algorithms for interpolation of 1-d signals and 2-d images; (2) Discrete Wavelet Transform domain based algorithms for filtering of image data; (3) wavelet-based smoothing of image sequence data originally obtained for the CRITTIR (Clutter Rejection Involving Temporal Techniques in the Infra-Red) project. The PI visited the University of Stellenbosch, South Africa to collaborate with colleagues Prof. B.M. Herbst and Prof. J. du Preez on the use of wavelet image processing in conjunction with pattern recognition techniques. The University of Stellenbosch has offered the PI partial funding to support a sabbatical visit in Fall 2003, the primary purpose of which is to enable the PI to develop and enhance his expertise in Pattern Recognition. During the first year, the grant supported publication of 3 referred papers, presentation of 9 seminars and an intensive two-day course on wavelet theory. The grant supported the work of two students who functioned as research assistants.

Computational intelligence for target assessment in Parkinson's disease

NASA Astrophysics Data System (ADS)

Micheli-Tzanakou, Evangelia; Hamilton, J. L.; Zheng, J.; Lehman, Richard M.

2001-11-01

Recent advances in image and signal processing have created a new challenging environment for biomedical engineers. Methods that were developed for different fields are now finding a fertile ground in biomedicine, especially in the analysis of bio-signals and in the understanding of images. More and more, these methods are used in the operating room, helping surgeons, and in the physician's office as aids for diagnostic purposes. Neural Network (NN) research on the other hand, has gone a long way in the past decade. NNs now consist of many thousands of highly interconnected processing elements that can encode, store and recall relationships between different patterns by altering the weighting coefficients of inputs in a systematic way. Although they can generate reasonable outputs from unknown input patterns, and can tolerate a great deal of noise, they are very slow when run on a serial machine. We have used advanced signal processing and innovative image processing methods that are used along with computational intelligence for diagnostic purposes and as visualization aids inside and outside the operating room. Applications to be discussed include EEGs and field potentials in Parkinson's disease along with 3D reconstruction of MR or fMR brain images in Parkinson's patients, are currently used in the operating room for Pallidotomies and Deep Brain Stimulation (DBS).

Meteor tracking via local pattern clustering in spatio-temporal domain

NASA Astrophysics Data System (ADS)

Kukal, Jaromír.; Klimt, Martin; Švihlík, Jan; Fliegel, Karel

2016-09-01

Reliable meteor detection is one of the crucial disciplines in astronomy. A variety of imaging systems is used for meteor path reconstruction. The traditional approach is based on analysis of 2D image sequences obtained from a double station video observation system. Precise localization of meteor path is difficult due to atmospheric turbulence and other factors causing spatio-temporal fluctuations of the image background. The proposed technique performs non-linear preprocessing of image intensity using Box-Cox transform as recommended in our previous work. Both symmetric and asymmetric spatio-temporal differences are designed to be robust in the statistical sense. Resulting local patterns are processed by data whitening technique and obtained vectors are classified via cluster analysis and Self-Organized Map (SOM).

TestSTORM: Simulator for optimizing sample labeling and image acquisition in localization based super-resolution microscopy

PubMed Central

Sinkó, József; Kákonyi, Róbert; Rees, Eric; Metcalf, Daniel; Knight, Alex E.; Kaminski, Clemens F.; Szabó, Gábor; Erdélyi, Miklós

2014-01-01

Localization-based super-resolution microscopy image quality depends on several factors such as dye choice and labeling strategy, microscope quality and user-defined parameters such as frame rate and number as well as the image processing algorithm. Experimental optimization of these parameters can be time-consuming and expensive so we present TestSTORM, a simulator that can be used to optimize these steps. TestSTORM users can select from among four different structures with specific patterns, dye and acquisition parameters. Example results are shown and the results of the vesicle pattern are compared with experimental data. Moreover, image stacks can be generated for further evaluation using localization algorithms, offering a tool for further software developments. PMID:24688813

Pattern recognition and feature extraction with an optical Hough transform

NASA Astrophysics Data System (ADS)

Fernández, Ariel

2016-09-01

Pattern recognition and localization along with feature extraction are image processing applications of great interest in defect inspection and robot vision among others. In comparison to purely digital methods, the attractiveness of optical processors for pattern recognition lies in their highly parallel operation and real-time processing capability. This work presents an optical implementation of the generalized Hough transform (GHT), a well-established technique for the recognition of geometrical features in binary images. Detection of a geometric feature under the GHT is accomplished by mapping the original image to an accumulator space; the large computational requirements for this mapping make the optical implementation an attractive alternative to digital- only methods. Starting from the integral representation of the GHT, it is possible to device an optical setup where the transformation is obtained, and the size and orientation parameters can be controlled, allowing for dynamic scale and orientation-variant pattern recognition. A compact system for the above purposes results from the use of an electrically tunable lens for scale control and a rotating pupil mask for orientation variation, implemented on a high-contrast spatial light modulator (SLM). Real-time (as limited by the frame rate of the device used to capture the GHT) can also be achieved, allowing for the processing of video sequences. Besides, by thresholding of the GHT (with the aid of another SLM) and inverse transforming (which is optically achieved in the incoherent system under appropriate focusing setting), the previously detected features of interest can be extracted.

Image processing and 3D visualization in forensic pathologic examination

NASA Astrophysics Data System (ADS)

Oliver, William R.; Altschuler, Bruce R.

1996-02-01

The use of image processing is becoming increasingly important in the evaluation of violent crime. While much work has been done in the use of these techniques for forensic purposes outside of forensic pathology, its use in the pathologic examination of wounding has been limited. We are investigating the use of image processing and three-dimensional visualization in the analysis of patterned injuries and tissue damage. While image processing will never replace classical understanding and interpretation of how injuries develop and evolve, it can be a useful tool in helping an observer notice features in an image, may help provide correlation of surface to deep tissue injury, and provide a mechanism for the development of a metric for analyzing how likely it may be that a given object may have caused a given wound. We are also exploring methods of acquiring three-dimensional data for such measurements, which is the subject of a second paper.

Bone marrow cavity segmentation using graph-cuts with wavelet-based texture feature.

PubMed

Shigeta, Hironori; Mashita, Tomohiro; Kikuta, Junichi; Seno, Shigeto; Takemura, Haruo; Ishii, Masaru; Matsuda, Hideo

2017-10-01

Emerging bioimaging technologies enable us to capture various dynamic cellular activities [Formula: see text]. As large amounts of data are obtained these days and it is becoming unrealistic to manually process massive number of images, automatic analysis methods are required. One of the issues for automatic image segmentation is that image-taking conditions are variable. Thus, commonly, many manual inputs are required according to each image. In this paper, we propose a bone marrow cavity (BMC) segmentation method for bone images as BMC is considered to be related to the mechanism of bone remodeling, osteoporosis, and so on. To reduce manual inputs to segment BMC, we classified the texture pattern using wavelet transformation and support vector machine. We also integrated the result of texture pattern classification into the graph-cuts-based image segmentation method because texture analysis does not consider spatial continuity. Our method is applicable to a particular frame in an image sequence in which the condition of fluorescent material is variable. In the experiment, we evaluated our method with nine types of mother wavelets and several sets of scale parameters. The proposed method with graph-cuts and texture pattern classification performs well without manual inputs by a user.

In Situ 3D Coherent X-ray Diffraction Imaging of Shock Experiments: Possible?

NASA Astrophysics Data System (ADS)

Barber, John

2011-03-01

In traditional coherent X-ray diffraction imaging (CXDI), a 2D or quasi-2D object is illuminated by a beam of coherent X-rays to produce a diffraction pattern, which is then manipulated via a process known as iterative phase retrieval to reconstruct an image of the original 2D sample. Recently, there have been dramatic advances in methods for performing fully 3D CXDI of a sample from a single diffraction pattern [Raines et al, Nature 463 214-7 (2010)], and these methods have been used to image samples tens of microns in size using soft X-rays. In this work, I explore the theoretical possibility of applying 3D CXDI techniques to the in situ imaging of the interaction between a shock front and a polycrystal, a far more stringent problem. A delicate trade-off is required between photon energy, spot size, imaging resolution, and the dimensions of the experimental setup. In this talk, I will outline the experimental and computational requirements for performing such an experiment, and I will present images and movies from simulations of one such hypothetical experiment, including both the time-resolved X-ray diffraction patterns and the time-resolved sample imagery.

Shape measurement and vibration analysis of moving speaker cone

NASA Astrophysics Data System (ADS)

Zhang, Qican; Liu, Yuankun; Lehtonen, Petri

2014-06-01

Surface three-dimensional (3-D) shape information is needed for many fast processes such as structural testing of material, standing waves on loudspeaker cone, etc. Usually measurement is done from limited number of points using electrical sensors or laser distance meters. Fourier Transform Profilometry (FTP) enables fast shape measurement of the whole surface. Method is based on angled sinusoidal fringe pattern projection and image capturing. FTP requires only one image of the deformed fringe pattern to restore the 3-D shape of the measured object, which makes real-time or dynamic data processing possible. In our experiment the method was used for loudspeaker cone distortion measurement in dynamic conditions. For sound quality issues it is important that the whole cone moves in same phase and there are no partial waves. Our imaging resolution was 1280x1024 pixels and frame rate was 200 fps. Using our setup we found unwanted spatial waves in our sample cone.

Near-infrared image formation and processing for the extraction of hand veins

NASA Astrophysics Data System (ADS)

Bouzida, Nabila; Hakim Bendada, Abdel; Maldague, Xavier P.

2010-10-01

The main objective of this work is to extract the hand vein network using a non-invasive technique in the near-infrared region (NIR). The visualization of the veins is based on a relevant feature of the blood in relation with certain wavelengths of the electromagnetic spectrum. In the present paper, we first introduce the image formation in the NIR spectral band. Then, the acquisition system will be presented as well as the method used for the image processing in order to extract the vein signature. Extractions of this pattern on the finger, on the wrist and on the dorsal hand are achieved after exposing the hand to an optical stimulation by reflection or transmission of light. We present meaningful results of the extracted vein pattern demonstrating the utility of the method for a clinical application like the diagnosis of vein disease, of primitive varicose vein and also for applications in vein biometrics.

Plant features measurements for robotics

NASA Technical Reports Server (NTRS)

Miles, Gaines E.

1989-01-01

Initial studies of the technical feasibility of using machine vision and color image processing to measure plant health were performed. Wheat plants were grown in nutrient solutions deficient in nitrogen, potassium, and iron. An additional treatment imposed water stress on wheat plants which received a full complement of nutrients. The results for juvenile (less than 2 weeks old) wheat plants show that imaging technology can be used to detect nutrient deficiencies. The relative amount of green color in a leaf declined with increased water stress. The absolute amount of green was higher for nitrogen deficient leaves compared to the control plants. Relative greenness was lower for iron deficient leaves, but the absolute green values were higher. The data showed patterns across the leaf consistent with visual symptons. The development of additional color image processing routines to recognize these patterns would improve the performance of this sensor of plant health.

SU-F-J-72: A Clinical Usable Integrated Contouring Quality Evaluation Software for Radiotherapy

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

Jiang, S; Dolly, S; Cai, B

Purpose: To introduce the Auto Contour Evaluation (ACE) software, which is the clinical usable, user friendly, efficient and all-in-one toolbox for automatically identify common contouring errors in radiotherapy treatment planning using supervised machine learning techniques. Methods: ACE is developed with C# using Microsoft .Net framework and Windows Presentation Foundation (WPF) for elegant GUI design and smooth GUI transition animations through the integration of graphics engines and high dots per inch (DPI) settings on modern high resolution monitors. The industrial standard software design pattern, Model-View-ViewModel (MVVM) pattern, is chosen to be the major architecture of ACE for neat coding structure, deepmore » modularization, easy maintainability and seamless communication with other clinical software. ACE consists of 1) a patient data importing module integrated with clinical patient database server, 2) a 2D DICOM image and RT structure simultaneously displaying module, 3) a 3D RT structure visualization module using Visualization Toolkit or VTK library and 4) a contour evaluation module using supervised pattern recognition algorithms to detect contouring errors and display detection results. ACE relies on supervised learning algorithms to handle all image processing and data processing jobs. Implementations of related algorithms are powered by Accord.Net scientific computing library for better efficiency and effectiveness. Results: ACE can take patient’s CT images and RT structures from commercial treatment planning software via direct user input or from patients’ database. All functionalities including 2D and 3D image visualization and RT contours error detection have been demonstrated with real clinical patient cases. Conclusion: ACE implements supervised learning algorithms and combines image processing and graphical visualization modules for RT contours verification. ACE has great potential for automated radiotherapy contouring quality verification. Structured with MVVM pattern, it is highly maintainable and extensible, and support smooth connections with other clinical software tools.« less

Patterns of Brain Activation when Mothers View Their Own Child and Dog: An fMRI Study

PubMed Central

Gollub, Randy L.; Niemi, Steven M.; Evins, Anne Eden

2014-01-01

Neural substrates underlying the human-pet relationship are largely unknown. We examined fMRI brain activation patterns as mothers viewed images of their own child and dog and an unfamiliar child and dog. There was a common network of brain regions involved in emotion, reward, affiliation, visual processing and social cognition when mothers viewed images of both their child and dog. Viewing images of their child resulted in brain activity in the midbrain (ventral tegmental area/substantia nigra involved in reward/affiliation), while a more posterior cortical brain activation pattern involving fusiform gyrus (visual processing of faces and social cognition) characterized a mother's response to her dog. Mothers also rated images of their child and dog as eliciting similar levels of excitement (arousal) and pleasantness (valence), although the difference in the own vs. unfamiliar child comparison was larger than the own vs. unfamiliar dog comparison for arousal. Valence ratings of their dog were also positively correlated with ratings of the attachment to their dog. Although there are similarities in the perceived emotional experience and brain function associated with the mother-child and mother-dog bond, there are also key differences that may reflect variance in the evolutionary course and function of these relationships. PMID:25279788

Patterns of brain activation when mothers view their own child and dog: an fMRI study.

PubMed

Stoeckel, Luke E; Palley, Lori S; Gollub, Randy L; Niemi, Steven M; Evins, Anne Eden

2014-01-01

Neural substrates underlying the human-pet relationship are largely unknown. We examined fMRI brain activation patterns as mothers viewed images of their own child and dog and an unfamiliar child and dog. There was a common network of brain regions involved in emotion, reward, affiliation, visual processing and social cognition when mothers viewed images of both their child and dog. Viewing images of their child resulted in brain activity in the midbrain (ventral tegmental area/substantia nigra involved in reward/affiliation), while a more posterior cortical brain activation pattern involving fusiform gyrus (visual processing of faces and social cognition) characterized a mother's response to her dog. Mothers also rated images of their child and dog as eliciting similar levels of excitement (arousal) and pleasantness (valence), although the difference in the own vs. unfamiliar child comparison was larger than the own vs. unfamiliar dog comparison for arousal. Valence ratings of their dog were also positively correlated with ratings of the attachment to their dog. Although there are similarities in the perceived emotional experience and brain function associated with the mother-child and mother-dog bond, there are also key differences that may reflect variance in the evolutionary course and function of these relationships.

Anti-nuclear antibody screening using HEp-2 cells.

PubMed

Buchner, Carol; Bryant, Cassandra; Eslami, Anna; Lakos, Gabriella

2014-06-23

The American College of Rheumatology position statement on ANA testing stipulates the use of IIF as the gold standard method for ANA screening(1). Although IIF is an excellent screening test in expert hands, the technical difficulties of processing and reading IIF slides--such as the labor intensive slide processing, manual reading, the need for experienced, trained technologists and the use of dark room--make the IIF method difficult to fit in the workflow of modern, automated laboratories. The first and crucial step towards high quality ANA screening is careful slide processing. This procedure is labor intensive, and requires full understanding of the process, as well as attention to details and experience. Slide reading is performed by fluorescent microscopy in dark rooms, and is done by trained technologists who are familiar with the various patterns, in the context of cell cycle and the morphology of interphase and dividing cells. Provided that IIF is the first line screening tool for SARD, understanding the steps to correctly perform this technique is critical. Recently, digital imaging systems have been developed for the automated reading of IIF slides. These systems, such as the NOVA View Automated Fluorescent Microscope, are designed to streamline the routine IIF workflow. NOVA View acquires and stores high resolution digital images of the wells, thereby separating image acquisition from interpretation; images are viewed an interpreted on high resolution computer monitors. It stores images for future reference and supports the operator's interpretation by providing fluorescent light intensity data on the images. It also preliminarily categorizes results as positive or negative, and provides pattern recognition for positive samples. In summary, it eliminates the need for darkroom, and automates and streamlines the IIF reading/interpretation workflow. Most importantly, it increases consistency between readers and readings. Moreover, with the use of barcoded slides, transcription errors are eliminated by providing sample traceability and positive patient identification. This results in increased patient data integrity and safety. The overall goal of this video is to demonstrate the IIF procedure, including slide processing, identification of common IIF patterns, and the introduction of new advancements to simplify and harmonize this technique.

[Image fusion: use in the control of the distribution of prostatic biopsies].

PubMed

Mozer, Pierre; Baumann, Michaël; Chevreau, Grégoire; Troccaz, Jocelyne

2008-02-01

Prostate biopsies are performed under 2D TransRectal UltraSound (US) guidance by sampling the prostate according to a predefined pattern. Modern image processing tools allow better control of biopsy distribution. We evaluated the accuracy of a single operator performing a pattern of 12 ultrasound-guided biopsies by registering 3D ultrasound control images acquired after each biopsy. For each patient, prostate image alignment was performed automatically with a voxel-based registration algorithm allowing visualization of each biopsy trajectory in a single ultrasound reference volume. On average, the operator reached the target in 60% of all cases. This study shows that it is difficult to accurately reach targets in the prostate using 2D ultrasound. In the near future, real-time fusion of MRI and US images will allow selection of a target in previously acquired MR images and biopsy of this target by US guidance.

Infrared Spectroscopic Imaging for Prostate Pathology Practice

DTIC Science & Technology

2011-04-01

features – geometric properties of epithelial cells/nuclei and lumens – that are quantified based on H&E stained images as well as FT-IR images of...the samples. By restricting the features used to geometric measures, we sought to mimic the pattern recognition process employed by human experts, and...relatively dark and can be modeled as small elliptical areas in the stained images. This geometrical model is often confounded as multiple nuclei can be

Are Ripples a Sign of Water?

NASA Technical Reports Server (NTRS)

2004-01-01

Scientists are investigating the ripples and textures seen in this 4-panel mosaic image, taken by the microscopic imager on the instrument deployment device or 'robotic arm' of NASA's Mars Exploration Rover Opportunity. The images were taken from 'Panoramic Position 2' on the southeast side of the rim of 'Endurance' Crater. This small set of nearly 150 images was acquired to examine small-scale ripple patterns suggestive of past aqueous processes on Mars.

Standing magnetic resonance imaging detection of bone marrow oedema-type signal pattern associated with subcarpal pain in 8 racehorses: a prospective study.

PubMed

Powell, S E; Ramzan, P H L; Head, M J; Shepherd, M C; Baldwin, G I; Steven, W N

2010-01-01

The proximal metacarpal region is a common site of origin of lameness in the performance horse. A number of disease entities are recognised as causes of proximal metacarpal lameness but a definitive diagnosis is often elusive. Magnetic resonance imaging (MRI) is hypothesised to offer advantages over traditional imaging modalities in the investigation of proximal metacarpal pain. To describe clinical and imaging features of cases of lameness in racehorses arising from the proximal metacarpal region in which standing MRI identified 'bone marrow oedema-type' (BMO-type) signal patterns. Records for all horses undergoing standing MRI of the proximal metacarpus/distal carpus from September 2006 to December 2008 were reviewed. Cases underwent a standardised protocol for diagnostic analgesia, radiography and ultrasonography of the proximal metacarpus and distal carpus. Cases with proximal metacarpal lameness displaying a characteristic BMO-type signal pattern on MRI were identified and outcomes analysed. Eight cases were identified with characteristic MRI findings of extensive hyperintensity on T2* gradient echo and short tau inversion fast spin echo sequences and corresponding hypointensity on T1 gradient echo images within the palmaroproximal aspect of the third metacarpal bone. Follow-up information was available for all cases; at the time of writing 7/8 had returned to full work and were free from lameness. The BMO-type signal patterns visible on MR images in these cases may signal the existence of a previously under-diagnosed pathological process associated with proximal metacarpal lameness in racehorses. This finding is postulated to be associated with a stress reaction and possible prodromal stress fracture of the palmaroproximal metacarpus not appreciable radiographically or ultrasonographically. MRI of the proximal metacarpal region permits detection of pathological processes, which may elude conventional imaging and, therefore, has important therapeutic and prognostic implications in these cases.

Temporal and spatial evolution characteristics of gas-liquid two-phase flow pattern based on image texture spectrum descriptor

NASA Astrophysics Data System (ADS)

Zhou, Xi-Guo; Jin, Ning-De; Wang, Zhen-Ya; Zhang, Wen-Yin

2009-11-01

The dynamic image information of typical gas-liquid two-phase flow patterns in vertical upward pipe is captured by a highspeed dynamic camera. The texture spectrum descriptor is used to describe the texture characteristics of the processed images whose content is represented in the form of texture spectrum histogram, and four time-varying characteristic parameter indexes which represent image texture structure of different flow patterns are extracted. The study results show that the amplitude fluctuation of texture characteristic parameter indexes of bubble flow is lowest and shows very random complex dynamic behavior; the amplitude fluctuation of slug flow is higher and shows intermittent motion behavior between gas slug and liquid slug, and the amplitude fluctuation of churn flow is the highest and shows better periodicity; the amplitude fluctuation of bubble-slug flow is from low to high and oscillating frequence is higher than that of slug flow, and includes the features of both slug flow and bubble flow; the slug-churn flow loses the periodicity of slug flow and churn flow, and the amplitude fluctuation is high. The results indicate that the image texture characteristic parameter indexes of different flow pattern can reflect the flow characteristics of gas-liquid two-phase flow, which provides a new approach to understand the temporal and spatial evolution of flow pattern dynamics.

Automated processing of zebrafish imaging data: a survey.

PubMed

Mikut, Ralf; Dickmeis, Thomas; Driever, Wolfgang; Geurts, Pierre; Hamprecht, Fred A; Kausler, Bernhard X; Ledesma-Carbayo, María J; Marée, Raphaël; Mikula, Karol; Pantazis, Periklis; Ronneberger, Olaf; Santos, Andres; Stotzka, Rainer; Strähle, Uwe; Peyriéras, Nadine

2013-09-01

Due to the relative transparency of its embryos and larvae, the zebrafish is an ideal model organism for bioimaging approaches in vertebrates. Novel microscope technologies allow the imaging of developmental processes in unprecedented detail, and they enable the use of complex image-based read-outs for high-throughput/high-content screening. Such applications can easily generate Terabytes of image data, the handling and analysis of which becomes a major bottleneck in extracting the targeted information. Here, we describe the current state of the art in computational image analysis in the zebrafish system. We discuss the challenges encountered when handling high-content image data, especially with regard to data quality, annotation, and storage. We survey methods for preprocessing image data for further analysis, and describe selected examples of automated image analysis, including the tracking of cells during embryogenesis, heartbeat detection, identification of dead embryos, recognition of tissues and anatomical landmarks, and quantification of behavioral patterns of adult fish. We review recent examples for applications using such methods, such as the comprehensive analysis of cell lineages during early development, the generation of a three-dimensional brain atlas of zebrafish larvae, and high-throughput drug screens based on movement patterns. Finally, we identify future challenges for the zebrafish image analysis community, notably those concerning the compatibility of algorithms and data formats for the assembly of modular analysis pipelines.

Automated Processing of Zebrafish Imaging Data: A Survey

PubMed Central

Dickmeis, Thomas; Driever, Wolfgang; Geurts, Pierre; Hamprecht, Fred A.; Kausler, Bernhard X.; Ledesma-Carbayo, María J.; Marée, Raphaël; Mikula, Karol; Pantazis, Periklis; Ronneberger, Olaf; Santos, Andres; Stotzka, Rainer; Strähle, Uwe; Peyriéras, Nadine

2013-01-01

Abstract Due to the relative transparency of its embryos and larvae, the zebrafish is an ideal model organism for bioimaging approaches in vertebrates. Novel microscope technologies allow the imaging of developmental processes in unprecedented detail, and they enable the use of complex image-based read-outs for high-throughput/high-content screening. Such applications can easily generate Terabytes of image data, the handling and analysis of which becomes a major bottleneck in extracting the targeted information. Here, we describe the current state of the art in computational image analysis in the zebrafish system. We discuss the challenges encountered when handling high-content image data, especially with regard to data quality, annotation, and storage. We survey methods for preprocessing image data for further analysis, and describe selected examples of automated image analysis, including the tracking of cells during embryogenesis, heartbeat detection, identification of dead embryos, recognition of tissues and anatomical landmarks, and quantification of behavioral patterns of adult fish. We review recent examples for applications using such methods, such as the comprehensive analysis of cell lineages during early development, the generation of a three-dimensional brain atlas of zebrafish larvae, and high-throughput drug screens based on movement patterns. Finally, we identify future challenges for the zebrafish image analysis community, notably those concerning the compatibility of algorithms and data formats for the assembly of modular analysis pipelines. PMID:23758125

The Degenerative Spine.

PubMed

Clarençon, Frédéric; Law-Ye, Bruno; Bienvenot, Peggy; Cormier, Évelyne; Chiras, Jacques

2016-08-01

Degenerative disease of the spine is a leading cause of back pain and radiculopathy, and is a frequent indication for spine MR imaging. Disc degeneration, disc protrusion/herniation, discarhtrosis, spinal canal stenosis, and facet joint arthrosis, as well as interspinous processes arthrosis, may require an MR imaging workup. This review presents the MR imaging patterns of these diseases and describes the benefit of the MR imaging in these indications compared with the other imaging modalities like plain radiographs or computed tomography scan. Copyright © 2016 Elsevier Inc. All rights reserved.

In-situ photoluminescence imaging for passivation-layer etching process control for photovoltaics

NASA Astrophysics Data System (ADS)

Lee, J. Z.; Michaelson, L.; Munoz, K.; Tyson, T.; Gallegos, A.; Sullivan, J. T.; Buonassisi, T.

2014-07-01

Light-induced plating (LIP) of solar-cell metal contacts is a scalable alternative to silver paste. However, LIP requires an additional patterning step to create openings in the silicon nitride (SiNx) antireflection coating (ARC) layer prior to metallization. One approach to pattern the SiNx is masking and wet chemical etching. In-situ real-time photoluminescence imaging (PLI) is demonstrated as a process-monitoring method to determine when SiNx has been fully removed during etching. We demonstrate that the change in PLI signal intensity during etching is caused by a combination of (1) decreasing light absorption from the reduction in SiNx ARC layer thickness and (2) decreasing surface lifetime as the SiNx/Si interface transitions to an etch-solution/Si. Using in-situ PLI to guide the etching process, we demonstrate a full-area plated single-crystalline silicon device. In-situ PLI has the potential to be integrated into a commercial processing line to improve process control and reliability.

Targeted and untargeted-metabolite profiling to track the compositional integrity of ginger during processing using digitally-enhanced HPTLC pattern recognition analysis.

PubMed

Ibrahim, Reham S; Fathy, Hoda

2018-03-30

Tracking the impact of commonly applied post-harvesting and industrial processing practices on the compositional integrity of ginger rhizome was implemented in this work. Untargeted metabolite profiling was performed using digitally-enhanced HPTLC method where the chromatographic fingerprints were extracted using ImageJ software then analysed with multivariate Principal Component Analysis (PCA) for pattern recognition. A targeted approach was applied using a new, validated, simple and fast HPTLC image analysis method for simultaneous quantification of the officially recognized markers 6-, 8-, 10-gingerol and 6-shogaol in conjunction with chemometric Hierarchical Clustering Analysis (HCA). The results of both targeted and untargeted metabolite profiling revealed that peeling, drying in addition to storage employed during processing have a great influence on ginger chemo-profile, the different forms of processed ginger shouldn't be used interchangeably. Moreover, it deemed necessary to consider the holistic metabolic profile for comprehensive evaluation of ginger during processing. Copyright © 2018. Published by Elsevier B.V.

Printing line/space patterns on nonplanar substrates using a digital micromirror device-based point-array scanning technique

NASA Astrophysics Data System (ADS)

Kuo, Hung-Fei; Kao, Guan-Hsuan; Zhu, Liang-Xiu; Hung, Kuo-Shu; Lin, Yu-Hsin

2018-02-01

This study used a digital micromirror device (DMD) to produce point-array patterns and employed a self-developed optical system to define line-and-space patterns on nonplanar substrates. First, field tracing was employed to analyze the aerial images of the lithographic system, which comprised an optical system and the DMD. Multiobjective particle swarm optimization was then applied to determine the spot overlapping rate used. The objective functions were set to minimize linewidth and maximize image log slope, through which the dose of the exposure agent could be effectively controlled and the quality of the nonplanar lithography could be enhanced. Laser beams with 405-nm wavelength were employed as the light source. Silicon substrates coated with photoresist were placed on a nonplanar translation stage. The DMD was used to produce lithographic patterns, during which the parameters were analyzed and optimized. The optimal delay time-sequence combinations were used to scan images of the patterns. Finally, an exposure linewidth of less than 10 μm was successfully achieved using the nonplanar lithographic process.

A gradient-based approach for automated crest-line detection and analysis of sand dune patterns on planetary surfaces

NASA Astrophysics Data System (ADS)

Lancaster, N.; LeBlanc, D.; Bebis, G.; Nicolescu, M.

2015-12-01

Dune-field patterns are believed to behave as self-organizing systems, but what causes the patterns to form is still poorly understood. The most obvious (and in many cases the most significant) aspect of a dune system is the pattern of dune crest lines. Extracting meaningful features such as crest length, orientation, spacing, bifurcations, and merging of crests from image data can reveal important information about the specific dune-field morphological properties, development, and response to changes in boundary conditions, but manual methods are labor-intensive and time-consuming. We are developing the capability to recognize and characterize patterns of sand dunes on planetary surfaces. Our goal is to develop a robust methodology and the necessary algorithms for automated or semi-automated extraction of dune morphometric information from image data. Our main approach uses image processing methods to extract gradient information from satellite images of dune fields. Typically, the gradients have a dominant magnitude and orientation. In many cases, the images have two major dominant gradient orientations, for the sunny and shaded side of the dunes. A histogram of the gradient orientations is used to determine the dominant orientation. A threshold is applied to the image based on gradient orientations which agree with the dominant orientation. The contours of the binary image can then be used to determine the dune crest-lines, based on pixel intensity values. Once the crest-lines have been extracted, the morphological properties can be computed. We have tested our approach on a variety of images of linear and crescentic (transverse) dunes and compared dune detection algorithms with manually-digitized dune crest lines, achieving true positive values of 0.57-0.99; and false positives values of 0.30-0.67, indicating that out approach is generally robust.

Some uses of wavelets for imaging dynamic processes in live cochlear structures

NASA Astrophysics Data System (ADS)

Boutet de Monvel, J.

2007-09-01

A variety of image and signal processing algorithms based on wavelet filtering tools have been developed during the last few decades, that are well adapted to the experimental variability typically encountered in live biological microscopy. A number of processing tools are reviewed, that use wavelets for adaptive image restoration and for motion or brightness variation analysis by optical flow computation. The usefulness of these tools for biological imaging is illustrated in the context of the restoration of images of the inner ear and the analysis of cochlear motion patterns in two and three dimensions. I also report on recent work that aims at capturing fluorescence intensity changes associated with vesicle dynamics at synaptic zones of sensory hair cells. This latest application requires one to separate the intensity variations associated with the physiological process under study from the variations caused by motion of the observed structures. A wavelet optical flow algorithm for doing this is presented, and its effectiveness is demonstrated on artificial and experimental image sequences.

Digital processing of radiographic images

NASA Technical Reports Server (NTRS)

Bond, A. D.; Ramapriyan, H. K.

1973-01-01

Some techniques are presented and the software documentation for the digital enhancement of radiographs. Both image handling and image processing operations are considered. The image handling operations dealt with are: (1) conversion of format of data from packed to unpacked and vice versa; (2) automatic extraction of image data arrays; (3) transposition and 90 deg rotations of large data arrays; (4) translation of data arrays for registration; and (5) reduction of the dimensions of data arrays by integral factors. Both the frequency and the spatial domain approaches are presented for the design and implementation of the image processing operation. It is shown that spatial domain recursive implementation of filters is much faster than nonrecursive implementations using fast fourier transforms (FFT) for the cases of interest in this work. The recursive implementation of a class of matched filters for enhancing image signal to noise ratio is described. Test patterns are used to illustrate the filtering operations. The application of the techniques to radiographic images of metallic structures is demonstrated through several examples.

High-quality and small-capacity e-learning video featuring lecturer-superimposing PC screen images

NASA Astrophysics Data System (ADS)

Nomura, Yoshihiko; Murakami, Michinobu; Sakamoto, Ryota; Sugiura, Tokuhiro; Matsui, Hirokazu; Kato, Norihiko

2006-10-01

Information processing and communication technology are progressing quickly, and are prevailing throughout various technological fields. Therefore, the development of such technology should respond to the needs for improvement of quality in the e-learning education system. The authors propose a new video-image compression processing system that ingeniously employs the features of the lecturing scene. While dynamic lecturing scene is shot by a digital video camera, screen images are electronically stored by a PC screen image capturing software in relatively long period at a practical class. Then, a lecturer and a lecture stick are extracted from the digital video images by pattern recognition techniques, and the extracted images are superimposed on the appropriate PC screen images by off-line processing. Thus, we have succeeded to create a high-quality and small-capacity (HQ/SC) video-on-demand educational content featuring the advantages: the high quality of image sharpness, the small electronic file capacity, and the realistic lecturer motion.

Real-time fringe pattern demodulation with a second-order digital phase-locked loop.

PubMed

Gdeisat, M A; Burton, D R; Lalor, M J

2000-10-10

The use of a second-order digital phase-locked loop (DPLL) to demodulate fringe patterns is presented. The second-order DPLL has better tracking ability and more noise immunity than the first-order loop. Consequently, the second-order DPLL is capable of demodulating a wider range of fringe patterns than the first-order DPLL. A basic analysis of the first- and the second-order loops is given, and a performance comparison between the first- and the second-order DPLL's in analyzing fringe patterns is presented. The implementation of the second-order loop in real time on a commercial parallel image processing system is described. Fringe patterns are grabbed and processed, and the resultant phase maps are displayed concurrently.

X-ray backscatter radiography with lower open fraction coded masks

NASA Astrophysics Data System (ADS)

Muñoz, André A. M.; Vella, Anna; Healy, Matthew J. F.; Lane, David W.; Jupp, Ian; Lockley, David

2017-09-01

Single sided radiographic imaging would find great utility for medical, aerospace and security applications. While coded apertures can be used to form such an image from backscattered X-rays they suffer from near field limitations that introduce noise. Several theoretical studies have indicated that for an extended source the images signal to noise ratio may be optimised by using a low open fraction (<0.5) mask. However, few experimental results have been published for such low open fraction patterns and details of their formulation are often unavailable or are ambiguous. In this paper we address this process for two types of low open fraction mask, the dilute URA and the Singer set array. For the dilute URA the procedure for producing multiple 2D array patterns from given 1D binary sequences (Barker codes) is explained. Their point spread functions are calculated and their imaging properties are critically reviewed. These results are then compared to those from the Singer set and experimental exposures are presented for both type of pattern; their prospects for near field imaging are discussed.

Meta-image navigation augmenters for GPS denied mountain navigation of small UAS

NASA Astrophysics Data System (ADS)

Wang, Teng; ćelik, Koray; Somani, Arun K.

2014-06-01

We present a novel approach to use mountain drainage patterns for GPS-Denied navigation of small unmanned aerial systems (UAS) such as the ScanEagle, utilizing a down-looking fixed focus monocular imager. Our proposal allows extension of missions to GPS-denied mountain areas, with no assumption of human-made geographic objects. We leverage the analogy between mountain drainage patterns, human arteriograms, and human fingerprints, to match local drainage patterns to Graphics Processing Unit (GPU) rendered parallax occlusion maps of geo-registered radar returns (GRRR). Details of our actual GPU algorithm is beyond the subject of this paper, and is planned as a future paper. The matching occurs in real-time, while GRRR data is loaded on-board the aircraft pre-mission, so as not to require a scanning aperture radar during the mission. For recognition purposes, we represent a given mountain area with a set of spatially distributed mountain minutiae, i.e., details found in the drainage patterns, so that conventional minutiae-based fingerprint matching approaches can be used to match real-time camera image against template images in the training set. We use medical arteriography processing techniques to extract the patterns. The minutiae-based representation of mountains is achieved by first exposing mountain ridges and valleys with a series of filters and then extracting mountain minutiae from these ridges/valleys. Our results are experimentally validated on actual terrain data and show the effectiveness of minutiae-based mountain representation method. Furthermore, we study how to select landmarks for UAS navigation based on the proposed mountain representation and give a set of examples to show its feasibility. This research was in part funded by Rockwell Collins Inc.

Visual information processing II; Proceedings of the Meeting, Orlando, FL, Apr. 14-16, 1993

NASA Technical Reports Server (NTRS)

Huck, Friedrich O. (Editor); Juday, Richard D. (Editor)

1993-01-01

Various papers on visual information processing are presented. Individual topics addressed include: aliasing as noise, satellite image processing using a hammering neural network, edge-detetion method using visual perception, adaptive vector median filters, design of a reading test for low-vision image warping, spatial transformation architectures, automatic image-enhancement method, redundancy reduction in image coding, lossless gray-scale image compression by predictive GDF, information efficiency in visual communication, optimizing JPEG quantization matrices for different applications, use of forward error correction to maintain image fidelity, effect of peanoscanning on image compression. Also discussed are: computer vision for autonomous robotics in space, optical processor for zero-crossing edge detection, fractal-based image edge detection, simulation of the neon spreading effect by bandpass filtering, wavelet transform (WT) on parallel SIMD architectures, nonseparable 2D wavelet image representation, adaptive image halftoning based on WT, wavelet analysis of global warming, use of the WT for signal detection, perfect reconstruction two-channel rational filter banks, N-wavelet coding for pattern classification, simulation of image of natural objects, number-theoretic coding for iconic systems.

High-speed 3D imaging using digital binary defocusing method vs sinusoidal method

NASA Astrophysics Data System (ADS)

Zhang, Song; Hyun, Jae-Sang; Li, Beiwen

2017-02-01

This paper presents our research findings on high-speed 3D imaging using digital light processing (DLP) technologies. In particular, we compare two different sinusoidal fringe generation techniques using the DLP projection devices: direct projection of 8-bit computer generated sinusoidal patterns (a.k.a, the sinusoidal method), and the creation of sinusoidal patterns by defocusing binary patterns (a.k.a., the binary defocusing method). This paper mainly examines their performance on high-accuracy measurement applications under precisely controlled settings. Two different projection systems were tested in this study: the commercially available inexpensive projector, and the DLP development kit. Experimental results demonstrated that the binary defocusing method always outperforms the sinusoidal method if a sufficient number of phase-shifted fringe patterns can be used.

Multi-Probe SPM using Interference Patterns for a Parallel Nano Imaging

NASA Astrophysics Data System (ADS)

Koyama, Hirotaka; Oohira, Fumikazu; Hosogi, Maho; Hashiguchi, Gen

This paper proposes a new composition of the multi-probe using optical interference patterns for a parallel nano imaging in a large area scanning. We achieved large-scale integration with 50,000 probes fabricated with MEMS technology, and measured the optical interference patterns with CCD, which was difficult in a conventional single scanning probe. In this research, the multi-probes are made of Si3N4 by MEMS process, and, the multi-probes are joined with a Pyrex glass by an anodic bonding. We designed, fabricated, and evaluated the characteristics of the probe. In addition, we changed the probe shape to decrease the warpage of the Si3N4 probe. We used the supercritical drying to avoid stiction of the Si3N4 probe with the glass surface and fabricated 4 types of the probe shapes without stiction. We took some interference patterns by CCD and measured the position of them. We calculate the probe height using the interference displacement and compared the result with the theoretical deflection curve. As a result, these interference patterns matched the theoretical deflection curve. We found that this multi-probe chip using interference patterns is effective in measurement for a parallel nano imaging.

Beyond arousal and valence: the importance of the biological versus social relevance of emotional stimuli.

PubMed

Sakaki, Michiko; Niki, Kazuhisa; Mather, Mara

2012-03-01

The present study addressed the hypothesis that emotional stimuli relevant to survival or reproduction (biologically emotional stimuli) automatically affect cognitive processing (e.g., attention, memory), while those relevant to social life (socially emotional stimuli) require elaborative processing to modulate attention and memory. Results of our behavioral studies showed that (1) biologically emotional images hold attention more strongly than do socially emotional images, (2) memory for biologically emotional images was enhanced even with limited cognitive resources, but (3) memory for socially emotional images was enhanced only when people had sufficient cognitive resources at encoding. Neither images' subjective arousal nor their valence modulated these patterns. A subsequent functional magnetic resonance imaging study revealed that biologically emotional images induced stronger activity in the visual cortex and greater functional connectivity between the amygdala and visual cortex than did socially emotional images. These results suggest that the interconnection between the amygdala and visual cortex supports enhanced attention allocation to biological stimuli. In contrast, socially emotional images evoked greater activity in the medial prefrontal cortex (MPFC) and yielded stronger functional connectivity between the amygdala and MPFC than did biological images. Thus, it appears that emotional processing of social stimuli involves elaborative processing requiring frontal lobe activity.

A new method of SC image processing for confluence estimation.

PubMed

Soleimani, Sajjad; Mirzaei, Mohsen; Toncu, Dana-Cristina

2017-10-01

Stem cells images are a strong instrument in the estimation of confluency during their culturing for therapeutic processes. Various laboratory conditions, such as lighting, cell container support and image acquisition equipment, effect on the image quality, subsequently on the estimation efficiency. This paper describes an efficient image processing method for cell pattern recognition and morphological analysis of images that were affected by uneven background. The proposed algorithm for enhancing the image is based on coupling a novel image denoising method through BM3D filter with an adaptive thresholding technique for improving the uneven background. This algorithm works well to provide a faster, easier, and more reliable method than manual measurement for the confluency assessment of stem cell cultures. The present scheme proves to be valid for the prediction of the confluency and growth of stem cells at early stages for tissue engineering in reparatory clinical surgery. The method used in this paper is capable of processing the image of the cells, which have already contained various defects due to either personnel mishandling or microscope limitations. Therefore, it provides proper information even out of the worst original images available. Copyright © 2017 Elsevier Ltd. All rights reserved.

Spatial memory and integration processes in congenital blindness.

PubMed

Vecchi, Tomaso; Tinti, Carla; Cornoldi, Cesare

2004-12-22

The paper tests the hypothesis that difficulties met by the blind in spatial processing are due to the simultaneous treatment of independent spatial representations. Results showed that lack of vision does not impede the ability to process and transform mental images; however, blind people are significantly poorer in the recall of more than a single spatial pattern at a time than in the recall of the corresponding material integrated into a single pattern. It is concluded that the simultaneous maintenance of different spatial information is affected by congenital blindness, while cognitive processes that may involve sequential manipulation are not.

All Source Sensor Analysis

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

- PNNL, Harold Trease

2012-10-10

ASSA is a software application that processes binary data into summarized index tables that can be used to organize features contained within the data. ASSA's index tables can also be used to search for user specified features. ASSA is designed to organize and search for patterns in unstructured binary data streams or archives, such as video, images, audio, and network traffic. ASSA is basically a very general search engine used to search for any pattern in any binary data stream. It has uses in video analytics, image analysis, audio analysis, searching hard-drives, monitoring network traffic, etc.

Simple agarose micro-confinement array and machine-learning-based classification for analyzing the patterned differentiation of mesenchymal stem cells

PubMed Central

Sato, Asako; Vogel, Viola; Tanaka, Yo

2017-01-01

The geometrical confinement of small cell colonies gives differential cues to cells sitting at the periphery versus the core. To utilize this effect, for example to create spatially graded differentiation patterns of human mesenchymal stem cells (hMSCs) in vitro or to investigate underpinning mechanisms, the confinement needs to be robust for extended time periods. To create highly repeatable micro-fabricated structures for cellular patterning and high-throughput data mining, we employed here a simple casting method to fabricate more than 800 adhesive patches confined by agarose micro-walls. In addition, a machine learning based image processing software was developed (open code) to detect the differentiation patterns of the population of hMSCs automatically. Utilizing the agarose walls, the circular patterns of hMSCs were successfully maintained throughout 15 days of cell culture. After staining lipid droplets and alkaline phosphatase as the markers of adipogenic and osteogenic differentiation, respectively, the mega-pixels of RGB color images of hMSCs were processed by the software on a laptop PC within several minutes. The image analysis successfully showed that hMSCs sitting on the more central versus peripheral sections of the adhesive circles showed adipogenic versus osteogenic differentiation as reported previously, indicating the compatibility of patterned agarose walls to conventional microcontact printing. In addition, we found a considerable fraction of undifferentiated cells which are preferentially located at the peripheral part of the adhesive circles, even in differentiation-inducing culture media. In this study, we thus successfully demonstrated a simple framework for analyzing the patterned differentiation of hMSCs in confined microenvironments, which has a range of applications in biology, including stem cell biology. PMID:28380036

Imaging wet granules with different flow patterns by electrical capacitance tomography and microwave tomography

NASA Astrophysics Data System (ADS)

Wang, H. G.; Zhang, J. L.; Ramli, M. F.; Mao, M. X.; Ye, J. M.; Yang, W. Q.; Wu, Z. P.

2016-11-01

The moisture content of granules in fluidised bed drying, granulation and coating processes can typically be between 1%~25%, resulting in the change of permittivity and conductivity during the processes. Electrical capacitance tomography (ECT) has been used for this purpose, but has a limit because too much water can cause a problem in capacitance measurement. Considering that microwave tomography (MWT) has a wide range of frequency (1~2.5 GHz) and can be used to measure materials with high permittivity and conductivity, the objective of this research is to combine ECT and MWT together to investigate the solids concentration with different moisture content and different flow patterns. The measurement results show that both ECT and MWT are functions of moisture content as well as flow patterns, and their measurements are complementary to each other. This is the first time that these two tomography modalities have been combined together and applied to image the complex solids distribution. The obtained information may be used for the process control of fluidised bed drying, granulation and coating to improve operation efficiency.

Wide-bandgap III-Nitride based Second Harmonic Generation

DTIC Science & Technology

2014-10-02

fabrication process for a GaN LPS. Fig. 1: 3-step Fabrication process of a GaN based lateral polar structure. ( a ) Growth of a 20 nm AlN buffer layer...etching of the LT-AlN stripes. This results are shown in Fig. 2 ( a ) and (b). Fig. 2: AFM images of KOH ( a ) and RIE (b) patterned templates for lateral ...was varied between 0.6 - 1.0. FIG. 3: Growth process of AlGaN based Lateral Polar Structures. ( a ) RIE patterning. (b) Growth of HT- AlN. (c

The magic of image processing

NASA Astrophysics Data System (ADS)

Sulentic, Jack W.; Lorre, Jean J.

1984-05-01

Digital technology has been used to improve enhancement techniques in astronomical image processing. Continuous tone variations in photographs are assigned density number (DN) values which are arranged in an array. DN locations are processed by computer and turned into pixels which form a reconstruction of the original scene on a television monitor. Digitized data can be manipulated to enhance contrast and filter out gross patterns of light and dark which obscure small scale features. Separate black and white frames exposed at different wavelengths can be digitized and processed individually, then recombined to produce a final image in color. Several examples of the use of the technique are provided, including photographs of spiral galaxy M33; four galaxies in Coma Berenices (NGC 4169, 4173, 4174, and 4175); and Stephens Quintet.

Patterns recognition of electric brain activity using artificial neural networks

NASA Astrophysics Data System (ADS)

Musatov, V. Yu.; Pchelintseva, S. V.; Runnova, A. E.; Hramov, A. E.

2017-04-01

An approach for the recognition of various cognitive processes in the brain activity in the perception of ambiguous images. On the basis of developed theoretical background and the experimental data, we propose a new classification of oscillating patterns in the human EEG by using an artificial neural network approach. After learning of the artificial neural network reliably identified cube recognition processes, for example, left-handed or right-oriented Necker cube with different intensity of their edges, construct an artificial neural network based on Perceptron architecture and demonstrate its effectiveness in the pattern recognition of the EEG in the experimental.

Optical Measurement of Cell Colonization Patterns on Individual Suspended Sediment Aggregates

NASA Astrophysics Data System (ADS)

Nguyen, Thu Ha; Tang, Fiona H. M.; Maggi, Federico

2017-10-01

Microbial processes can make substantial differences to the way in which particles settle in aquatic environments. A novel method (OMCEC, optical measurement of cell colonization) is introduced to systematically map the biological spatial distribution over individual suspended sediment aggregates settling through a water column. OMCEC was used to investigate (1) whether a carbon source concentration has an impact on cell colonization, (2) how cells colonize minerals, and (3) if a correlation between colonization patterns and aggregate geometry exists. Incubations of Saccharomyces cerevisiae and stained montmorillonite at four sucrose concentrations were tested in a settling column equipped with a full-color microparticle image velocimetry system. The acquired high-resolution images were processed to map the cell distribution on aggregates based on emission spectra separation. The likelihood of cells colonizing minerals increased with increasing sucrose concentration. Colonization patterns were classified into (i) scattered, (ii) well touched, and (iii) poorly touched, with the second being predominant. Cell clusters in well-touched patterns were found to have lower capacity dimension than those in other patterns, while the capacity dimension of the corresponding aggregates was relatively high. A strong correlation of colonization patterns with aggregate biomass fraction and properties suggests dynamic colonization mechanisms from cell attachment to minerals, to joining of isolated cell clusters, and finally cell growth over the entire aggregate. This paper introduces a widely applicable method for analyses of microbial-affected sediment dynamics and highlights the microbial control on aggregate geometry, which can improve the prediction of large-scale morphodynamics processes.

Patterning control strategies for minimum edge placement error in logic devices

NASA Astrophysics Data System (ADS)

Mulkens, Jan; Hanna, Michael; Slachter, Bram; Tel, Wim; Kubis, Michael; Maslow, Mark; Spence, Chris; Timoshkov, Vadim

2017-03-01

In this paper we discuss the edge placement error (EPE) for multi-patterning semiconductor manufacturing. In a multi-patterning scheme the creation of the final pattern is the result of a sequence of lithography and etching steps, and consequently the contour of the final pattern contains error sources of the different process steps. We describe the fidelity of the final pattern in terms of EPE, which is defined as the relative displacement of the edges of two features from their intended target position. We discuss our holistic patterning optimization approach to understand and minimize the EPE of the final pattern. As an experimental test vehicle we use the 7-nm logic device patterning process flow as developed by IMEC. This patterning process is based on Self-Aligned-Quadruple-Patterning (SAQP) using ArF lithography, combined with line cut exposures using EUV lithography. The computational metrology method to determine EPE is explained. It will be shown that ArF to EUV overlay, CDU from the individual process steps, and local CD and placement of the individual pattern features, are the important contributors. Based on the error budget, we developed an optimization strategy for each individual step and for the final pattern. Solutions include overlay and CD metrology based on angle resolved scatterometry, scanner actuator control to enable high order overlay corrections and computational lithography optimization to minimize imaging induced pattern placement errors of devices and metrology targets.

Real-time blood flow visualization using the graphics processing unit

NASA Astrophysics Data System (ADS)

Yang, Owen; Cuccia, David; Choi, Bernard

2011-01-01

Laser speckle imaging (LSI) is a technique in which coherent light incident on a surface produces a reflected speckle pattern that is related to the underlying movement of optical scatterers, such as red blood cells, indicating blood flow. Image-processing algorithms can be applied to produce speckle flow index (SFI) maps of relative blood flow. We present a novel algorithm that employs the NVIDIA Compute Unified Device Architecture (CUDA) platform to perform laser speckle image processing on the graphics processing unit. Software written in C was integrated with CUDA and integrated into a LabVIEW Virtual Instrument (VI) that is interfaced with a monochrome CCD camera able to acquire high-resolution raw speckle images at nearly 10 fps. With the CUDA code integrated into the LabVIEW VI, the processing and display of SFI images were performed also at ~10 fps. We present three video examples depicting real-time flow imaging during a reactive hyperemia maneuver, with fluid flow through an in vitro phantom, and a demonstration of real-time LSI during laser surgery of a port wine stain birthmark.

Real-time blood flow visualization using the graphics processing unit

PubMed Central

Yang, Owen; Cuccia, David; Choi, Bernard

2011-01-01

Laser speckle imaging (LSI) is a technique in which coherent light incident on a surface produces a reflected speckle pattern that is related to the underlying movement of optical scatterers, such as red blood cells, indicating blood flow. Image-processing algorithms can be applied to produce speckle flow index (SFI) maps of relative blood flow. We present a novel algorithm that employs the NVIDIA Compute Unified Device Architecture (CUDA) platform to perform laser speckle image processing on the graphics processing unit. Software written in C was integrated with CUDA and integrated into a LabVIEW Virtual Instrument (VI) that is interfaced with a monochrome CCD camera able to acquire high-resolution raw speckle images at nearly 10 fps. With the CUDA code integrated into the LabVIEW VI, the processing and display of SFI images were performed also at ∼10 fps. We present three video examples depicting real-time flow imaging during a reactive hyperemia maneuver, with fluid flow through an in vitro phantom, and a demonstration of real-time LSI during laser surgery of a port wine stain birthmark. PMID:21280915

Automatic assessment of mitral regurgitation severity based on extensive textural features on 2D echocardiography videos.

PubMed

Moghaddasi, Hanie; Nourian, Saeed

2016-06-01

Heart disease is the major cause of death as well as a leading cause of disability in the developed countries. Mitral Regurgitation (MR) is a common heart disease which does not cause symptoms until its end stage. Therefore, early diagnosis of the disease is of crucial importance in the treatment process. Echocardiography is a common method of diagnosis in the severity of MR. Hence, a method which is based on echocardiography videos, image processing techniques and artificial intelligence could be helpful for clinicians, especially in borderline cases. In this paper, we introduce novel features to detect micro-patterns of echocardiography images in order to determine the severity of MR. Extensive Local Binary Pattern (ELBP) and Extensive Volume Local Binary Pattern (EVLBP) are presented as image descriptors which include details from different viewpoints of the heart in feature vectors. Support Vector Machine (SVM), Linear Discriminant Analysis (LDA) and Template Matching techniques are used as classifiers to determine the severity of MR based on textural descriptors. The SVM classifier with Extensive Uniform Local Binary Pattern (ELBPU) and Extensive Volume Local Binary Pattern (EVLBP) have the best accuracy with 99.52%, 99.38%, 99.31% and 99.59%, respectively, for the detection of Normal, Mild MR, Moderate MR and Severe MR subjects among echocardiography videos. The proposed method achieves 99.38% sensitivity and 99.63% specificity for the detection of the severity of MR and normal subjects. Copyright © 2016 Elsevier Ltd. All rights reserved.

Histopathologic correlation of magnetic resonance imaging signal patterns in a spinal cord injury model.

PubMed

Weirich, S D; Cotler, H B; Narayana, P A; Hazle, J D; Jackson, E F; Coupe, K J; McDonald, C L; Langford, L A; Harris, J H

1990-07-01

Magnetic resonance imaging (MRI) provides a noninvasive method of monitoring the pathologic response to spinal cord injury. Specific MR signal intensity patterns appear to correlate with degrees of improvement in the neurologic status in spinal cord injury patients. Histologic correlation of two types of MR signal intensity patterns are confirmed in the current study using a rat animal model. Adult male Sprague-Dawley rats underwent spinal cord trauma at the midthoracic level using a weight-dropping technique. After laminectomy, 5- and 10-gm brass weights were dropped from designated heights onto a 0.1-gm impounder placed on the exposed dura. Animals allowed to regain consciousness demonstrated variable recovery of hind limb paraplegia. Magnetic resonance images were obtained from 2 hours to 1 week after injury using a 2-tesla MRI/spectrometer. Sacrifice under anesthesia was performed by perfusive fixation; spinal columns were excised en bloc, embedded, sectioned, and observed with the compound light microscope. Magnetic resonance axial images obtained during the time sequence after injury demonstrate a distinct correlation between MR signal intensity patterns and the histologic appearance of the spinal cord. Magnetic resonance imaging delineates the pathologic processes resulting from acute spinal cord injury and can be used to differentiate the type of injury and prognosis.

Optical coherence tomography in differential diagnosis of skin pathology

NASA Astrophysics Data System (ADS)

Gladkova, Natalia D.; Petrova, Galina P.; Derpaluk, Elena; Nikulin, Nikolai K.; Snopova, Ludmila; Chumakov, Yuri; Feldchtein, Felix I.; Gelikonov, Valentin M.; Gelikonov, Grigory V.; Kuranov, Roman V.

2000-05-01

The capabilities of optical coherence tomography (OCT) for imaging in vivo of optical patterns of pathomorphological processes in the skin and use of their optical patterns in clinical practice for differential diagnosis of dermatoses are presented. Images of skin tissue 0.8 - 1.5 mm deep were acquired with a resolution of 5, 12 and 20 micrometer using three compact fiber OCT devices developed at the Institute of Applied Physics RAS. The acquisition time of images of skin regions 2 - 6 mm in length was 2 - 4 s. The OCT capabilities were analyzed based on the study of 50 patients with different dermatoses. OCT images were interpreted by comparing with parallel histology. It is shown that OCT can detect in vivo optical patterns of morphological alterations in such general papulous dermatoses as lichen ruber planus and psoriasis, a capability that can be used in differential diagnosis of these diseases. Most informative are OCT images obtained with a resolution of 5 micrometer. The results of our study demonstrate the practical importance of OCT imaging for diagnosis of different dermatoses. OCT is noninvasive and, therefore, makes it possible to perform frequent multifocal examination of skin without any adverse effects.

Method for determining and displaying the spacial distribution of a spectral pattern of received light

DOEpatents

Bennett, C.L.

1996-07-23

An imaging Fourier transform spectrometer is described having a Fourier transform infrared spectrometer providing a series of images to a focal plane array camera. The focal plane array camera is clocked to a multiple of zero crossing occurrences as caused by a moving mirror of the Fourier transform infrared spectrometer and as detected by a laser detector such that the frame capture rate of the focal plane array camera corresponds to a multiple of the zero crossing rate of the Fourier transform infrared spectrometer. The images are transmitted to a computer for processing such that representations of the images as viewed in the light of an arbitrary spectral ``fingerprint`` pattern can be displayed on a monitor or otherwise stored and manipulated by the computer. 2 figs.

Dynamic Speckle Imaging with Low-Cost Devices

ERIC Educational Resources Information Center

Vannoni, Maurizio; Trivi, Marcelo; Arizaga, Ricardo; Rabal, Hector; Molesini, Giuseppe

2008-01-01

Light from a rough sample surface illuminated with a laser consists of a speckle pattern. If the surface evolves with time, the pattern becomes dynamic, following the activity of the sample. This phenomenon is used both in research and in industry to monitor processes and systems that change with time. The measuring equipment generally includes…

Comparison of line shortening assessed by aerial image and wafer measurements

NASA Astrophysics Data System (ADS)

Ziegler, Wolfram; Pforr, Rainer; Thiele, Joerg; Maurer, Wilhelm

1997-02-01

Increasing number of patterns per area and decreasing linewidth demand enhancement technologies for optical lithography. OPC, the correction of systematic non-linearity in the pattern transfer process by correction of design data is one possibility to tighten process control and to increase the lifetime of existing lithographic equipment. The two most prominent proximity effects to be corrected by OPC are CD variation and line shortening. Line shortening measured on a wafer is up to 2 times larger than full resist simulation results. Therefore, the influence of mask geometry to line shortening is a key item to parameterize lithography. The following paper discusses the effect of adding small serifs to line ends with 0.25 micrometer ground-rule design. For reticles produced on an ALTA 3000 with standard wet etch process, the corner rounding on them mask can be reduced by adding serifs of a certain size. The corner rounding was measured and the effect on line shortening on the wafer is determined. This was investigated by resist measurements on wafer, aerial image plus resist simulation and aerial image measurements on the AIMS microscope.

Exogenic and endogenic albedo and color patterns on Europa

NASA Technical Reports Server (NTRS)

Mcewen, A. S.

1986-01-01

New global and high-resolution multispectral mosaics of Europa have been produced from the Voyager imaging data. Photometric normalizations are based on multiple-image techniques that explicitly account for intrinsic albedo variations through pixel-by-pixel solutions. The exogenic color and albedo pattern on Europa is described by a second-order function of the cosine of the angular distance from the apex of orbital motion. On the basis of this second-order function and of color trends that are different on the leading and trailing hemispheres, the exogenic pattern is interpreted as being due to equilibrium between two dominant processes: (1) impact gardening and (2) magnetospheric interactions, including sulfur-ion implantation and sputtering redistribution. Removal of the model exogenic pattern in the mosaics reveals the endogenic variations, consisting of only two major units: darker (redder) and bright materials. Therefore Europa's visual spectral reflectivity is simple, having one continuous exogenic pattern and two discrete endogenic units.

Patterning optimization for 55nm design rule DRAM/flash memory using production-ready customized illuminations

NASA Astrophysics Data System (ADS)

Chen, Ting; Van Den Broeke, Doug; Hsu, Stephen; Hsu, Michael; Park, Sangbong; Berger, Gabriel; Coskun, Tamer; de Vocht, Joep; Chen, Fung; Socha, Robert; Park, JungChul; Gronlund, Keith

2005-11-01

Illumination optimization, often combined with optical proximity corrections (OPC) to the mask, is becoming one of the critical components for a production-worthy lithography process for 55nm-node DRAM/Flash memory devices and beyond. At low-k1, e.g. k1<0.31, both resolution and imaging contrast can be severely limited by the current imaging tools while using the standard illumination sources. Illumination optimization is a process where the source shape is varied, in both profile and intensity distribution, to achieve enhancement in the final image contrast as compared to using the non-optimized sources. The optimization can be done efficiently for repetitive patterns such as DRAM/Flash memory cores. However, illumination optimization often produces source shapes that are "free-form" like and they can be too complex to be directly applicable for production and lack the necessary radial and annular symmetries desirable for the diffractive optical element (DOE) based illumination systems in today's leading lithography tools. As a result, post-optimization rendering and verification of the optimized source shape are often necessary to meet the production-ready or manufacturability requirements and ensure optimal performance gains. In this work, we describe our approach to the illumination optimization for k1<0.31 DRAM/Flash memory patterns, using an ASML XT:1400i at NA 0.93, where the all necessary manufacturability requirements are fully accounted for during the optimization. The imaging contrast in the resist is optimized in a reduced solution space constrained by the manufacturability requirements, which include minimum distance between poles, minimum opening pole angles, minimum ring width and minimum source filling factor in the sigma space. For additional performance gains, the intensity within the optimized source can vary in a gray-tone fashion (eight shades used in this work). Although this new optimization approach can sometimes produce closely spaced solutions as gauged by the NILS based metrics, we show that the optimal and production-ready source shape solution can be easily determined by comparing the best solutions to the "free-form" solution and more importantly, by their respective imaging fidelity and process latitude ranking. Imaging fidelity and process latitude simulations are performed to analyze the impact and sensitivity of the manufacturability requirements on pattern specific illumination optimizations using ASML XT:1400i and other latest imaging systems. Mask model based OPC (MOPC) is applied and optimized sequentially to ensure that the CD uniformity requirements are met.

Inferring consistent functional interaction patterns from natural stimulus FMRI data

PubMed Central

Sun, Jiehuan; Hu, Xintao; Huang, Xiu; Liu, Yang; Li, Kaiming; Li, Xiang; Han, Junwei; Guo, Lei

2014-01-01

There has been increasing interest in how the human brain responds to natural stimulus such as video watching in the neuroimaging field. Along this direction, this paper presents our effort in inferring consistent and reproducible functional interaction patterns under natural stimulus of video watching among known functional brain regions identified by task-based fMRI. Then, we applied and compared four statistical approaches, including Bayesian network modeling with searching algorithms: greedy equivalence search (GES), Peter and Clark (PC) analysis, independent multiple greedy equivalence search (IMaGES), and the commonly used Granger causality analysis (GCA), to infer consistent and reproducible functional interaction patterns among these brain regions. It is interesting that a number of reliable and consistent functional interaction patterns were identified by the GES, PC and IMaGES algorithms in different participating subjects when they watched multiple video shots of the same semantic category. These interaction patterns are meaningful given current neuroscience knowledge and are reasonably reproducible across different brains and video shots. In particular, these consistent functional interaction patterns are supported by structural connections derived from diffusion tensor imaging (DTI) data, suggesting the structural underpinnings of consistent functional interactions. Our work demonstrates that specific consistent patterns of functional interactions among relevant brain regions might reflect the brain's fundamental mechanisms of online processing and comprehension of video messages. PMID:22440644

FIVQ algorithm for interference hyper-spectral image compression

NASA Astrophysics Data System (ADS)

Wen, Jia; Ma, Caiwen; Zhao, Junsuo

2014-07-01

Based on the improved vector quantization (IVQ) algorithm [1] which was proposed in 2012, this paper proposes a further improved vector quantization (FIVQ) algorithm for LASIS (Large Aperture Static Imaging Spectrometer) interference hyper-spectral image compression. To get better image quality, IVQ algorithm takes both the mean values and the VQ indices as the encoding rules. Although IVQ algorithm can improve both the bit rate and the image quality, it still can be further improved in order to get much lower bit rate for the LASIS interference pattern with the special optical characteristics based on the pushing and sweeping in LASIS imaging principle. In the proposed algorithm FIVQ, the neighborhood of the encoding blocks of the interference pattern image, which are using the mean value rules, will be checked whether they have the same mean value as the current processing block. Experiments show the proposed algorithm FIVQ can get lower bit rate compared to that of the IVQ algorithm for the LASIS interference hyper-spectral sequences.

Computation of the intensities of parametric holographic scattering patterns in photorefractive crystals.

PubMed

Schwalenberg, Simon

2005-06-01

The present work represents a first attempt to perform computations of output intensity distributions for different parametric holographic scattering patterns. Based on the model for parametric four-wave mixing processes in photorefractive crystals and taking into account realistic material properties, we present computed images of selected scattering patterns. We compare these calculated light distributions to the corresponding experimental observations. Our analysis is especially devoted to dark scattering patterns as they make high demands on the underlying model.

Usefulness of tissue autofluorescence imaging in actinic cheilitis diagnosis.

PubMed

Takahama Junior, Ademar; Kurachi, Cristina; Cosci, Alessandro; Pereira Faustino, Isabel Schausltz; Camisasca, Danielle Resende; da Costa Fontes, Karla Bianca Fernandes; Pires, Fábio Ramôa; Azevedo, Rebeca Souza

2013-07-01

Actinic cheilitis (AC) is a potentially malignant disorder of the lips. Because of its heterogeneous clinical aspect, it is difficult to indicate representative biopsy area. The purpose of this study was to evaluate the usefulness of tissue autofluorescence in AC diagnosis. The system was composed of a 405-nm light-emitting diode, sent to the sample by a dichroic, that allows the fluorescence signal to reach a camera directly plugged in the system. Fifty-seven patients with clinical diagnosis of AC and 45 normal volunteers were selected. According to clinical and fluorescence features, one or more areas were selected for biopsies in the AC group and epithelial dysplasia (ED) grades were established. The autofluorescence images were processed by a clustering algorithm for AC automated diagnosis. The tissue autofluorescence image revealed a heterogeneous pattern of loss and increase of fluorescence in patients with AC. ED was found in 93% of the cases, and most of the areas graded as moderate or severe ED were chosen with the aid of autofluorescence. The processed autofluorescence images from AC patients showed a higher number of spots in an irregular pattern. Tissue autofluorescence image system is a useful technique in association with clinical examination for AC diagnosis.

Infrared fix pattern noise reduction method based on Shearlet Transform

NASA Astrophysics Data System (ADS)

Rong, Shenghui; Zhou, Huixin; Zhao, Dong; Cheng, Kuanhong; Qian, Kun; Qin, Hanlin

2018-06-01

The non-uniformity correction (NUC) is an effective way to reduce fix pattern noise (FPN) and improve infrared image quality. The temporal high-pass NUC method is a kind of practical NUC method because of its simple implementation. However, traditional temporal high-pass NUC methods rely deeply on the scene motion and suffer image ghosting and blurring. Thus, this paper proposes an improved NUC method based on Shearlet Transform (ST). First, the raw infrared image is decomposed into multiscale and multi-orientation subbands by ST and the FPN component mainly exists in some certain high-frequency subbands. Then, high-frequency subbands are processed by the temporal filter to extract the FPN due to its low-frequency characteristics. Besides, each subband has a confidence parameter to determine the degree of FPN, which is estimated by the variance of subbands adaptively. At last, the process of NUC is achieved by subtracting the estimated FPN component from the original subbands and the corrected infrared image can be obtained by the inverse ST. The performance of the proposed method is evaluated with real and synthetic infrared image sequences thoroughly. Experimental results indicate that the proposed method can reduce heavily FPN with less roughness and RMSE.

Beyond arousal and valence: The importance of the biological versus social relevance of emotional stimuli

PubMed Central

Sakaki, Michiko; Niki, Kazuhisa; Mather, Mara

2012-01-01

The present study addressed the hypothesis that emotional stimuli relevant to survival or reproduction (biologically emotional stimuli) automatically affect cognitive processing (e.g., attention; memory), while those relevant to social life (socially emotional stimuli) require elaborative processing to modulate attention and memory. Results of our behavioral studies showed that: a) biologically emotional images hold attention more strongly than socially emotional images, b) memory for biologically emotional images was enhanced even with limited cognitive resources, but c) memory for socially emotional images was enhanced only when people had sufficient cognitive resources at encoding. Neither images’ subjective arousal nor their valence modulated these patterns. A subsequent functional magnetic resonance imaging study revealed that biologically emotional images induced stronger activity in visual cortex and greater functional connectivity between amygdala and visual cortex than did socially emotional images. These results suggest that the interconnection between the amygdala and visual cortex supports enhanced attention allocation to biological stimuli. In contrast, socially emotional images evoked greater activity in medial prefrontal cortex (MPFC) and yielded stronger functional connectivity between amygdala and MPFC than biological images. Thus, it appears that emotional processing of social stimuli involves elaborative processing requiring frontal lobe activity. PMID:21964552

Functional Magnetic Resonance Imaging of Cognitive Processing in Young Adults with Down Syndrome

ERIC Educational Resources Information Center

Jacola, Lisa M.; Byars, Anna W.; Chalfonte-Evans, Melinda; Schmithorst, Vincent J.; Hickey, Fran; Patterson, Bonnie; Hotze, Stephanie; Vannest, Jennifer; Chiu, Chung-Yiu; Holland, Scott K.; Schapiro, Mark B.

2011-01-01

The authors used functional magnetic resonance imaging (fMRI) to investigate neural activation during a semantic-classification/object-recognition task in 13 persons with Down syndrome and 12 typically developing control participants (age range = 12-26 years). A comparison between groups suggested atypical patterns of brain activation for the…

Flow visualization studies of transverse fuel injection patterns in a nonreacting Mach 2 combustor

NASA Technical Reports Server (NTRS)

Mcdaniel, J. C.

1987-01-01

Planar visualization images are recorded of transverse jet mixing in a supersonic combustor flowfield, without chemical reaction, using laser-induced fluorescence from iodine molecules. Digital image processing and three-dimensional display enable complete representations of fuel penetration boundary and shock surfaces corresponding to several injection geometries and pressures.

Real-time simulation of the retina allowing visualization of each processing stage

NASA Astrophysics Data System (ADS)

Teeters, Jeffrey L.; Werblin, Frank S.

1991-08-01

The retina computes to let us see, but can we see the retina compute? Until now, the answer has been no, because the unconscious nature of the processing hides it from our view. Here the authors describe a method of seeing computations performed throughout the retina. This is achieved by using neurophysiological data to construct a model of the retina, and using a special-purpose image processing computer (PIPE) to implement the model in real time. Processing in the model is organized into stages corresponding to computations performed by each retinal cell type. The final stage is the transient (change detecting) ganglion cell. A CCD camera forms the input image, and the activity of a selected retinal cell type is the output which is displayed on a TV monitor. By changing the retina cell driving the monitor, the progressive transformations of the image by the retina can be observed. These simulations demonstrate the ubiquitous presence of temporal and spatial variations in the patterns of activity generated by the retina which are fed into the brain. The dynamical aspects make these patterns very different from those generated by the common DOG (Difference of Gaussian) model of receptive field. Because the retina is so successful in biological vision systems, the processing described here may be useful in machine vision.

Sign Language Recognition System using Neural Network for Digital Hardware Implementation

NASA Astrophysics Data System (ADS)

Vargas, Lorena P.; Barba, Leiner; Torres, C. O.; Mattos, L.

2011-01-01

This work presents an image pattern recognition system using neural network for the identification of sign language to deaf people. The system has several stored image that show the specific symbol in this kind of language, which is employed to teach a multilayer neural network using a back propagation algorithm. Initially, the images are processed to adapt them and to improve the performance of discriminating of the network, including in this process of filtering, reduction and elimination noise algorithms as well as edge detection. The system is evaluated using the signs without including movement in their representation.

Multiple Point Statistics algorithm based on direct sampling and multi-resolution images

NASA Astrophysics Data System (ADS)

Julien, S.; Renard, P.; Chugunova, T.

2017-12-01

Multiple Point Statistics (MPS) has become popular for more than one decade in Earth Sciences, because these methods allow to generate random fields reproducing highly complex spatial features given in a conceptual model, the training image, while classical geostatistics techniques based on bi-point statistics (covariance or variogram) fail to generate realistic models. Among MPS methods, the direct sampling consists in borrowing patterns from the training image to populate a simulation grid. This latter is sequentially filled by visiting each of these nodes in a random order, and then the patterns, whose the number of nodes is fixed, become narrower during the simulation process, as the simulation grid is more densely informed. Hence, large scale structures are caught in the beginning of the simulation and small scale ones in the end. However, MPS may mix spatial characteristics distinguishable at different scales in the training image, and then loose the spatial arrangement of different structures. To overcome this limitation, we propose to perform MPS simulation using a decomposition of the training image in a set of images at multiple resolutions. Applying a Gaussian kernel onto the training image (convolution) results in a lower resolution image, and iterating this process, a pyramid of images depicting fewer details at each level is built, as it can be done in image processing for example to lighten the space storage of a photography. The direct sampling is then employed to simulate the lowest resolution level, and then to simulate each level, up to the finest resolution, conditioned to the level one rank coarser. This scheme helps reproduce the spatial structures at any scale of the training image and then generate more realistic models. We illustrate the method with aerial photographies (satellite images) and natural textures. Indeed, these kinds of images often display typical structures at different scales and are well-suited for MPS simulation techniques.

Right hemisphere performance and competence in processing mental images, in a case of partial interhemispheric disconnection.

PubMed

Blanc-Garin, J; Faure, S; Sabio, P

1993-05-01

The objective of this study was to analyze dynamic aspects of right hemisphere implementation in processing visual images. Two tachistoscopic, divided visual field experiments were carried out on a partial split-brain patient with no damage to the right hemisphere. In the first experiment, image generation performance for letters presented in the right visual field (/left hemisphere) was undeniably optimal. In the left visual field (/right hemisphere), performance was no better than chance level at first, but then improved dramatically across stimulation blocks, in each of five successive sessions. This was interpreted as revealing the progressive spontaneous activation of the right hemisphere's competence not shown initially. The aim of the second experiment was to determine some conditions under which this pattern was obtained. The experimental design contrasted stimuli (words and pictures) and representational activity (phonologic and visuo-imaged processing). The right visual field (/left hemisphere: LH) elicited higher performance than the left visual field (/right hemisphere, RH) in the three situations where verbal activity was required. No superiority could be found when visual images were to be generated from pictures: parallel and weak improvement of both hemispheres was observed across sessions. Two other patterns were obtained: improvement in RH performance (although LH performance remained superior) and an unexpectedly large decrease in RH performance. These data are discussed in terms of RH cognitive competence and hemisphere implementation.

Algorithms for Image Analysis and Combination of Pattern Classifiers with Application to Medical Diagnosis

NASA Astrophysics Data System (ADS)

Georgiou, Harris

2009-10-01

Medical Informatics and the application of modern signal processing in the assistance of the diagnostic process in medical imaging is one of the more recent and active research areas today. This thesis addresses a variety of issues related to the general problem of medical image analysis, specifically in mammography, and presents a series of algorithms and design approaches for all the intermediate levels of a modern system for computer-aided diagnosis (CAD). The diagnostic problem is analyzed with a systematic approach, first defining the imaging characteristics and features that are relevant to probable pathology in mammo-grams. Next, these features are quantified and fused into new, integrated radio-logical systems that exhibit embedded digital signal processing, in order to improve the final result and minimize the radiological dose for the patient. In a higher level, special algorithms are designed for detecting and encoding these clinically interest-ing imaging features, in order to be used as input to advanced pattern classifiers and machine learning models. Finally, these approaches are extended in multi-classifier models under the scope of Game Theory and optimum collective deci-sion, in order to produce efficient solutions for combining classifiers with minimum computational costs for advanced diagnostic systems. The material covered in this thesis is related to a total of 18 published papers, 6 in scientific journals and 12 in international conferences.

Fast in-situ tool inspection based on inverse fringe projection and compact sensor heads

NASA Astrophysics Data System (ADS)

Matthias, Steffen; Kästner, Markus; Reithmeier, Eduard

2016-11-01

Inspection of machine elements is an important task in production processes in order to ensure the quality of produced parts and to gather feedback for the continuous improvement process. A new measuring system is presented, which is capable of performing the inspection of critical tool geometries, such as gearing elements, inside the forming machine. To meet the constraints on sensor head size and inspection time imposed by the limited space inside the machine and the cycle time of the process, the measuring device employs a combination of endoscopy techniques with the fringe projection principle. Compact gradient index lenses enable a compact design of the sensor head, which is connected to a CMOS camera and a flexible micro-mirror based projector via flexible fiber bundles. Using common fringe projection patterns, the system achieves measuring times of less than five seconds. To further reduce the time required for inspection, the generation of inverse fringe projection patterns has been implemented for the system. Inverse fringe projection speeds up the inspection process by employing object-adapted patterns, which enable the detection of geometry deviations in a single image. Two different approaches to generate object adapted patterns are presented. The first approach uses a reference measurement of a manufactured tool master to generate the inverse pattern. The second approach is based on a virtual master geometry in the form of a CAD file and a ray-tracing model of the measuring system. Virtual modeling of the measuring device and inspection setup allows for geometric tolerancing for free-form surfaces by the tool designer in the CAD-file. A new approach is presented, which uses virtual tolerance specifications and additional simulation steps to enable fast checking of metric tolerances. Following the description of the pattern generation process, the image processing steps required for inspection are demonstrated on captures of gearing geometries.

64nm pitch metal1 double patterning metrology: CD and OVL control by SEMCD, image based overlay and diffraction based overlay

NASA Astrophysics Data System (ADS)

Ducoté, Julien; Dettoni, Florent; Bouyssou, Régis; Le-Gratiet, Bertrand; Carau, Damien; Dezauzier, Christophe

2015-03-01

Patterning process control of advanced nodes has required major changes over the last few years. Process control needs of critical patterning levels since 28nm technology node is extremely aggressive showing that metrology accuracy/sensitivity must be finely tuned. The introduction of pitch splitting (Litho-Etch-Litho-Etch) at 14FDSOInm node requires the development of specific metrologies to adopt advanced process control (for CD, overlay and focus corrections). The pitch splitting process leads to final line CD uniformities that are a combination of the CD uniformities of the two exposures, while the space CD uniformities are depending on both CD and OVL variability. In this paper, investigations of CD and OVL process control of 64nm minimum pitch at Metal1 level of 14FDSOI technology, within the double patterning process flow (Litho, hard mask etch, line etch) are presented. Various measurements with SEMCD tools (Hitachi), and overlay tools (KT for Image Based Overlay - IBO, and ASML for Diffraction Based Overlay - DBO) are compared. Metrology targets are embedded within a block instanced several times within the field to perform intra-field process variations characterizations. Specific SEMCD targets were designed for independent measurement of both line CD (A and B) and space CD (A to B and B to A) for each exposure within a single measurement during the DP flow. Based on those measurements correlation between overlay determined with SEMCD and with standard overlay tools can be evaluated. Such correlation at different steps through the DP flow is investigated regarding the metrology type. Process correction models are evaluated with respect to the measurement type and the intra-field sampling.

Multiple Scale Landscape Pattern Index Interpretation for the Persistent Monitoring of Land-Cover and Land-Use

NASA Astrophysics Data System (ADS)

Spivey, Alvin J.

Mapping land-cover land-use change (LCLUC) over regional and continental scales, and long time scales (years and decades), can be accomplished using thematically identified classification maps of a landscape---a LCLU class map. Observations of a landscape's LCLU class map pattern can indicate the most relevant process, like hydrologic or ecologic function, causing landscape scale environmental change. Quantified as Landscape Pattern Metrics (LPM), emergent landscape patterns act as Landscape Indicators (LI) when physically interpreted. The common mathematical approach to quantifying observed landscape scale pattern is to have LPM measure how connected a class exists within the landscape, through nonlinear local kernel operations of edges and gradients in class maps. Commonly applied kernel-based LPM that consistently reveal causal processes are Dominance, Contagion, and Fractal Dimension. These kernel-based LPM can be difficult to interpret. The emphasis on an image pixel's edge by gradient operations and dependence on an image pixel's existence according to classification accuracy limit the interpretation of LPM. For example, the Dominance and Contagion kernel-based LPM very similarly measure how connected a landscape is. Because of this, their reported edge measurements of connected pattern correlate strongly, making their results ambiguous. Additionally, each of these kernel-based LPM are unscalable when comparing class maps from separate imaging system sensor scenarios that change the image pixel's edge position (i.e. changes in landscape extent, changes in pixel size, changes in orientation, etc), and can only interpret landscape pattern as accurately as the LCLU map classification will allow. This dissertation discusses the reliability of common LPM in light of imaging system effects such as: algorithm classification likelihoods, LCLU classification accuracy due to random image sensor noise, and image scale. A description of an approach to generating well behaved LPM through a Fourier system analysis of the entire class map, or any subset of the class map (e.g. the watershed) is the focus of this work. The Fourier approach provides four improvements for LPM. First, the approach reduces any correlation between metrics by developing them within an independent (i.e. orthogonal) Fourier vector space; a Fourier vector space that includes relevant physically representative parameters ( i.e. between class Euclidean distance). Second, accounting for LCLU classification accuracy the LPM measurement precision and measurement accuracy are reported. Third, the mathematics of this approach makes it possible to compare image data captured at separate pixel resolutions or even from separate landscape scenes. Fourth, Fourier interpreted landscape pattern measurement can be a measure of the entire landscape shape, of individual landscape cover change, or as exchanges between class map subsets by operating on the entire class map, subset of class map, or separate subsets of class map[s] respectively. These LCLUC LPM are examined along the 1991-1992 and 2000-2001 records of National Land Cover Database Landsat data products. Those LPM results are used in a predictive fecal coliform model at the South Carolina watershed level in the context of past (validation study) change. Finally, the proposed LPM ability to be used as ecologically relevant environmental indicators is tested by correlating metrics with other, well known LI that consistently reveal causal processes in the literature.

Pattern recognition and image processing for environmental monitoring

NASA Astrophysics Data System (ADS)

Siddiqui, Khalid J.; Eastwood, DeLyle

1999-12-01

Pattern recognition (PR) and signal/image processing methods are among the most powerful tools currently available for noninvasively examining spectroscopic and other chemical data for environmental monitoring. Using spectral data, these systems have found a variety of applications employing analytical techniques for chemometrics such as gas chromatography, fluorescence spectroscopy, etc. An advantage of PR approaches is that they make no a prior assumption regarding the structure of the patterns. However, a majority of these systems rely on human judgment for parameter selection and classification. A PR problem is considered as a composite of four subproblems: pattern acquisition, feature extraction, feature selection, and pattern classification. One of the basic issues in PR approaches is to determine and measure the features useful for successful classification. Selection of features that contain the most discriminatory information is important because the cost of pattern classification is directly related to the number of features used in the decision rules. The state of the spectral techniques as applied to environmental monitoring is reviewed. A spectral pattern classification system combining the above components and automatic decision-theoretic approaches for classification is developed. It is shown how such a system can be used for analysis of large data sets, warehousing, and interpretation. In a preliminary test, the classifier was used to classify synchronous UV-vis fluorescence spectra of relatively similar petroleum oils with reasonable success.

Lensless digital holography with diffuse illumination through a pseudo-random phase mask.

PubMed

Bernet, Stefan; Harm, Walter; Jesacher, Alexander; Ritsch-Marte, Monika

2011-12-05

Microscopic imaging with a setup consisting of a pseudo-random phase mask, and an open CMOS camera, without an imaging objective, is demonstrated. The pseudo random phase mask acts as a diffuser for an incoming laser beam, scattering a speckle pattern to a CMOS chip, which is recorded once as a reference. A sample which is afterwards inserted somewhere in the optical beam path changes the speckle pattern. A single (non-iterative) image processing step, comparing the modified speckle pattern with the previously recorded one, generates a sharp image of the sample. After a first calibration the method works in real-time and allows quantitative imaging of complex (amplitude and phase) samples in an extended three-dimensional volume. Since no lenses are used, the method is free from lens abberations. Compared to standard inline holography the diffuse sample illumination improves the axial sectioning capability by increasing the effective numerical aperture in the illumination path, and it suppresses the undesired so-called twin images. For demonstration, a high resolution spatial light modulator (SLM) is programmed to act as the pseudo-random phase mask. We show experimental results, imaging microscopic biological samples, e.g. insects, within an extended volume at a distance of 15 cm with a transverse and longitudinal resolution of about 60 μm and 400 μm, respectively.

Scanning electron microscope automatic defect classification of process induced defects

NASA Astrophysics Data System (ADS)

Wolfe, Scott; McGarvey, Steve

2017-03-01

With the integration of high speed Scanning Electron Microscope (SEM) based Automated Defect Redetection (ADR) in both high volume semiconductor manufacturing and Research and Development (R and D), the need for reliable SEM Automated Defect Classification (ADC) has grown tremendously in the past few years. In many high volume manufacturing facilities and R and D operations, defect inspection is performed on EBeam (EB), Bright Field (BF) or Dark Field (DF) defect inspection equipment. A comma separated value (CSV) file is created by both the patterned and non-patterned defect inspection tools. The defect inspection result file contains a list of the inspection anomalies detected during the inspection tools' examination of each structure, or the examination of an entire wafers surface for non-patterned applications. This file is imported into the Defect Review Scanning Electron Microscope (DRSEM). Following the defect inspection result file import, the DRSEM automatically moves the wafer to each defect coordinate and performs ADR. During ADR the DRSEM operates in a reference mode, capturing a SEM image at the exact position of the anomalies coordinates and capturing a SEM image of a reference location in the center of the wafer. A Defect reference image is created based on the Reference image minus the Defect image. The exact coordinates of the defect is calculated based on the calculated defect position and the anomalies stage coordinate calculated when the high magnification SEM defect image is captured. The captured SEM image is processed through either DRSEM ADC binning, exporting to a Yield Analysis System (YAS), or a combination of both. Process Engineers, Yield Analysis Engineers or Failure Analysis Engineers will manually review the captured images to insure that either the YAS defect binning is accurately classifying the defects or that the DRSEM defect binning is accurately classifying the defects. This paper is an exploration of the feasibility of the utilization of a Hitachi RS4000 Defect Review SEM to perform Automatic Defect Classification with the objective of the total automated classification accuracy being greater than human based defect classification binning when the defects do not require multiple process step knowledge for accurate classification. The implementation of DRSEM ADC has the potential to improve the response time between defect detection and defect classification. Faster defect classification will allow for rapid response to yield anomalies that will ultimately reduce the wafer and/or the die yield.

Breast Cancer Diagnostics Based on Spatial Genome Organization

DTIC Science & Technology

2012-07-01

using an already established imaging tool, called NMFA-FLO (Nuclei Manual and FISH automatic). In order to achieve accurate segmentation of nuclei...in tissue we used an artificial neuronal network (ANN)-based supervised pattern recognition approach to screen out well segmented nuclei, after image ... segmentation used to process images for automated nuclear segmentation . Part a) has been adapted from [15] and b) from [16]. Figure 4. Comparison of

A new three-dimensional nonscanning laser imaging system based on the illumination pattern of a point-light-source array

NASA Astrophysics Data System (ADS)

Xia, Wenze; Ma, Yayun; Han, Shaokun; Wang, Yulin; Liu, Fei; Zhai, Yu

2018-06-01

One of the most important goals of research on three-dimensional nonscanning laser imaging systems is the improvement of the illumination system. In this paper, a new three-dimensional nonscanning laser imaging system based on the illumination pattern of a point-light-source array is proposed. This array is obtained using a fiber array connected to a laser array with each unit laser having independent control circuits. This system uses a point-to-point imaging process, which is realized using the exact corresponding optical relationship between the point-light-source array and a linear-mode avalanche photodiode array detector. The complete working process of this system is explained in detail, and the mathematical model of this system containing four equations is established. A simulated contrast experiment and two real contrast experiments which use the simplified setup without a laser array are performed. The final results demonstrate that unlike a conventional three-dimensional nonscanning laser imaging system, the proposed system meets all the requirements of an eligible illumination system. Finally, the imaging performance of this system is analyzed under defocusing situations, and analytical results show that the system has good defocusing robustness and can be easily adjusted in real applications.

Surface defect detection in tiling Industries using digital image processing methods: analysis and evaluation.

PubMed

Karimi, Mohammad H; Asemani, Davud

2014-05-01

Ceramic and tile industries should indispensably include a grading stage to quantify the quality of products. Actually, human control systems are often used for grading purposes. An automatic grading system is essential to enhance the quality control and marketing of the products. Since there generally exist six different types of defects originating from various stages of tile manufacturing lines with distinct textures and morphologies, many image processing techniques have been proposed for defect detection. In this paper, a survey has been made on the pattern recognition and image processing algorithms which have been used to detect surface defects. Each method appears to be limited for detecting some subgroup of defects. The detection techniques may be divided into three main groups: statistical pattern recognition, feature vector extraction and texture/image classification. The methods such as wavelet transform, filtering, morphology and contourlet transform are more effective for pre-processing tasks. Others including statistical methods, neural networks and model-based algorithms can be applied to extract the surface defects. Although, statistical methods are often appropriate for identification of large defects such as Spots, but techniques such as wavelet processing provide an acceptable response for detection of small defects such as Pinhole. A thorough survey is made in this paper on the existing algorithms in each subgroup. Also, the evaluation parameters are discussed including supervised and unsupervised parameters. Using various performance parameters, different defect detection algorithms are compared and evaluated. Copyright © 2013 ISA. Published by Elsevier Ltd. All rights reserved.

Tectonic geomorphology of the New Madrid seismic zone based on imaging of digital topographic data

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

Mayer, L.

1993-03-01

Topographic analysis using digital elevation data of the New Madrid region focuses on topographic features that occur at several spatial scales and can be used to delineate distinct anomalies. In this region, topographic anomalies occur as domal or elongate uplifts and bowl-shaped depressions approximately 1--10 km in size, topographic lineaments, and differences in topographic blocking across 50 km long boundaries. In order to fully explain these topographic anomalies, tectonic processes may be required. Imaging is based on digital topographic data from USGS 30 arc-second, 3 arc-second, and 30 m resolutions. Imaging of these data uses standard imaging processing techniques tomore » examine topography within the contexts of geomorphological hypothesis testing. A good example is the use of thresholding to highlight areas of unusually high elevation given the hypothesis of fluvial landscape architecture. Thresholding delineates topographic features such as the Tiptonville dome which is strongly believed to be tectonic in origin. To determine the pattern of topographic blocking, defined as a pattern that topography assumes when constrained by active forces other than erosion alone, low frequency passing spatial convolutions are used as filters and the resulting data are sliced into blocks according to pseudoelevations that produce a stable block pattern. The resultant blocks are analyzed according to its structural pattern of block size and block orientation. This analysis suggests that a topographic boundary cuts across the Mississippi embayment from near the Newport pluton on the west, to the area south of Memphis on east.« less

Demonstration of an N7 integrated fab process for metal oxide EUV photoresist

NASA Astrophysics Data System (ADS)

De Simone, Danilo; Mao, Ming; Kocsis, Michael; De Schepper, Peter; Lazzarino, Frederic; Vandenberghe, Geert; Stowers, Jason; Meyers, Stephen; Clark, Benjamin L.; Grenville, Andrew; Luong, Vinh; Yamashita, Fumiko; Parnell, Doni

2016-03-01

Inpria has developed a directly patternable metal oxide hard-mask as a robust, high-resolution photoresist for EUV lithography. In this paper we demonstrate the full integration of a baseline Inpria resist into an imec N7 BEOL block mask process module. We examine in detail both the lithography and etch patterning results. By leveraging the high differential etch resistance of metal oxide photoresists, we explore opportunities for process simplification and cost reduction. We review the imaging results from the imec N7 block mask patterns and its process windows as well as routes to maximize the process latitude, underlayer integration, etch transfer, cross sections, etch equipment integration from cross metal contamination standpoint and selective resist strip process. Finally, initial results from a higher sensitivity Inpria resist are also reported. A dose to size of 19 mJ/cm2 was achieved to print pillars as small as 21nm.

Optical head tracking for functional magnetic resonance imaging using structured light.

PubMed

Zaremba, Andrei A; MacFarlane, Duncan L; Tseng, Wei-Che; Stark, Andrew J; Briggs, Richard W; Gopinath, Kaundinya S; Cheshkov, Sergey; White, Keith D

2008-07-01

An accurate motion-tracking technique is needed to compensate for subject motion during functional magnetic resonance imaging (fMRI) procedures. Here, a novel approach to motion metrology is discussed. A structured light pattern specifically coded for digital signal processing is positioned onto a fiduciary of the patient. As the patient undergoes spatial transformations in 6 DoF (degrees of freedom), a high-resolution CCD camera captures successive images for analysis on a computing platform. A high-speed image processing algorithm is used to calculate spatial transformations in a time frame commensurate with patient movements (10-100 ms) and with a precision of at least 0.5 microm for translations and 0.1 deg for rotations.

Profiling and sorting Mangifera Indica morphology for quality attributes and grade standards using integrated image processing algorithms

NASA Astrophysics Data System (ADS)

Balbin, Jessie R.; Fausto, Janette C.; Janabajab, John Michael M.; Malicdem, Daryl James L.; Marcelo, Reginald N.; Santos, Jan Jeffrey Z.

2017-06-01

Mango production is highly vital in the Philippines. It is very essential in the food industry as it is being used in markets and restaurants daily. The quality of mangoes can affect the income of a mango farmer, thus incorrect time of harvesting will result to loss of quality mangoes and income. Scientific farming is much needed nowadays together with new gadgets because wastage of mangoes increase annually due to uncouth quality. This research paper focuses on profiling and sorting of Mangifera Indica using image processing techniques and pattern recognition. The image of a mango is captured on a weekly basis from its early stage. In this study, the researchers monitor the growth and color transition of a mango for profiling purposes. Actual dimensions of the mango are determined through image conversion and determination of pixel and RGB values covered through MATLAB. A program is developed to determine the range of the maximum size of a standard ripe mango. Hue, light, saturation (HSL) correction is used in the filtering process to assure the exactness of RGB values of a mango subject. By pattern recognition technique, the program can determine if a mango is standard and ready to be exported.

Design and implementation of non-linear image processing functions for CMOS image sensor

NASA Astrophysics Data System (ADS)

Musa, Purnawarman; Sudiro, Sunny A.; Wibowo, Eri P.; Harmanto, Suryadi; Paindavoine, Michel

2012-11-01

Today, solid state image sensors are used in many applications like in mobile phones, video surveillance systems, embedded medical imaging and industrial vision systems. These image sensors require the integration in the focal plane (or near the focal plane) of complex image processing algorithms. Such devices must meet the constraints related to the quality of acquired images, speed and performance of embedded processing, as well as low power consumption. To achieve these objectives, low-level analog processing allows extracting the useful information in the scene directly. For example, edge detection step followed by a local maxima extraction will facilitate the high-level processing like objects pattern recognition in a visual scene. Our goal was to design an intelligent image sensor prototype achieving high-speed image acquisition and non-linear image processing (like local minima and maxima calculations). For this purpose, we present in this article the design and test of a 64×64 pixels image sensor built in a standard CMOS Technology 0.35 μm including non-linear image processing. The architecture of our sensor, named nLiRIC (non-Linear Rapid Image Capture), is based on the implementation of an analog Minima/Maxima Unit. This MMU calculates the minimum and maximum values (non-linear functions), in real time, in a 2×2 pixels neighbourhood. Each MMU needs 52 transistors and the pitch of one pixel is 40×40 mu m. The total area of the 64×64 pixels is 12.5mm2. Our tests have shown the validity of the main functions of our new image sensor like fast image acquisition (10K frames per second), minima/maxima calculations in less then one ms.

Manufacturing of ArF chromeless hard shifter for 65-nm technology

NASA Astrophysics Data System (ADS)

Park, Keun-Taek; Dieu, Laurent; Hughes, Greg P.; Green, Kent G.; Croffie, Ebo H.; Taravade, Kunal N.

2003-12-01

For logic design, Chrome-less Phase Shift Mask is one of the possible solutions for defining small geometry with low MEF (mask enhancement factor) for the 65nm node. There have been lots of dedicated studies on the PCO (Phase Chrome Off-axis) mask technology and several design approaches have been proposed including grating background, chrome patches (or chrome shield) for applying PCO on line/space and contact pattern. In this paper, we studied the feasibility of grating design for line and contact pattern. The design of the grating pattern was provided from the EM simulation software (TEMPEST) and the aerial image simulation software. AIMS measurements with high NA annular illumination were done. Resist images were taken on designed pattern in different focus. Simulations, AIMS are compared to verify the consistency of the process with wafer printed performance.

Spatial super-resolution of colored images by micro mirrors

NASA Astrophysics Data System (ADS)

Dahan, Daniel; Yaacobi, Ami; Pinsky, Ephraim; Zalevsky, Zeev

2018-06-01

In this paper, we present two methods of dealing with the geometric resolution limit of color imaging sensors. It is possible to overcome the pixel size limit by adding a digital micro-mirror device component on the intermediate image plane of an optical system, and adapting its pattern in a computerized manner before sampling each frame. The full RGB image can be reconstructed from the Bayer camera by building a dedicated optical design, or by adjusting the demosaicing process to the special format of the enhanced image.

Optical information-processing systems and architectures II; Proceedings of the Meeting, San Diego, CA, July 9-13, 1990

NASA Astrophysics Data System (ADS)

Javidi, Bahram

The present conference discusses topics in the fields of neural networks, acoustooptic signal processing, pattern recognition, phase-only processing, nonlinear signal processing, image processing, optical computing, and optical information processing. Attention is given to the optical implementation of an inner-product neural associative memory, optoelectronic associative recall via motionless-head/parallel-readout optical disk, a compact real-time acoustooptic image correlator, a multidimensional synthetic estimation filter, and a light-efficient joint transform optical correlator. Also discussed are a high-resolution spatial light modulator, compact real-time interferometric Fourier-transform processors, a fast decorrelation algorithm for permutation arrays, the optical interconnection of optical modules, and carry-free optical binary adders.

Early stage hot spot analysis through standard cell base random pattern generation

NASA Astrophysics Data System (ADS)

Jeon, Joong-Won; Song, Jaewan; Kim, Jeong-Lim; Park, Seongyul; Yang, Seung-Hune; Lee, Sooryong; Kang, Hokyu; Madkour, Kareem; ElManhawy, Wael; Lee, SeungJo; Kwan, Joe

2017-04-01

Due to limited availability of DRC clean patterns during the process and RET recipe development, OPC recipes are not tested with high pattern coverage. Various kinds of pattern can help OPC engineer to detect sensitive patterns to lithographic effects. Random pattern generation is needed to secure robust OPC recipe. However, simple random patterns without considering real product layout style can't cover patterning hotspot in production levels. It is not effective to use them for OPC optimization thus it is important to generate random patterns similar to real product patterns. This paper presents a strategy for generating random patterns based on design architecture information and preventing hotspot in early process development stage through a tool called Layout Schema Generator (LSG). Using LSG, we generate standard cell based on random patterns reflecting real design cell structure - fin pitch, gate pitch and cell height. The output standard cells from LSG are applied to an analysis methodology to assess their hotspot severity by assigning a score according to their optical image parameters - NILS, MEEF, %PV band and thus potential hotspots can be defined by determining their ranking. This flow is demonstrated on Samsung 7nm technology optimizing OPC recipe and early enough in the process avoiding using problematic patterns.

Spatially Pooled Contrast Responses Predict Neural and Perceptual Similarity of Naturalistic Image Categories

PubMed Central

Groen, Iris I. A.; Ghebreab, Sennay; Lamme, Victor A. F.; Scholte, H. Steven

2012-01-01

The visual world is complex and continuously changing. Yet, our brain transforms patterns of light falling on our retina into a coherent percept within a few hundred milliseconds. Possibly, low-level neural responses already carry substantial information to facilitate rapid characterization of the visual input. Here, we computationally estimated low-level contrast responses to computer-generated naturalistic images, and tested whether spatial pooling of these responses could predict image similarity at the neural and behavioral level. Using EEG, we show that statistics derived from pooled responses explain a large amount of variance between single-image evoked potentials (ERPs) in individual subjects. Dissimilarity analysis on multi-electrode ERPs demonstrated that large differences between images in pooled response statistics are predictive of more dissimilar patterns of evoked activity, whereas images with little difference in statistics give rise to highly similar evoked activity patterns. In a separate behavioral experiment, images with large differences in statistics were judged as different categories, whereas images with little differences were confused. These findings suggest that statistics derived from low-level contrast responses can be extracted in early visual processing and can be relevant for rapid judgment of visual similarity. We compared our results with two other, well- known contrast statistics: Fourier power spectra and higher-order properties of contrast distributions (skewness and kurtosis). Interestingly, whereas these statistics allow for accurate image categorization, they do not predict ERP response patterns or behavioral categorization confusions. These converging computational, neural and behavioral results suggest that statistics of pooled contrast responses contain information that corresponds with perceived visual similarity in a rapid, low-level categorization task. PMID:23093921

Adaptive pattern for autonomous UAV guidance

NASA Astrophysics Data System (ADS)

Sung, Chen-Ko; Segor, Florian

2013-09-01

The research done at the Fraunhofer IOSB in Karlsruhe within the AMFIS project is focusing on a mobile system to support rescue forces in accidents or disasters. The system consists of a ground control station which has the capability to communicate with a large number of heterogeneous sensors and sensor carriers and provides several open interfaces to allow easy integration of additional sensors into the system. Within this research we focus mainly on UAV such as VTOL (Vertical takeoff and Landing) systems because of their ease of use and their high maneuverability. To increase the positioning capability of the UAV, different onboard processing chains of image exploitation for real time detection of patterns on the ground and the interfacing technology for controlling the UAV from the payload during flight were examined. The earlier proposed static ground pattern was extended by an adaptive component which admits an additional visual communication channel to the aircraft. For this purpose different components were conceived to transfer additive information using changeable patterns on the ground. The adaptive ground pattern and their application suitability had to be tested under external influence. Beside the adaptive ground pattern, the onboard process chains and the adaptations to the demands of changing patterns are introduced in this paper. The tracking of the guiding points, the UAV navigation and the conversion of the guiding point positions from the images to real world co-ordinates in video sequences, as well as use limits and the possibilities of an adaptable pattern are examined.

Simulation of speckle patterns with pre-defined correlation distributions.

PubMed

Song, Lipei; Zhou, Zhen; Wang, Xueyan; Zhao, Xing; Elson, Daniel S

2016-03-01

We put forward a method to easily generate a single or a sequence of fully developed speckle patterns with pre-defined correlation distribution by utilizing the principle of coherent imaging. The few-to-one mapping between the input correlation matrix and the correlation distribution between simulated speckle patterns is realized and there is a simple square relationship between the values of these two correlation coefficient sets. This method is demonstrated both theoretically and experimentally. The square relationship enables easy conversion from any desired correlation distribution. Since the input correlation distribution can be defined by a digital matrix or a gray-scale image acquired experimentally, this method provides a convenient way to simulate real speckle-related experiments and to evaluate data processing techniques.

The Newport Button: The Large Scale Replication Of Combined Three-And Two-Dimensional Holographic Images

NASA Astrophysics Data System (ADS)

Cowan, James J.

1984-05-01

A unique type of holographic imagery and its large scale replication are described. The "Newport Button", which was designed as an advertising premium item for the Newport Corporation, incorporates a complex overlay of holographic diffraction gratings surrounding a three-dimensional holographic image of a real object. The combined pattern is recorded onto a photosensitive medium from which a metal master is made. The master is subsequently used to repeatedly emboss the pattern into a thin plastic sheet. Individual patterns are then die cut from the metallized plastic and mounted onto buttons. A discussion is given of the diffraction efficiencies of holograms made in this particular fashion and of the special requirements of the replication process.

Simulation of speckle patterns with pre-defined correlation distributions

PubMed Central

Song, Lipei; Zhou, Zhen; Wang, Xueyan; Zhao, Xing; Elson, Daniel S.

2016-01-01

We put forward a method to easily generate a single or a sequence of fully developed speckle patterns with pre-defined correlation distribution by utilizing the principle of coherent imaging. The few-to-one mapping between the input correlation matrix and the correlation distribution between simulated speckle patterns is realized and there is a simple square relationship between the values of these two correlation coefficient sets. This method is demonstrated both theoretically and experimentally. The square relationship enables easy conversion from any desired correlation distribution. Since the input correlation distribution can be defined by a digital matrix or a gray-scale image acquired experimentally, this method provides a convenient way to simulate real speckle-related experiments and to evaluate data processing techniques. PMID:27231589

Iapetus: Unique Surface Properties and a Global Color Dichotomy from Cassini Imaging

NASA Astrophysics Data System (ADS)

Denk, Tilmann; Neukum, Gerhard; Roatsch, Thomas; Porco, Carolyn C.; Burns, Joseph A.; Galuba, Götz G.; Schmedemann, Nico; Helfenstein, Paul; Thomas, Peter C.; Wagner, Roland J.; West, Robert A.

2010-01-01

Since 2004, Saturn’s moon Iapetus has been observed repeatedly with the Imaging Science Subsystem of the Cassini spacecraft. The images show numerous impact craters down to the resolution limit of ~10 meters per pixel. Small, bright craters within the dark hemisphere indicate a dark blanket thickness on the order of meters or less. Dark, equator-facing and bright, poleward-facing crater walls suggest temperature-driven water-ice sublimation as the process responsible for local albedo patterns. Imaging data also reveal a global color dichotomy, wherein both dark and bright materials on the leading side have a substantially redder color than the respective trailing-side materials. This global pattern indicates an exogenic origin for the redder leading-side parts and suggests that the global color dichotomy initiated the thermal formation of the global albedo dichotomy.

Iapetus: unique surface properties and a global color dichotomy from Cassini imaging.

PubMed

Denk, Tilmann; Neukum, Gerhard; Roatsch, Thomas; Porco, Carolyn C; Burns, Joseph A; Galuba, Götz G; Schmedemann, Nico; Helfenstein, Paul; Thomas, Peter C; Wagner, Roland J; West, Robert A

2010-01-22

Since 2004, Saturn's moon Iapetus has been observed repeatedly with the Imaging Science Subsystem of the Cassini spacecraft. The images show numerous impact craters down to the resolution limit of approximately 10 meters per pixel. Small, bright craters within the dark hemisphere indicate a dark blanket thickness on the order of meters or less. Dark, equator-facing and bright, poleward-facing crater walls suggest temperature-driven water-ice sublimation as the process responsible for local albedo patterns. Imaging data also reveal a global color dichotomy, wherein both dark and bright materials on the leading side have a substantially redder color than the respective trailing-side materials. This global pattern indicates an exogenic origin for the redder leading-side parts and suggests that the global color dichotomy initiated the thermal formation of the global albedo dichotomy.

Modeling and possible implementation of self-learning equivalence-convolutional neural structures for auto-encoding-decoding and clusterization of images

NASA Astrophysics Data System (ADS)

Krasilenko, Vladimir G.; Lazarev, Alexander A.; Nikitovich, Diana V.

2017-08-01

Self-learning equivalent-convolutional neural structures (SLECNS) for auto-coding-decoding and image clustering are discussed. The SLECNS architectures and their spatially invariant equivalent models (SI EMs) using the corresponding matrix-matrix procedures with basic operations of continuous logic and non-linear processing are proposed. These SI EMs have several advantages, such as the ability to recognize image fragments with better efficiency and strong cross correlation. The proposed clustering method of fragments with regard to their structural features is suitable not only for binary, but also color images and combines self-learning and the formation of weight clustered matrix-patterns. Its model is constructed and designed on the basis of recursively processing algorithms and to k-average method. The experimental results confirmed that larger images and 2D binary fragments with a large numbers of elements may be clustered. For the first time the possibility of generalization of these models for space invariant case is shown. The experiment for an image with dimension of 256x256 (a reference array) and fragments with dimensions of 7x7 and 21x21 for clustering is carried out. The experiments, using the software environment Mathcad, showed that the proposed method is universal, has a significant convergence, the small number of iterations is easily, displayed on the matrix structure, and confirmed its prospects. Thus, to understand the mechanisms of self-learning equivalence-convolutional clustering, accompanying her to the competitive processes in neurons, and the neural auto-encoding-decoding and recognition principles with the use of self-learning cluster patterns is very important which used the algorithm and the principles of non-linear processing of two-dimensional spatial functions of images comparison. These SIEMs can simply describe the signals processing during the all training and recognition stages and they are suitable for unipolar-coding multilevel signals. We show that the implementation of SLECNS based on known equivalentors or traditional correlators is possible if they are based on proposed equivalental two-dimensional functions of image similarity. The clustering efficiency in such models and their implementation depends on the discriminant properties of neural elements of hidden layers. Therefore, the main models and architecture parameters and characteristics depends on the applied types of non-linear processing and function used for image comparison or for adaptive-equivalental weighing of input patterns. Real model experiments in Mathcad are demonstrated, which confirm that non-linear processing on equivalent functions allows you to determine the neuron winners and adjust the weight matrix. Experimental results have shown that such models can be successfully used for auto- and hetero-associative recognition. They can also be used to explain some mechanisms known as "focus" and "competing gain-inhibition concept". The SLECNS architecture and hardware implementations of its basic nodes based on multi-channel convolvers and correlators with time integration are proposed. The parameters and performance of such architectures are estimated.

Software phantom with realistic speckle modeling for validation of image analysis methods in echocardiography

NASA Astrophysics Data System (ADS)

Law, Yuen C.; Tenbrinck, Daniel; Jiang, Xiaoyi; Kuhlen, Torsten

2014-03-01

Computer-assisted processing and interpretation of medical ultrasound images is one of the most challenging tasks within image analysis. Physical phenomena in ultrasonographic images, e.g., the characteristic speckle noise and shadowing effects, make the majority of standard methods from image analysis non optimal. Furthermore, validation of adapted computer vision methods proves to be difficult due to missing ground truth information. There is no widely accepted software phantom in the community and existing software phantoms are not exible enough to support the use of specific speckle models for different tissue types, e.g., muscle and fat tissue. In this work we propose an anatomical software phantom with a realistic speckle pattern simulation to _ll this gap and provide a exible tool for validation purposes in medical ultrasound image analysis. We discuss the generation of speckle patterns and perform statistical analysis of the simulated textures to obtain quantitative measures of the realism and accuracy regarding the resulting textures.

Applications of satellite image processing to the analysis of Amazonian cultural ecology

NASA Technical Reports Server (NTRS)

Behrens, Clifford A.

1991-01-01

This paper examines the application of satellite image processing towards identifying and comparing resource exploitation among indigenous Amazonian peoples. The use of statistical and heuristic procedures for developing land cover/land use classifications from Thematic Mapper satellite imagery will be discussed along with actual results from studies of relatively small (100 - 200 people) settlements. Preliminary research indicates that analysis of satellite imagery holds great potential for measuring agricultural intensification, comparing rates of tropical deforestation, and detecting changes in resource utilization patterns over time.

An improved architecture for video rate image transformations

NASA Technical Reports Server (NTRS)

Fisher, Timothy E.; Juday, Richard D.

1989-01-01

Geometric image transformations are of interest to pattern recognition algorithms for their use in simplifying some aspects of the pattern recognition process. Examples include reducing sensitivity to rotation, scale, and perspective of the object being recognized. The NASA Programmable Remapper can perform a wide variety of geometric transforms at full video rate. An architecture is proposed that extends its abilities and alleviates many of the first version's shortcomings. The need for the improvements are discussed in the context of the initial Programmable Remapper and the benefits and limitations it has delivered. The implementation and capabilities of the proposed architecture are discussed.

Electronic recording of holograms with applications to holographic displays

NASA Technical Reports Server (NTRS)

Claspy, P. C.; Merat, F. L.

1979-01-01

The paper describes an electronic heterodyne recording which uses electrooptic modulation to introduce a sinusoidal phase shift between the object and reference wave. The resulting temporally modulated holographic interference pattern is scanned by a commercial image dissector camera, and the rejection of the self-interference terms is accomplished by heterodyne detection at the camera output. The electrical signal representing this processed hologram can then be used to modify the properties of a liquid crystal light valve or a similar device. Such display devices transform the displayed interference pattern into a phase modulated wave front rendering a three-dimensional image.

A new framework for an electrophotographic printer model

NASA Astrophysics Data System (ADS)

Colon-Lopez, Fermin A.

Digital halftoning is a printing technology that creates the illusion of continuous tone images for printing devices such as electrophotographic printers that can only produce a limited number of tone levels. Digital halftoning works because the human visual system has limited spatial resolution which blurs the printed dots of the halftone image, creating the gray sensation of a continuous tone image. Because the printing process is imperfect it introduces distortions to the halftone image. The quality of the printed image depends, among other factors, on the complex interactions between the halftone image, the printer characteristics, the colorant, and the printing substrate. Printer models are used to assist in the development of new types of halftone algorithms that are designed to withstand the effects of printer distortions. For example, model-based halftone algorithms optimize the halftone image through an iterative process that integrates a printer model within the algorithm. The two main goals of a printer model are to provide accurate estimates of the tone and of the spatial characteristics of the printed halftone pattern. Various classes of printer models, from simple tone calibrations to complex mechanistic models, have been reported in the literature. Existing models have one or more of the following limiting factors: they only predict tone reproduction, they depend on the halftone pattern, they require complex calibrations or complex calculations, they are printer specific, they reproduce unrealistic dot structures, and they are unable to adapt responses to new data. The two research objectives of this dissertation are (1) to introduce a new framework for printer modeling and (2) to demonstrate the feasibility of such a framework in building an electrophotographic printer model. The proposed framework introduces the concept of modeling a printer as a texture transformation machine. The basic premise is that modeling the texture differences between the output printed images and the input images encompasses all printing distortions. The feasibility of the framework was tested with a case study modeling a monotone electrophotographic printer. The printer model was implemented as a bank of feed-forward neural networks, each one specialized in modeling a group of textural features of the printed halftone pattern. The textural features were obtained using a parametric representation of texture developed from a multiresolution decomposition proposed by other researchers. The textural properties of halftone patterns were analyzed and the key texture parameters to be modeled by the bank were identified. Guidelines for the multiresolution texture decomposition and the model operational parameters and operational limits were established. A method for the selection of training sets based on the morphological properties of the halftone patterns was also developed. The model is fast and has the capability to continue to learn with additional training. The model can be easily implemented because it only requires a calibrated scanner. The model was tested with halftone patterns representing a range of spatial characteristics found in halftoning. Results show that the model provides accurate predictions for the tone and the spatial characteristics when modeling halftone patterns individually and it provides close approximations when modeling multiple halftone patterns simultaneously. The success of the model justifies continued research of this new printer model framework.

Advances in dual-tone development for pitch frequency doubling

NASA Astrophysics Data System (ADS)

Fonseca, Carlos; Somervell, Mark; Scheer, Steven; Kuwahara, Yuhei; Nafus, Kathleen; Gronheid, Roel; Tarutani, Shinji; Enomoto, Yuuichiro

2010-04-01

Dual-tone development (DTD) has been previously proposed as a potential cost-effective double patterning technique1. DTD was reported as early as in the late 1990's2. The basic principle of dual-tone imaging involves processing exposed resist latent images in both positive tone (aqueous base) and negative tone (organic solvent) developers. Conceptually, DTD has attractive cost benefits since it enables pitch doubling without the need for multiple etch steps of patterned resist layers. While the concept for DTD technique is simple to understand, there are many challenges that must be overcome and understood in order to make it a manufacturing solution. Previous work by the authors demonstrated feasibility of DTD imaging for 50nm half-pitch features at 0.80NA (k1 = 0.21) and discussed challenges lying ahead for printing sub-40nm half-pitch features with DTD. While previous experimental results suggested that clever processing on the wafer track can be used to enable DTD beyond 50nm halfpitch, it also suggest that identifying suitable resist materials or chemistries is essential for achieving successful imaging results with novel resist processing methods on the wafer track. In this work, we present recent advances in the search for resist materials that work in conjunction with novel resist processing methods on the wafer track to enable DTD. Recent experimental results with new resist chemistries, specifically designed for DTD, are presented in this work. We also present simulation studies that help and support identifying resist properties that could enable DTD imaging, which ultimately lead to producing viable DTD resist materials.

Novel wavelength diversity technique for high-speed atmospheric turbulence compensation

NASA Astrophysics Data System (ADS)

Arrasmith, William W.; Sullivan, Sean F.

2010-04-01

The defense, intelligence, and homeland security communities are driving a need for software dominant, real-time or near-real time atmospheric turbulence compensated imagery. The development of parallel processing capabilities are finding application in diverse areas including image processing, target tracking, pattern recognition, and image fusion to name a few. A novel approach to the computationally intensive case of software dominant optical and near infrared imaging through atmospheric turbulence is addressed in this paper. Previously, the somewhat conventional wavelength diversity method has been used to compensate for atmospheric turbulence with great success. We apply a new correlation based approach to the wavelength diversity methodology using a parallel processing architecture enabling high speed atmospheric turbulence compensation. Methods for optical imaging through distributed turbulence are discussed, simulation results are presented, and computational and performance assessments are provided.

Spatio-Temporal Changes of Lymphatic Contractility and Drainage Patterns following Lymphadenectomy in Mice

PubMed Central

Kwon, Sunkuk; Agollah, Germaine D.; Wu, Grace; Sevick-Muraca, Eva M.

2014-01-01

Objective To investigate the redirection of lymphatic drainage post-lymphadenectomy using non-invasive near-infrared fluorescence (NIRF) imaging, and to subsequently assess impact on metastasis. Background Cancer-acquired lymphedema arises from dysfunctional fluid transport after lymphadenectomy performed for staging and to disrupt drainage pathways for regional control of disease. However, little is known about the normal regenerative processes of the lymphatics in response to lymphadenectomy and how these responses can be accelerated, delayed, or can impact metastasis. Methods Changes in lymphatic “pumping” function and drainage patterns were non-invasively and longitudinally imaged using NIRF lymphatic imaging after popliteal lymphadenectomy in mice. In a cohort of mice, B16F10 melanoma was inoculated on the dorsal aspect of the paw 27 days after lymphadenectomy to assess how drainage patterns affect metastasis. Results NIRF imaging demonstrates that, although lymphatic function and drainage patterns change significantly in early response to popliteal lymph node (PLN) removal in mice, these changes are transient and regress dramatically due to a high regenerative capacity of the lymphatics and co-opting of collateral lymphatic pathways around the site of obstruction. Metastases followed the pattern of collateral pathways and could be detected proximal to the site of lymphadenectomy. Conclusions Both lymphatic vessel regeneration and co-opting of contralateral vessels occur following lymphadenectomy, with contractile function restored within 13 days, providing a basis for preclinical and clinical investigations to hasten lymphatic repair and restore contractile lymphatic function after surgery to prevent cancer-acquired lymphedema. Patterns of cancer metastasis after lymphadenectomy were altered, consistent with patterns of re-directed lymphatic drainage. PMID:25170770

JPRS Report, Science & Technology, Japan, 27th Aircraft Symposium

DTIC Science & Technology

1990-10-29

screen; the relative attitude is then determined . 2) Video Sensor System Specific patterns (grapple target, etc.) drawn on the target spacecraft , or the...entire target spacecraft , is imaged by camera . Navigation information is obtained by on-board image processing, such as extraction of contours and...standard figure called "grapple target" located in the vicinity of the grapple fixture on the target spacecraft is imaged by camera . Contour lines and

Optical sectioning in wide-field microscopy obtained by dynamic structured light illumination and detection based on a smart pixel detector array.

PubMed

Mitić, Jelena; Anhut, Tiemo; Meier, Matthias; Ducros, Mathieu; Serov, Alexander; Lasser, Theo

2003-05-01

Optical sectioning in wide-field microscopy is achieved by illumination of the object with a continuously moving single-spatial-frequency pattern and detecting the image with a smart pixel detector array. This detector performs an on-chip electronic signal processing that extracts the optically sectioned image. The optically sectioned image is directly observed in real time without any additional postprocessing.

Synthetic Aperture Imaging Polarimeter: Postprint

DTIC Science & Technology

2010-02-01

mechanical design of the SAlP prototype revol .... es around the concept of a modular array. The modular aspect allows for the array to be built in...imagery of source . The top row images are of the actual fringe pattern incident on the SAlP prototype array. These pictures were taken through the...processed images associated with each of the inputs. The results demonstrated that the SAlP prototype array works in conjunction with the algorithm

Human Expertise Helps Computer Classify Images

NASA Technical Reports Server (NTRS)

Rorvig, Mark E.

1991-01-01

Two-domain method of computational classification of images requires less computation than other methods for computational recognition, matching, or classification of images or patterns. Does not require explicit computational matching of features, and incorporates human expertise without requiring translation of mental processes of classification into language comprehensible to computer. Conceived to "train" computer to analyze photomicrographs of microscope-slide specimens of leucocytes from human peripheral blood to distinguish between specimens from healthy and specimens from traumatized patients.

Stereoscopic Machine-Vision System Using Projected Circles

NASA Technical Reports Server (NTRS)

Mackey, Jeffrey R.

2010-01-01

A machine-vision system capable of detecting obstacles large enough to damage or trap a robotic vehicle is undergoing development. The system includes (1) a pattern generator that projects concentric circles of laser light forward onto the terrain, (2) a stereoscopic pair of cameras that are aimed forward to acquire images of the circles, (3) a frame grabber and digitizer for acquiring image data from the cameras, and (4) a single-board computer that processes the data. The system is being developed as a prototype of machine- vision systems to enable robotic vehicles ( rovers ) on remote planets to avoid craters, large rocks, and other terrain features that could capture or damage the vehicles. Potential terrestrial applications of systems like this one could include terrain mapping, collision avoidance, navigation of robotic vehicles, mining, and robotic rescue. This system is based partly on the same principles as those of a prior stereoscopic machine-vision system in which the cameras acquire images of a single stripe of laser light that is swept forward across the terrain. However, this system is designed to afford improvements over some of the undesirable features of the prior system, including the need for a pan-and-tilt mechanism to aim the laser to generate the swept stripe, ambiguities in interpretation of the single-stripe image, the time needed to sweep the stripe across the terrain and process the data from many images acquired during that time, and difficulty of calibration because of the narrowness of the stripe. In this system, the pattern generator does not contain any moving parts and need not be mounted on a pan-and-tilt mechanism: the pattern of concentric circles is projected steadily in the forward direction. The system calibrates itself by use of data acquired during projection of the concentric-circle pattern onto a known target representing flat ground. The calibration- target image data are stored in the computer memory for use as a template in processing terrain images. During operation on terrain, the images acquired by the left and right cameras are analyzed. The analysis includes (1) computation of the horizontal and vertical dimensions and the aspect ratios of rectangles that bound the circle images and (2) comparison of these aspect ratios with those of the template. Coordinates of distortions of the circles are used to identify and locate objects. If the analysis leads to identification of an object of significant size, then stereoscopicvision algorithms are used to estimate the distance to the object. The time taken in performing this analysis on a single pair of images acquired by the left and right cameras in this system is a fraction of the time taken in processing the many pairs of images acquired in a sweep of the laser stripe across the field of view in the prior system. The results of the analysis include data on sizes and shapes of, and distances and directions to, objects. Coordinates of objects are updated as the vehicle moves so that intelligent decisions regarding speed and direction can be made. The results of the analysis are utilized in a computational decision-making process that generates obstacle-avoidance data and feeds those data to the control system of the robotic vehicle.

On the role of spatial phase and phase correlation in vision, illusion, and cognition

PubMed Central

Gladilin, Evgeny; Eils, Roland

2015-01-01

Numerous findings indicate that spatial phase bears an important cognitive information. Distortion of phase affects topology of edge structures and makes images unrecognizable. In turn, appropriately phase-structured patterns give rise to various illusions of virtual image content and apparent motion. Despite a large body of phenomenological evidence not much is known yet about the role of phase information in neural mechanisms of visual perception and cognition. Here, we are concerned with analysis of the role of spatial phase in computational and biological vision, emergence of visual illusions and pattern recognition. We hypothesize that fundamental importance of phase information for invariant retrieval of structural image features and motion detection promoted development of phase-based mechanisms of neural image processing in course of evolution of biological vision. Using an extension of Fourier phase correlation technique, we show that the core functions of visual system such as motion detection and pattern recognition can be facilitated by the same basic mechanism. Our analysis suggests that emergence of visual illusions can be attributed to presence of coherently phase-shifted repetitive patterns as well as the effects of acuity compensation by saccadic eye movements. We speculate that biological vision relies on perceptual mechanisms effectively similar to phase correlation, and predict neural features of visual pattern (dis)similarity that can be used for experimental validation of our hypothesis of “cognition by phase correlation.” PMID:25954190

On the role of spatial phase and phase correlation in vision, illusion, and cognition.

PubMed

Gladilin, Evgeny; Eils, Roland

2015-01-01

Numerous findings indicate that spatial phase bears an important cognitive information. Distortion of phase affects topology of edge structures and makes images unrecognizable. In turn, appropriately phase-structured patterns give rise to various illusions of virtual image content and apparent motion. Despite a large body of phenomenological evidence not much is known yet about the role of phase information in neural mechanisms of visual perception and cognition. Here, we are concerned with analysis of the role of spatial phase in computational and biological vision, emergence of visual illusions and pattern recognition. We hypothesize that fundamental importance of phase information for invariant retrieval of structural image features and motion detection promoted development of phase-based mechanisms of neural image processing in course of evolution of biological vision. Using an extension of Fourier phase correlation technique, we show that the core functions of visual system such as motion detection and pattern recognition can be facilitated by the same basic mechanism. Our analysis suggests that emergence of visual illusions can be attributed to presence of coherently phase-shifted repetitive patterns as well as the effects of acuity compensation by saccadic eye movements. We speculate that biological vision relies on perceptual mechanisms effectively similar to phase correlation, and predict neural features of visual pattern (dis)similarity that can be used for experimental validation of our hypothesis of "cognition by phase correlation."

Method of fabricating a 3-dimensional tool master

DOEpatents

Bonivert, William D.; Hachman, John T.

2002-01-01

The invention is a method for the fabrication of an imprint tool master. The process begins with a metallic substrate. A layer of photoresist is placed onto the metallic substrate and a image pattern mask is then aligned to the mask. The mask pattern has opaque portions that block exposure light and "open" or transparent portions which transmit exposure light. The photoresist layer is then exposed to light transmitted through the "open" portions of the first image pattern mask and the mask is then removed. A second layer of photoresist then can be placed onto the first photoresist layer and a second image pattern mask may be placed on the second layer of photoresist. The second layer of photoresist is exposed to light, as before, and the second mask removed. The photoresist layers are developed simultaneously to produce a multi-level master mandrel upon which a conductive film is formed. A tool master can now be formed onto the conductive film. An imprint tool is then produced from the tool master. In one embodiment, nickel is electroplated onto the tool master to produce a three-dimensional imprint tool.

Nonparametric Hierarchical Bayesian Model for Functional Brain Parcellation

PubMed Central

Lashkari, Danial; Sridharan, Ramesh; Vul, Edward; Hsieh, Po-Jang; Kanwisher, Nancy; Golland, Polina

2011-01-01

We develop a method for unsupervised analysis of functional brain images that learns group-level patterns of functional response. Our algorithm is based on a generative model that comprises two main layers. At the lower level, we express the functional brain response to each stimulus as a binary activation variable. At the next level, we define a prior over the sets of activation variables in all subjects. We use a Hierarchical Dirichlet Process as the prior in order to simultaneously learn the patterns of response that are shared across the group, and to estimate the number of these patterns supported by data. Inference based on this model enables automatic discovery and characterization of salient and consistent patterns in functional signals. We apply our method to data from a study that explores the response of the visual cortex to a collection of images. The discovered profiles of activation correspond to selectivity to a number of image categories such as faces, bodies, and scenes. More generally, our results appear superior to the results of alternative data-driven methods in capturing the category structure in the space of stimuli. PMID:21841977

Real-time image processing for non-contact monitoring of dynamic displacements using smartphone technologies

NASA Astrophysics Data System (ADS)

Min, Jae-Hong; Gelo, Nikolas J.; Jo, Hongki

2016-04-01

The newly developed smartphone application, named RINO, in this study allows measuring absolute dynamic displacements and processing them in real time using state-of-the-art smartphone technologies, such as high-performance graphics processing unit (GPU), in addition to already powerful CPU and memories, embedded high-speed/ resolution camera, and open-source computer vision libraries. A carefully designed color-patterned target and user-adjustable crop filter enable accurate and fast image processing, allowing up to 240fps for complete displacement calculation and real-time display. The performances of the developed smartphone application are experimentally validated, showing comparable accuracy with those of conventional laser displacement sensor.

Reconstruction dynamics of recorded holograms in photochromic glass.

PubMed

Mihailescu, Mona; Pavel, Eugen; Nicolae, Vasile B

2011-06-20

We have investigated the dynamics of the record-erase process of holograms in photochromic glass using continuum Nd:YVO₄ laser radiation (λ=532 nm). A bidimensional microgrid pattern was formed and visualized in photochromic glass, and its diffraction efficiency decay versus time (during reconstruction step) gave us information (D, Δn) about the diffusion process inside the material. The recording and reconstruction processes were carried out in an off-axis setup, and the images of the reconstructed object were recorded by a CCD camera. Measurements realized on reconstructed object images using holograms recorded at a different incident power laser have shown a two-stage process involved in silver atom kinetics.

Spatial and temporal selectivity patterns of fires in Attika, Greece from 1984 to 2015 delineated from Landsat time series satellite images

NASA Astrophysics Data System (ADS)

Stamos, Zoi; Koutsias, Nikos

2017-04-01

The aim of this study is to assess spatial and temporalfire selectivity patterns in the region of Attica - Greece from 1984 to 2015. Our work is implemented in two distinct phases: the first consists of the accurate delineation of the fire perimeter using satellite remote sensing technology, and the second consists of the application of suitable GIS supported analyses to develop thematic layers that optimally summarised the spatial and temporal information of fire occurrence. Fire perimeters of wildland fires occurred within the time window 1984-2015 were delineated from freely available Landsat images from USGS and ESA sources.More than three thousands satellite images were processed in order to extract fire perimeters and create maps of fire frequency and fire return interval. In total one thousand and one hundred twenty fire perimeters were recorded during this thirty years' period. Fire perimeters within each year of fire occurrence were compared against the available to burn under complete random processes to identify selectivity patterns over (i) CORINE land use/land cover, (ii) fire frequency and (iii) time since last firemaps. For example, non- irrigated arable lands, complex cultivation patterns and discontinuous urban fabrics are negative related with fires, while coniferous forests, sclerophyllous vegetation and transitional woodlands seem to be preferable by the fires. Additionally, it seems that fires prefer their old burnings (two and three times burned) and also places with different patterns of time since last fire depending on the time needed by the type of vegetation to recover and thus to re-burn.

Integration of mask and silicon metrology in DFM

NASA Astrophysics Data System (ADS)

Matsuoka, Ryoichi; Mito, Hiroaki; Sugiyama, Akiyuki; Toyoda, Yasutaka

2009-03-01

We have developed a highly integrated method of mask and silicon metrology. The method adopts a metrology management system based on DBM (Design Based Metrology). This is the high accurate contouring created by an edge detection algorithm used in mask CD-SEM and silicon CD-SEM. We have inspected the high accuracy, stability and reproducibility in the experiments of integration. The accuracy is comparable with that of the mask and silicon CD-SEM metrology. In this report, we introduce the experimental results and the application. As shrinkage of design rule for semiconductor device advances, OPC (Optical Proximity Correction) goes aggressively dense in RET (Resolution Enhancement Technology). However, from the view point of DFM (Design for Manufacturability), the cost of data process for advanced MDP (Mask Data Preparation) and mask producing is a problem. Such trade-off between RET and mask producing is a big issue in semiconductor market especially in mask business. Seeing silicon device production process, information sharing is not completely organized between design section and production section. Design data created with OPC and MDP should be linked to process control on production. But design data and process control data are optimized independently. Thus, we provided a solution of DFM: advanced integration of mask metrology and silicon metrology. The system we propose here is composed of followings. 1) Design based recipe creation: Specify patterns on the design data for metrology. This step is fully automated since they are interfaced with hot spot coordinate information detected by various verification methods. 2) Design based image acquisition: Acquire the images of mask and silicon automatically by a recipe based on the pattern design of CD-SEM.It is a robust automated step because a wide range of design data is used for the image acquisition. 3) Contour profiling and GDS data generation: An image profiling process is applied to the acquired image based on the profiling method of the field proven CD metrology algorithm. The detected edges are then converted to GDSII format, which is a standard format for a design data, and utilized for various DFM systems such as simulation. Namely, by integrating pattern shapes of mask and silicon formed during a manufacturing process into GDSII format, it makes it possible to bridge highly accurate pattern profile information over to the design field of various EDA systems. These are fully integrated into design data and automated. Bi-directional cross probing between mask data and process control data is allowed by linking them. This method is a solution for total optimization that covers Design, MDP, mask production and silicon device producing. This method therefore is regarded as a strategic DFM approach in the semiconductor metrology.

Real-time optical fiber digital speckle pattern interferometry for industrial applications

NASA Astrophysics Data System (ADS)

Chan, Robert K.; Cheung, Y. M.; Lo, C. H.; Tam, T. K.

1997-03-01

There is current interest, especially in the industrial sector, to use the digital speckle pattern interferometry (DSPI) technique to measure surface stress. Indeed, many publications in the subject are evident of the growing interests in the field. However, to bring the technology to industrial use requires the integration of several emerging technologies, viz. optics, feedback control, electronics, imaging processing and digital signal processing. Due to the highly interdisciplinary nature of the technique, successful implementation and development require expertise in all of the fields. At Baptist University, under the funding of a major industrial grant, we are developing the technology for the industrial sector. Our system fully exploits optical fibers and diode lasers in the design to enable practical and rugged systems suited for industrial applications. Besides the development in optics, we have broken away from the reliance of a microcomputer PC platform for both image capture and processing, and have developed a digital signal processing array system that can handle simultaneous and independent image capture/processing with feedback control. The system, named CASPA for 'cascadable architecture signal processing array,' is a third generation development system that utilizes up to 7 digital signal processors has proved to be a very powerful system. With our CASPA we are now in a better position to developing novel optical measurement systems for industrial application that may require different measurement systems to operate concurrently and requiring information exchange between the systems. Applications in mind such as simultaneous in-plane and out-of-plane DSPI image capture/process, vibrational analysis with interactive DSPI and phase shifting control of optical systems are a few good examples of the potentials.

Brain-based Learning.

ERIC Educational Resources Information Center

Weiss, Ruth Palombo

2000-01-01

Discusses brain research and how new imaging technologies allow scientists to explore how human brains process memory, emotion, attention, patterning, motivation, and context. Explains how brain research is being used to revise learning theories. (JOW)

Automated aerial image based CD metrology initiated by pattern marking with photomask layout data

NASA Astrophysics Data System (ADS)

Davis, Grant; Choi, Sun Young; Jung, Eui Hee; Seyfarth, Arne; van Doornmalen, Hans; Poortinga, Eric

2007-05-01

The photomask is a critical element in the lithographic image transfer process from the drawn layout to the final structures on the wafer. The non-linearity of the imaging process and the related MEEF impose a tight control requirement on the photomask critical dimensions. Critical dimensions can be measured in aerial images with hardware emulation. This is a more recent complement to the standard scanning electron microscope measurement of wafers and photomasks. Aerial image measurement includes non-linear, 3-dimensional, and materials effects on imaging that cannot be observed directly by SEM measurement of the mask. Aerial image measurement excludes the processing effects of printing and etching on the wafer. This presents a unique contribution to the difficult process control and modeling tasks in mask making. In the past, aerial image measurements have been used mainly to characterize the printability of mask repair sites. Development of photomask CD characterization with the AIMS TM tool was motivated by the benefit of MEEF sensitivity and the shorter feedback loop compared to wafer exposures. This paper describes a new application that includes: an improved interface for the selection of meaningful locations using the photomask and design layout data with the Calibre TM Metrology Interface, an automated recipe generation process, an automated measurement process, and automated analysis and result reporting on a Carl Zeiss AIMS TM system.

Symposium on Machine Processing of Remotely Sensed Data, Purdue University, West Lafayette, Ind., June 29-July 1, 1976, Proceedings

NASA Technical Reports Server (NTRS)

1976-01-01

Papers are presented on the applicability of Landsat data to water management and control needs, IBIS, a geographic information system based on digital image processing and image raster datatype, and the Image Data Access Method (IDAM) for the Earth Resources Interactive Processing System. Attention is also given to the Prototype Classification and Mensuration System (PROCAMS) applied to agricultural data, the use of Landsat for water quality monitoring in North Carolina, and the analysis of geophysical remote sensing data using multivariate pattern recognition. The Illinois crop-acreage estimation experiment, the Pacific Northwest Resources Inventory Demonstration, and the effects of spatial misregistration on multispectral recognition are also considered. Individual items are announced in this issue.

Applied photo interpretation for airbrush cartography

NASA Technical Reports Server (NTRS)

Inge, J. L.; Bridges, P. M.

1976-01-01

New techniques of cartographic portrayal have been developed for the compilation of maps of lunar and planetary surfaces. Conventional photo interpretation methods utilizing size, shape, shadow, tone, pattern, and texture are applied to computer processed satellite television images. The variety of the image data allows the illustrator to interpret image details by inter-comparison and intra-comparison of photographs. Comparative judgements are affected by illumination, resolution, variations in surface coloration, and transmission or processing artifacts. The validity of the interpretation process is tested by making a representational drawing by an airbrush portrayal technique. Production controls insure the consistency of a map series. Photo interpretive cartographic portrayal skills are used to prepare two kinds of map series and are adaptable to map products of different kinds and purposes.

Multistability of the Brain Network for Self-other Processing

PubMed Central

Chen, Yi-An; Huang, Tsung-Ren

2017-01-01

Early fMRI studies suggested that brain areas processing self-related and other-related information were highly overlapping. Hypothesising functional localisation of the cortex, researchers have tried to locate “self-specific” and “other-specific” regions within these overlapping areas by subtracting suspected confounding signals in task-based fMRI experiments. Inspired by recent advances in whole-brain dynamic modelling, we instead explored an alternative hypothesis that similar spatial activation patterns could be associated with different processing modes in the form of different synchronisation patterns. Combining an automated synthesis of fMRI data with a presumption-free diffusion spectrum image (DSI) fibre-tracking algorithm, we isolated a network putatively composed of brain areas and white matter tracts involved in self-other processing. We sampled synchronisation patterns from the dynamical systems of this network using various combinations of physiological parameters. Our results showed that the self-other processing network, with simulated gamma-band activity, tended to stabilise at a number of distinct synchronisation patterns. This phenomenon, termed “multistability,” could serve as an alternative model in theorising the mechanism of processing self-other information. PMID:28256520

Suppression of fixed pattern noise for infrared image system

NASA Astrophysics Data System (ADS)

Park, Changhan; Han, Jungsoo; Bae, Kyung-Hoon

2008-04-01

In this paper, we propose suppression of fixed pattern noise (FPN) and compensation of soft defect for improvement of object tracking in cooled staring infrared focal plane array (IRFPA) imaging system. FPN appears an observable image which applies to non-uniformity compensation (NUC) by temperature. Soft defect appears glittering black and white point by characteristics of non-uniformity for IR detector by time. This problem is very important because it happen serious problem for object tracking as well as degradation for image quality. Signal processing architecture in cooled staring IRFPA imaging system consists of three tables: low, normal, high temperature for reference gain and offset values. Proposed method operates two offset tables for each table. This is method which operates six term of temperature on the whole. Proposed method of soft defect compensation consists of three stages: (1) separates sub-image for an image, (2) decides a motion distribution of object between each sub-image, (3) analyzes for statistical characteristic from each stationary fixed pixel. Based on experimental results, the proposed method shows an improved image which suppresses FPN by change of temperature distribution from an observational image in real-time.

Evaluation of Alternative Conceptual Models Using Interdisciplinary Information: An Application in Shallow Groundwater Recharge and Discharge

NASA Astrophysics Data System (ADS)

Lin, Y.; Bajcsy, P.; Valocchi, A. J.; Kim, C.; Wang, J.

2007-12-01

Natural systems are complex, thus extensive data are needed for their characterization. However, data acquisition is expensive; consequently we develop models using sparse, uncertain information. When all uncertainties in the system are considered, the number of alternative conceptual models is large. Traditionally, the development of a conceptual model has relied on subjective professional judgment. Good judgment is based on experience in coordinating and understanding auxiliary information which is correlated to the model but difficult to be quantified into the mathematical model. For example, groundwater recharge and discharge (R&D) processes are known to relate to multiple information sources such as soil type, river and lake location, irrigation patterns and land use. Although hydrologists have been trying to understand and model the interaction between each of these information sources and R&D processes, it is extremely difficult to quantify their correlations using a universal approach due to the complexity of the processes, the spatiotemporal distribution and uncertainty. There is currently no single method capable of estimating R&D rates and patterns for all practical applications. Chamberlin (1890) recommended use of "multiple working hypotheses" (alternative conceptual models) for rapid advancement in understanding of applied and theoretical problems. Therefore, cross analyzing R&D rates and patterns from various estimation methods and related field information will likely be superior to using only a single estimation method. We have developed the Pattern Recognition Utility (PRU), to help GIS users recognize spatial patterns from noisy 2D image. This GIS plug-in utility has been applied to help hydrogeologists establish alternative R&D conceptual models in a more efficient way than conventional methods. The PRU uses numerical methods and image processing algorithms to estimate and visualize shallow R&D patterns and rates. It can provide a fast initial estimate prior to planning labor intensive and time consuming field R&D measurements. Furthermore, the Spatial Pattern 2 Learn (SP2L) was developed to cross analyze results from the PRU with ancillary field information, such as land coverage, soil type, topographic maps and previous estimates. The learning process of SP2L cross examines each initially recognized R&D pattern with the ancillary spatial dataset, and then calculates a quantifiable reliability index for each R&D map using a supervised machine learning technique called decision tree. This JAVA based software package is capable of generating alternative R&D maps if the user decides to apply certain conditions recognized by the learning process. The reliability indices from SP2L will improve the traditionally subjective approach to initiating conceptual models by providing objectively quantifiable conceptual bases for further probabilistic and uncertainty analyses. Both the PRU and SP2L have been designed to be user-friendly and universal utilities for pattern recognition and learning to improve model predictions from sparse measurements by computer-assisted integration of spatially dense geospatial image data and machine learning of model dependencies.

Rotation covariant image processing for biomedical applications.

PubMed

Skibbe, Henrik; Reisert, Marco

2013-01-01

With the advent of novel biomedical 3D image acquisition techniques, the efficient and reliable analysis of volumetric images has become more and more important. The amount of data is enormous and demands an automated processing. The applications are manifold, ranging from image enhancement, image reconstruction, and image description to object/feature detection and high-level contextual feature extraction. In most scenarios, it is expected that geometric transformations alter the output in a mathematically well-defined manner. In this paper we emphasis on 3D translations and rotations. Many algorithms rely on intensity or low-order tensorial-like descriptions to fulfill this demand. This paper proposes a general mathematical framework based on mathematical concepts and theories transferred from mathematical physics and harmonic analysis into the domain of image analysis and pattern recognition. Based on two basic operations, spherical tensor differentiation and spherical tensor multiplication, we show how to design a variety of 3D image processing methods in an efficient way. The framework has already been applied to several biomedical applications ranging from feature and object detection tasks to image enhancement and image restoration techniques. In this paper, the proposed methods are applied on a variety of different 3D data modalities stemming from medical and biological sciences.

Nuclear Magnetic Resonance Relaxation and Imaging Studies on Water Flow in Soil Cores

NASA Astrophysics Data System (ADS)

Pohlmeier, Andreas; Haber-Pohlmeier, Sabina; Stapf, Siegfried

2010-05-01

Magnetic resonance imaging (MRI) is applied to the study of flow processes in a model and a natural soils core. Since flow velocities in soils are mostly too slow to be monitored directly by MRI flow velocity imaging, Gd-DTPA was used as contrast agent for the first time for flow processes in soils. Apart from its chemical stability the main advantage is the anionic net charge in neutral aqueous solution. Here we can show that this property hinders the adsorption at soil mineral surfaces and therefore retardation. Gd-DTPA turns out to be a very convenient conservative tracer for the investigation of flow processes in model and natural soil cores. With respect to the flow processes in the coaxial model soil column and the natural soil column we found total different flow patterns: In the first case tracer plume moves quite homogeneously only in the inner highly conductive core. No penetration into the outer fine material takes place. In contrast, the natural soil core shows a flow pattern which is characterized by preferential paths avoiding dense regions and preferring loose structures. In the case of the simpler model column also the local flow velocities are calculated by the application of a peak tracking algorithm.

Chemometrics.

ERIC Educational Resources Information Center

Delaney, Michael F.

1984-01-01

This literature review on chemometrics (covering December 1981 to December 1983) is organized under these headings: personal supermicrocomputers; education and books; statistics; modeling and parameter estimation; resolution; calibration; signal processing; image analysis; factor analysis; pattern recognition; optimization; artificial…

The software peculiarities of pattern recognition in track detectors

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

Starkov, N.

The different kinds of nuclear track recognition algorithms are represented. Several complicated samples of use them in physical experiments are considered. The some processing methods of complicated images are described.

Fourier power spectrum characteristics of face photographs: attractiveness perception depends on low-level image properties.

PubMed

Menzel, Claudia; Hayn-Leichsenring, Gregor U; Langner, Oliver; Wiese, Holger; Redies, Christoph

2015-01-01

We investigated whether low-level processed image properties that are shared by natural scenes and artworks - but not veridical face photographs - affect the perception of facial attractiveness and age. Specifically, we considered the slope of the radially averaged Fourier power spectrum in a log-log plot. This slope is a measure of the distribution of special frequency power in an image. Images of natural scenes and artworks possess - compared to face images - a relatively shallow slope (i.e., increased high spatial frequency power). Since aesthetic perception might be based on the efficient processing of images with natural scene statistics, we assumed that the perception of facial attractiveness might also be affected by these properties. We calculated Fourier slope and other beauty-associated measurements in face images and correlated them with ratings of attractiveness and age of the depicted persons (Study 1). We found that Fourier slope - in contrast to the other tested image properties - did not predict attractiveness ratings when we controlled for age. In Study 2A, we overlaid face images with random-phase patterns with different statistics. Patterns with a slope similar to those in natural scenes and artworks resulted in lower attractiveness and higher age ratings. In Studies 2B and 2C, we directly manipulated the Fourier slope of face images and found that images with shallower slopes were rated as more attractive. Additionally, attractiveness of unaltered faces was affected by the Fourier slope of a random-phase background (Study 3). Faces in front of backgrounds with statistics similar to natural scenes and faces were rated as more attractive. We conclude that facial attractiveness ratings are affected by specific image properties. An explanation might be the efficient coding hypothesis.

Fourier Power Spectrum Characteristics of Face Photographs: Attractiveness Perception Depends on Low-Level Image Properties

PubMed Central

Langner, Oliver; Wiese, Holger; Redies, Christoph

2015-01-01

We investigated whether low-level processed image properties that are shared by natural scenes and artworks – but not veridical face photographs – affect the perception of facial attractiveness and age. Specifically, we considered the slope of the radially averaged Fourier power spectrum in a log-log plot. This slope is a measure of the distribution of special frequency power in an image. Images of natural scenes and artworks possess – compared to face images – a relatively shallow slope (i.e., increased high spatial frequency power). Since aesthetic perception might be based on the efficient processing of images with natural scene statistics, we assumed that the perception of facial attractiveness might also be affected by these properties. We calculated Fourier slope and other beauty-associated measurements in face images and correlated them with ratings of attractiveness and age of the depicted persons (Study 1). We found that Fourier slope – in contrast to the other tested image properties – did not predict attractiveness ratings when we controlled for age. In Study 2A, we overlaid face images with random-phase patterns with different statistics. Patterns with a slope similar to those in natural scenes and artworks resulted in lower attractiveness and higher age ratings. In Studies 2B and 2C, we directly manipulated the Fourier slope of face images and found that images with shallower slopes were rated as more attractive. Additionally, attractiveness of unaltered faces was affected by the Fourier slope of a random-phase background (Study 3). Faces in front of backgrounds with statistics similar to natural scenes and faces were rated as more attractive. We conclude that facial attractiveness ratings are affected by specific image properties. An explanation might be the efficient coding hypothesis. PMID:25835539

Technical Note: Detection of gas bubble leakage via correlation of water column multibeam images

NASA Astrophysics Data System (ADS)

Schneider von Deimling, J.; Papenberg, C.

2012-03-01

Hydroacoustic detection of natural gas release from the seafloor has been conducted in the past by using singlebeam echosounders. In contrast, modern multibeam swath mapping systems allow much wider coverage, higher resolution, and offer 3-D spatial correlation. Up to the present, the extremely high data rate hampers water column backscatter investigations and more sophisticated visualization and processing techniques are needed. Here, we present water column backscatter data acquired with a 50 kHz prototype multibeam system over a period of 75 seconds. Display types are of swath-images as well as of a "re-sorted" singlebeam presentation. Thus, individual and/or groups of gas bubbles rising from the 24 m deep seafloor clearly emerge in the acoustic images, making it possible to estimate rise velocities. A sophisticated processing scheme is introduced to identify those rising gas bubbles in the hydroacoustic data. We apply a cross-correlation technique adapted from particle imaging velocimetry (PIV) to the acoustic backscatter images. Temporal and spatial drift patterns of the bubbles are assessed and are shown to match very well to measured and theoretical rise patterns. The application of this processing to our field data gives clear results with respect to unambiguous bubble detection and remote bubble rise velocimetry. The method can identify and exclude the main source of misinterpretations, i.e. fish-mediated echoes. Although image-based cross-correlation techniques are well known in the field of fluid mechanics for high resolution and non-inversive current flow field analysis, we present the first application of this technique as an acoustic bubble detector.

[Computer-assisted measurement of ocular misalignment in infants and young children using the digital Purkinje reflection pattern procedure].

PubMed

Barry, J C; Effert, R; Kaupp, A; Kleine, M; Reim, M

1994-02-01

A digital image recording and processing system is presented that allows a quick diagnosis of microstrabismus in non-cooperative children. It is thus particularly suited for screening purposes. The Purkinje Reflection Pattern Evaluation (RPE) method is used: three small flashes are used to produce the desired Purkinje images. Two horizontal rows of the three 1st Purkinje images (anterior corneal reflections) and of the three 4th Purkinje images (posterior crystalline lens reflections) stemming from the three light sources form the characteristic Purkinje image reflection pattern. Each eye's position is calculated from the shift between the upper and lower rows of reflections by means of two simple formulae. From the angles obtained in binocular fixation and monocular fixation the manifest angle of strabismus corresponding to the angle measured in the simultaneous prism-and-cover test is computed. The measurement is performed at a fixation distance of 50 cm under natural viewing conditions. To obtain a picture one only has to get the child's attention for a short moment. The primary position is triggered with the fixation light, which is operated by a switch. The digital image recording is done with a hand-held device comprising two miniaturized video cameras, three photo flashes and a fixation light that is operated manually. An IBM-compatible PC equipped with a hard disk and two frame grabbers was adapted for the storage and processing of the pictures. The pictures are evaluated interactively in a few minutes on the workstation's monitor immediately after the measurement. To this end specially designed menu-driven software was implemented. Examples of the measuring procedure and clinical results in infants with microtropic highlight the potential of the system as a screening apparatus and for the exact measurement of small and large squint angles. Usually even 1-year-old children can cooperate well enough to get good-quality pictures in binocular fixation. The new digital system allows easy and rapid application of the Purkinje Reflection Pattern Evaluation method since the time-consuming photographic film processing and evaluation are no longer necessary. For the first time small angles of strabismus under 5 degrees (10 PD) can be measured with a precision of less than 1 degree (2 PD) under clinical conditions in non-cooperative children.

Superior pattern processing is the essence of the evolved human brain

PubMed Central

Mattson, Mark P.

2014-01-01

Humans have long pondered the nature of their mind/brain and, particularly why its capacities for reasoning, communication and abstract thought are far superior to other species, including closely related anthropoids. This article considers superior pattern processing (SPP) as the fundamental basis of most, if not all, unique features of the human brain including intelligence, language, imagination, invention, and the belief in imaginary entities such as ghosts and gods. SPP involves the electrochemical, neuronal network-based, encoding, integration, and transfer to other individuals of perceived or mentally-fabricated patterns. During human evolution, pattern processing capabilities became increasingly sophisticated as the result of expansion of the cerebral cortex, particularly the prefrontal cortex and regions involved in processing of images. Specific patterns, real or imagined, are reinforced by emotional experiences, indoctrination and even psychedelic drugs. Impaired or dysregulated SPP is fundamental to cognitive and psychiatric disorders. A broader understanding of SPP mechanisms, and their roles in normal and abnormal function of the human brain, may enable the development of interventions that reduce irrational decisions and destructive behaviors. PMID:25202234

Spray pattern analysis in TWAS using photogrammetry and digital image correlation

NASA Astrophysics Data System (ADS)

Tillmann, W.; Rademacher, H. G.; Hagen, L.; Abdulgader, M.; El Barad’ei, M.

2018-06-01

In terms of arc spraying processes, the spray plume characteristic is mainly affected by the flow characteristic of the atomization gas at the nozzle inlet and intersection point of the wire tips, which in turn affect the particle distribution at the moment of impact when molten spray particles splash onto the substrate. With respect to the route of manufacturing of near net-shaped coatings on complex geometries, the acquisition of the spray patterns is pressingly necessary to determine the produced coating thickness. Within the scope of this study, computer fluid dynamics (CFD) simulations were carried out to determine the distribution of spray particles for different spray parameter settings. The results were evaluated by three-dimensional spray spot analyses using an optical measurement based on photogrammetry and digital image correlation. The optical measurement represents a promising and much faster candidate to measure spray patterns compared to the tactile measurement system but with an equal accuracy. For given nozzle configurations and spray parameter settings, numerous spray patterns were examined to their shape factors, demonstrating the potential of an online analysis, which encompasses a “fast sample loop” and a data processing system to generate a three-dimensional surface of the spray spot profile.

Qualitative and quantitative processing of side-scan sonar data

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

Dwan, F.S.; Anderson, A.L.; Hilde, T.W.C.

1990-06-01

Modern side-scan sonar systems allow vast areas of seafloor to be rapidly imaged and quantitatively mapped in detail. The application of remote sensing image processing techniques can be used to correct for various distortions inherent in raw sonography. Corrections are possible for water column, slant-range, aspect ratio, speckle and striping noise, multiple returns, power drop-off, and for georeferencing. The final products reveal seafloor features and patterns that are geometrically correct, georeferenced, and have improved signal/noise ratio. These products can be merged with other georeferenced data bases for further database management and information extraction. In order to compare data collected bymore » different systems from a common area and to ground truth measurements and geoacoustic models, quantitative correction must be made for calibrated sonar system and bathymetry effects. Such data inversion must account for system source level, beam pattern, time-varying gain, processing gain, transmission loss, absorption, insonified area, and grazing angle effects. Seafloor classification can then be performed on the calculated back-scattering strength using Lambert's Law and regression analysis. Examples are given using both approaches: image analysis and inversion of data based on the sonar equation.« less

A fractal concentration area method for assigning a color palette for image representation

NASA Astrophysics Data System (ADS)

Cheng, Qiuming; Li, Qingmou

2002-05-01

Displaying the remotely sensed image with a proper color palette is the first task in any kind of image processing and pattern recognition in GIS and image processing environments. The purpose of displaying the image should be not only to provide a visual representation of the variance of the image, although this has been the primary objective of most conventional methods, but also the color palette should reflect real-world features on the ground which must be the primary objective of employing remotely sensed data. Although most conventional methods focus only on the first purpose of image representation, the concentration-area ( C- A plot) fractal method proposed in this paper aims to meet both purposes on the basis of pixel values and pixel value frequency distribution as well as spatial and geometrical properties of image patterns. The C- A method can be used to establish power-law relationships between the area A(⩾ s) with the pixel values greater than s and the pixel value s itself after plotting these values on log-log paper. A number of straight-line segments can be manually or automatically fitted to the points on the log-log paper, each representing a power-law relationship between the area A and the cutoff pixel value for s in a particular range. These straight-line segments can yield a group of cutoff values on the basis of which the image can be classified into discrete classes or zones. These zones usually correspond to the real-world features on the ground. A Windows program has been prepared in ActiveX format for implementing the C- A method and integrating it into other GIS and image processing systems. A case study of Landsat TM band 5 has been used to demonstrate the application of the method and the flexibility of the computer program.

Performance improvements of binary diffractive structures via optimization of the photolithography and dry etch processes

NASA Astrophysics Data System (ADS)

Welch, Kevin; Leonard, Jerry; Jones, Richard D.

2010-08-01

Increasingly stringent requirements on the performance of diffractive optical elements (DOEs) used in wafer scanner illumination systems are driving continuous improvements in their associated manufacturing processes. Specifically, these processes are designed to improve the output pattern uniformity of off-axis illumination systems to minimize degradation in the ultimate imaging performance of a lithographic tool. In this paper, we discuss performance improvements in both photolithographic patterning and RIE etching of fused silica diffractive optical structures. In summary, optimized photolithographic processes were developed to increase critical dimension uniformity and featuresize linearity across the substrate. The photoresist film thickness was also optimized for integration with an improved etch process. This etch process was itself optimized for pattern transfer fidelity, sidewall profile (wall angle, trench bottom flatness), and across-wafer etch depth uniformity. Improvements observed with these processes on idealized test structures (for ease of analysis) led to their implementation in product flows, with comparable increases in performance and yield on customer designs.

Improving the analysis of biogeochemical patterns associated with internal waves in the strait of Gibraltar using remote sensing images

NASA Astrophysics Data System (ADS)

Navarro, Gabriel; Vicent, Jorge; Caballero, Isabel; Gómez-Enri, Jesús; Morris, Edward P.; Sabater, Neus; Macías, Diego; Bolado-Penagos, Marina; Gomiz, Juan Jesús; Bruno, Miguel; Caldeira, Rui; Vázquez, Águeda

2018-05-01

High Amplitude Internal Waves (HAIWs) are physical processes observed in the Strait of Gibraltar (the narrow channel between the Atlantic Ocean and the Mediterranean Sea). These internal waves are generated over the Camarinal Sill (western side of the strait) during the tidal outflow (toward the Atlantic Ocean) when critical hydraulic conditions are established. HAIWs remain over the sill for up to 4 h until the outflow slackens, being then released (mostly) towards the Mediterranean Sea. These have been previously observed using Synthetic Aperture Radar (SAR), which captures variations in surface water roughness. However, in this work we use high resolution optical remote sensing, with the aim of examining the influence of HAIWs on biogeochemical processes. We used hyperspectral images from the Hyperspectral Imager for the Coastal Ocean (HICO) and high spatial resolution (10 m) images from the MultiSpectral Instrument (MSI) onboard the Sentinel-2A satellite. This work represents the first attempt to examine the relation between internal wave generation and the water constituents of the Camarinal Sill using hyperspectral and high spatial resolution remote sensing images. This enhanced spatial and spectral resolution revealed the detailed biogeochemical patterns associated with the internal waves and suggests local enhancements of productivity associated with internal waves trains.

Principal Component Analysis in the Spectral Analysis of the Dynamic Laser Speckle Patterns

NASA Astrophysics Data System (ADS)

Ribeiro, K. M.; Braga, R. A., Jr.; Horgan, G. W.; Ferreira, D. D.; Safadi, T.

2014-02-01

Dynamic laser speckle is a phenomenon that interprets an optical patterns formed by illuminating a surface under changes with coherent light. Therefore, the dynamic change of the speckle patterns caused by biological material is known as biospeckle. Usually, these patterns of optical interference evolving in time are analyzed by graphical or numerical methods, and the analysis in frequency domain has also been an option, however involving large computational requirements which demands new approaches to filter the images in time. Principal component analysis (PCA) works with the statistical decorrelation of data and it can be used as a data filtering. In this context, the present work evaluated the PCA technique to filter in time the data from the biospeckle images aiming the reduction of time computer consuming and improving the robustness of the filtering. It was used 64 images of biospeckle in time observed in a maize seed. The images were arranged in a data matrix and statistically uncorrelated by PCA technique, and the reconstructed signals were analyzed using the routine graphical and numerical methods to analyze the biospeckle. Results showed the potential of the PCA tool in filtering the dynamic laser speckle data, with the definition of markers of principal components related to the biological phenomena and with the advantage of fast computational processing.

High Resolution Imaging Science Experiment (HiRISE) observations of glacial and periglacial morphologies in the circum-Argyre Planitia highlands, Mars

USGS Publications Warehouse

Banks, Maria E.; McEwen, Alfred S.; Kargel, Jeffrey S.; Baker, Victor R.; Strom, Robert G.; Mellon, Michael T.; Gulick, Virginia C.; Keszthelyi, Laszlo; Herkenhoff, Kenneth E.; Pelletier, Jon D.; Jaeger, Windy L.

2008-01-01

The landscape of the Argyre Planitia and adjoining Charitum and Nereidum Montes in the southern hemisphere of Mars has been heavily modified since formation of the Argyre impact basin. This study examines morphologies in the Argyre region revealed in images acquired by the High Resolution Imaging Science Experiment (HiRISE) camera and discusses the implications for glacial and periglacial processes. Distinctive features such as large grooves, semicircular embayments in high topography, and streamlined hills are interpreted as glacially eroded grooves, cirques, and whalebacks or roche moutonnée, respectively. Large boulders scattered across the floor of a valley may be ground moraine deposited by ice ablation. Glacial interpretations are supported by the association of these features with other landforms typical of glaciated landscapes such as broad valleys with parabolic cross sections and stepped longitudinal profiles, lobate debris aprons interpreted as remnant debris covered glaciers or rock glaciers, and possible hanging valleys. Aligned boulders observed on slopes may also indicate glacial processes such as fluting. Alternatively, boulders aligned on slopes and organized in clumps and polygonal patterns on flatter surfaces may indicate periglacial processes, perhaps postglaciation, that form patterned ground. At least portions of the Argyre region appear to have been modified by processes of ice accumulation, glacial flow, erosion, sediment deposition, ice stagnation and ablation, and perhaps subsequent periglacial processes. The type of bedrock erosion apparent in images suggests that glaciers were, at times, wet based. The number of superposed craters is consistent with geologically recent glacial activity, but may be due to subsequent modification.

Integrated optical 3D digital imaging based on DSP scheme

NASA Astrophysics Data System (ADS)

Wang, Xiaodong; Peng, Xiang; Gao, Bruce Z.

2008-03-01

We present a scheme of integrated optical 3-D digital imaging (IO3DI) based on digital signal processor (DSP), which can acquire range images independently without PC support. This scheme is based on a parallel hardware structure with aid of DSP and field programmable gate array (FPGA) to realize 3-D imaging. In this integrated scheme of 3-D imaging, the phase measurement profilometry is adopted. To realize the pipeline processing of the fringe projection, image acquisition and fringe pattern analysis, we present a multi-threads application program that is developed under the environment of DSP/BIOS RTOS (real-time operating system). Since RTOS provides a preemptive kernel and powerful configuration tool, with which we are able to achieve a real-time scheduling and synchronization. To accelerate automatic fringe analysis and phase unwrapping, we make use of the technique of software optimization. The proposed scheme can reach a performance of 39.5 f/s (frames per second), so it may well fit into real-time fringe-pattern analysis and can implement fast 3-D imaging. Experiment results are also presented to show the validity of proposed scheme.

Camera calibration based on the back projection process

NASA Astrophysics Data System (ADS)

Gu, Feifei; Zhao, Hong; Ma, Yueyang; Bu, Penghui

2015-12-01

Camera calibration plays a crucial role in 3D measurement tasks of machine vision. In typical calibration processes, camera parameters are iteratively optimized in the forward imaging process (FIP). However, the results can only guarantee the minimum of 2D projection errors on the image plane, but not the minimum of 3D reconstruction errors. In this paper, we propose a universal method for camera calibration, which uses the back projection process (BPP). In our method, a forward projection model is used to obtain initial intrinsic and extrinsic parameters with a popular planar checkerboard pattern. Then, the extracted image points are projected back into 3D space and compared with the ideal point coordinates. Finally, the estimation of the camera parameters is refined by a non-linear function minimization process. The proposed method can obtain a more accurate calibration result, which is more physically useful. Simulation and practical data are given to demonstrate the accuracy of the proposed method.

MToS: A Tree of Shapes for Multivariate Images.

PubMed

Carlinet, Edwin; Géraud, Thierry

2015-12-01

The topographic map of a gray-level image, also called tree of shapes, provides a high-level hierarchical representation of the image contents. This representation, invariant to contrast changes and to contrast inversion, has been proved very useful to achieve many image processing and pattern recognition tasks. Its definition relies on the total ordering of pixel values, so this representation does not exist for color images, or more generally, multivariate images. Common workarounds, such as marginal processing, or imposing a total order on data, are not satisfactory and yield many problems. This paper presents a method to build a tree-based representation of multivariate images, which features marginally the same properties of the gray-level tree of shapes. Briefly put, we do not impose an arbitrary ordering on values, but we only rely on the inclusion relationship between shapes in the image definition domain. The interest of having a contrast invariant and self-dual representation of multivariate image is illustrated through several applications (filtering, segmentation, and object recognition) on different types of data: color natural images, document images, satellite hyperspectral imaging, multimodal medical imaging, and videos.

COMPUTATIONAL ANALYSIS BASED ON ARTIFICIAL NEURAL NETWORKS FOR AIDING IN DIAGNOSING OSTEOARTHRITIS OF THE LUMBAR SPINE.

PubMed

Veronezi, Carlos Cassiano Denipotti; de Azevedo Simões, Priscyla Waleska Targino; Dos Santos, Robson Luiz; da Rocha, Edroaldo Lummertz; Meláo, Suelen; de Mattos, Merisandra Côrtes; Cechinel, Cristian

2011-01-01

To ascertain the advantages of applying artificial neural networks to recognize patterns on lumbar spine radiographies in order to aid in the process of diagnosing primary osteoarthritis. This was a cross-sectional descriptive analytical study with a quantitative approach and an emphasis on diagnosis. The training set was composed of images collected between January and July 2009 from patients who had undergone lateral-view digital radiographies of the lumbar spine, which were provided by a radiology clinic located in the municipality of Criciúma (SC). Out of the total of 260 images gathered, those with distortions, those presenting pathological conditions that altered the architecture of the lumbar spine and those with patterns that were difficult to characterize were discarded, resulting in 206 images. The image data base (n = 206) was then subdivided, resulting in 68 radiographies for the training stage, 68 images for tests and 70 for validation. A hybrid neural network based on Kohonen self-organizing maps and on Multilayer Perceptron networks was used. After 90 cycles, the validation was carried out on the best results, achieving accuracy of 62.85%, sensitivity of 65.71% and specificity of 60%. Even though the effectiveness shown was moderate, this study is still innovative. The values show that the technique used has a promising future, pointing towards further studies on image and cycle processing methodology with a larger quantity of radiographies.

Expanding the printable design space for lithography processes utilizing a cut mask

NASA Astrophysics Data System (ADS)

Wandell, Jerome; Salama, Mohamed; Wilkinson, William; Curtice, Mark; Feng, Jui-Hsuan; Gao, Shao Wen; Asthana, Abhishek

2016-03-01

The utilization of a cut-mask in semiconductor patterning processes has been in practice for logic devices since the inception of 32nm-node devices, notably with unidirectional gate level printing. However, the microprocessor applications where cut-mask patterning methods are used are expanding as Self-Aligned Double Patterning (SADP) processes become mainstream for 22/14nm fin diffusion, and sub-14nm metal levels. One common weakness for these types of lithography processes is that the initial pattern requiring the follow-up cut-mask typically uses an extreme off-axis imaging source such as dipole to enhance the resolution and line-width roughness (LWR) for critical dense patterns. This source condition suffers from poor process margin in the semi-dense (forbidden pitch) realm and wrong-way directional design spaces. Common pattern failures in these limited design regions include bridging and extra-printing defects that are difficult to resolve with traditional mask improvement means. This forces the device maker to limit the allowable geometries that a designer may use on a device layer. This paper will demonstrate methods to expand the usable design space on dipole-like processes such as unidirectional gate and SADP processes by utilizing the follow-up cut mask to improve the process window. Traditional mask enhancement means for improving the process window in this design realm will be compared to this new cut-mask approach. The unique advantages and disadvantages of the cut-mask solution will be discussed in contrast to those customary methods.

Dual Use of Image Based Tracking Techniques: Laser Eye Surgery and Low Vision Prosthesis

NASA Technical Reports Server (NTRS)

Juday, Richard D.; Barton, R. Shane

1994-01-01

With a concentration on Fourier optics pattern recognition, we have developed several methods of tracking objects in dynamic imagery to automate certain space applications such as orbital rendezvous and spacecraft capture, or planetary landing. We are developing two of these techniques for Earth applications in real-time medical image processing. The first is warping of a video image, developed to evoke shift invariance to scale and rotation in correlation pattern recognition. The technology is being applied to compensation for certain field defects in low vision humans. The second is using the optical joint Fourier transform to track the translation of unmodeled scenes. Developed as an image fixation tool to assist in calculating shape from motion, it is being applied to tracking motions of the eyeball quickly enough to keep a laser photocoagulation spot fixed on the retina, thus avoiding collateral damage.

Bi-dimensional empirical mode decomposition based fringe-like pattern suppression in polarization interference imaging spectrometer

NASA Astrophysics Data System (ADS)

Ren, Wenyi; Cao, Qizhi; Wu, Dan; Jiang, Jiangang; Yang, Guoan; Xie, Yingge; Wang, Guodong; Zhang, Sheqi

2018-01-01

Many observers using interference imaging spectrometer were plagued by the fringe-like pattern(FP) that occurs for optical wavelengths in red and near-infrared region. It brings us more difficulties in the data processing such as the spectrum calibration, information retrieval, and so on. An adaptive method based on the bi-dimensional empirical mode decomposition was developed to suppress the nonlinear FP in polarization interference imaging spectrometer. The FP and corrected interferogram were separated effectively. Meanwhile, the stripes introduced by CCD mosaic was suppressed. The nonlinear interferogram background removal and the spectrum distortion correction were implemented as well. It provides us an alternative method to adaptively suppress the nonlinear FP without prior experimental data and knowledge. This approach potentially is a powerful tool in the fields of Fourier transform spectroscopy, holographic imaging, optical measurement based on moire fringe, etc.

Method for determining and displaying the spacial distribution of a spectral pattern of received light

DOEpatents

Bennett, Charles L.

1996-01-01

An imaging Fourier transform spectrometer (10, 210) having a Fourier transform infrared spectrometer (12) providing a series of images (40) to a focal plane array camera (38). The focal plane array camera (38) is clocked to a multiple of zero crossing occurrences as caused by a moving mirror (18) of the Fourier transform infrared spectrometer (12) and as detected by a laser detector (50) such that the frame capture rate of the focal plane array camera (38) corresponds to a multiple of the zero crossing rate of the Fourier transform infrared spectrometer (12). The images (40) are transmitted to a computer (45) for processing such that representations of the images (40) as viewed in the light of an arbitrary spectral "fingerprint" pattern can be displayed on a monitor (60) or otherwise stored and manipulated by the computer (45).

Decoding mobile-phone image sensor rolling shutter effect for visible light communications

NASA Astrophysics Data System (ADS)

Liu, Yang

2016-01-01

Optical wireless communication (OWC) using visible lights, also known as visible light communication (VLC), has attracted significant attention recently. As the traditional OWC and VLC receivers (Rxs) are based on PIN photo-diode or avalanche photo-diode, deploying the complementary metal-oxide-semiconductor (CMOS) image sensor as the VLC Rx is attractive since nowadays nearly every person has a smart phone with embedded CMOS image sensor. However, deploying the CMOS image sensor as the VLC Rx is challenging. In this work, we propose and demonstrate two simple contrast ratio (CR) enhancement schemes to improve the contrast of the rolling shutter pattern. Then we describe their processing algorithms one by one. The experimental results show that both the proposed CR enhancement schemes can significantly mitigate the high-intensity fluctuations of the rolling shutter pattern and improve the bit-error-rate performance.

Reversible integer wavelet transform for blind image hiding method

PubMed Central

Bibi, Nargis; Mahmood, Zahid; Akram, Tallha; Naqvi, Syed Rameez

2017-01-01

In this article, a blind data hiding reversible methodology to embed the secret data for hiding purpose into cover image is proposed. The key advantage of this research work is to resolve the privacy and secrecy issues raised during the data transmission over the internet. Firstly, data is decomposed into sub-bands using the integer wavelets. For decomposition, the Fresnelet transform is utilized which encrypts the secret data by choosing a unique key parameter to construct a dummy pattern. The dummy pattern is then embedded into an approximated sub-band of the cover image. Our proposed method reveals high-capacity and great imperceptibility of the secret embedded data. With the utilization of family of integer wavelets, the proposed novel approach becomes more efficient for hiding and retrieving process. It retrieved the secret hidden data from the embedded data blindly, without the requirement of original cover image. PMID:28498855

Dual use of image based tracking techniques: Laser eye surgery and low vision prosthesis

NASA Technical Reports Server (NTRS)

Juday, Richard D.

1994-01-01

With a concentration on Fourier optics pattern recognition, we have developed several methods of tracking objects in dynamic imagery to automate certain space applications such as orbital rendezvous and spacecraft capture, or planetary landing. We are developing two of these techniques for Earth applications in real-time medical image processing. The first is warping of a video image, developed to evoke shift invariance to scale and rotation in correlation pattern recognition. The technology is being applied to compensation for certain field defects in low vision humans. The second is using the optical joint Fourier transform to track the translation of unmodeled scenes. Developed as an image fixation tool to assist in calculating shape from motion, it is being applied to tracking motions of the eyeball quickly enough to keep a laser photocoagulation spot fixed on the retina, thus avoiding collateral damage.

Spatial light modulator array with heat minimization and image enhancement features

DOEpatents

Jain, Kanti [Briarcliff Manor, NY; Sweatt, William C [Albuquerque, NM; Zemel, Marc [New Rochelle, NY

2007-01-30

An enhanced spatial light modulator (ESLM) array, a microelectronics patterning system and a projection display system using such an ESLM for heat-minimization and resolution enhancement during imaging, and the method for fabricating such an ESLM array. The ESLM array includes, in each individual pixel element, a small pixel mirror (reflective region) and a much larger pixel surround. Each pixel surround includes diffraction-grating regions and resolution-enhancement regions. During imaging, a selected pixel mirror reflects a selected-pixel beamlet into the capture angle of a projection lens, while the diffraction grating of the pixel surround redirects heat-producing unused radiation away from the projection lens. The resolution-enhancement regions of selected pixels provide phase shifts that increase effective modulation-transfer function in imaging. All of the non-selected pixel surrounds redirect all radiation energy away from the projection lens. All elements of the ESLM are fabricated by deposition, patterning, etching and other microelectronic process technologies.

Method for characterizing mask defects using image reconstruction from X-ray diffraction patterns

DOEpatents

Hau-Riege, Stefan Peter [Fremont, CA

2007-05-01

The invention applies techniques for image reconstruction from X-ray diffraction patterns on the three-dimensional imaging of defects in EUVL multilayer films. The reconstructed image gives information about the out-of-plane position and the diffraction strength of the defect. The positional information can be used to select the correct defect repair technique. This invention enables the fabrication of defect-free (since repaired) X-ray Mo--Si multilayer mirrors. Repairing Mo--Si multilayer-film defects on mask blanks is a key for the commercial success of EUVL. It is known that particles are added to the Mo--Si multilayer film during the fabrication process. There is a large effort to reduce this contamination, but results are not sufficient, and defects continue to be a major mask yield limiter. All suggested repair strategies need to know the out-of-plane position of the defects in the multilayer.

The Role of Prototype Learning in Hierarchical Models of Vision

ERIC Educational Resources Information Center

Thomure, Michael David

2014-01-01

I conduct a study of learning in HMAX-like models, which are hierarchical models of visual processing in biological vision systems. Such models compute a new representation for an image based on the similarity of image sub-parts to a number of specific patterns, called prototypes. Despite being a central piece of the overall model, the issue of…

Artifacts in magnetic spirals retrieved by transport of intensity equation (TIE)

NASA Astrophysics Data System (ADS)

Cui, J.; Yao, Y.; Shen, X.; Wang, Y. G.; Yu, R. C.

2018-05-01

The artifacts in the magnetic structures reconstructed from Lorentz transmission electron microscopy (LTEM) images with TIE method have been analyzed in detail. The processing for the simulated images of Bloch and Neel spirals indicated that the improper parameters in TIE may overestimate the high frequency information and induce some false features in the retrieved images. The specimen tilting will further complicate the analysis of the images because the LTEM image contrast is not the result of the magnetization distribution within the specimen but the integral projection pattern of the magnetic induction filling the entire space including the specimen.

Infrared thermography quantitative image processing

NASA Astrophysics Data System (ADS)

Skouroliakou, A.; Kalatzis, I.; Kalyvas, N.; Grivas, TB

2017-11-01

Infrared thermography is an imaging technique that has the ability to provide a map of temperature distribution of an object’s surface. It is considered for a wide range of applications in medicine as well as in non-destructive testing procedures. One of its promising medical applications is in orthopaedics and diseases of the musculoskeletal system where temperature distribution of the body’s surface can contribute to the diagnosis and follow up of certain disorders. Although the thermographic image can give a fairly good visual estimation of distribution homogeneity and temperature pattern differences between two symmetric body parts, it is important to extract a quantitative measurement characterising temperature. Certain approaches use temperature of enantiomorphic anatomical points, or parameters extracted from a Region of Interest (ROI). A number of indices have been developed by researchers to that end. In this study a quantitative approach in thermographic image processing is attempted based on extracting different indices for symmetric ROIs on thermograms of the lower back area of scoliotic patients. The indices are based on first order statistical parameters describing temperature distribution. Analysis and comparison of these indices result in evaluating the temperature distribution pattern of the back trunk expected in healthy, regarding spinal problems, subjects.

Advances in two photon scanning and scanless microscopy technologies for functional neural circuit imaging.

PubMed

Schultz, Simon R; Copeland, Caroline S; Foust, Amanda J; Quicke, Peter; Schuck, Renaud

2017-01-01

Recent years have seen substantial developments in technology for imaging neural circuits, raising the prospect of large scale imaging studies of neural populations involved in information processing, with the potential to lead to step changes in our understanding of brain function and dysfunction. In this article we will review some key recent advances: improved fluorophores for single cell resolution functional neuroimaging using a two photon microscope; improved approaches to the problem of scanning active circuits; and the prospect of scanless microscopes which overcome some of the bandwidth limitations of current imaging techniques. These advances in technology for experimental neuroscience have in themselves led to technical challenges, such as the need for the development of novel signal processing and data analysis tools in order to make the most of the new experimental tools. We review recent work in some active topics, such as region of interest segmentation algorithms capable of demixing overlapping signals, and new highly accurate algorithms for calcium transient detection. These advances motivate the development of new data analysis tools capable of dealing with spatial or spatiotemporal patterns of neural activity, that scale well with pattern size.

Advances in two photon scanning and scanless microscopy technologies for functional neural circuit imaging

PubMed Central

Schultz, Simon R.; Copeland, Caroline S.; Foust, Amanda J.; Quicke, Peter; Schuck, Renaud

2017-01-01

Recent years have seen substantial developments in technology for imaging neural circuits, raising the prospect of large scale imaging studies of neural populations involved in information processing, with the potential to lead to step changes in our understanding of brain function and dysfunction. In this article we will review some key recent advances: improved fluorophores for single cell resolution functional neuroimaging using a two photon microscope; improved approaches to the problem of scanning active circuits; and the prospect of scanless microscopes which overcome some of the bandwidth limitations of current imaging techniques. These advances in technology for experimental neuroscience have in themselves led to technical challenges, such as the need for the development of novel signal processing and data analysis tools in order to make the most of the new experimental tools. We review recent work in some active topics, such as region of interest segmentation algorithms capable of demixing overlapping signals, and new highly accurate algorithms for calcium transient detection. These advances motivate the development of new data analysis tools capable of dealing with spatial or spatiotemporal patterns of neural activity, that scale well with pattern size. PMID:28757657

Optical image encryption via high-quality computational ghost imaging using iterative phase retrieval

NASA Astrophysics Data System (ADS)

Liansheng, Sui; Yin, Cheng; Bing, Li; Ailing, Tian; Krishna Asundi, Anand

2018-07-01

A novel computational ghost imaging scheme based on specially designed phase-only masks, which can be efficiently applied to encrypt an original image into a series of measured intensities, is proposed in this paper. First, a Hadamard matrix with a certain order is generated, where the number of elements in each row is equal to the size of the original image to be encrypted. Each row of the matrix is rearranged into the corresponding 2D pattern. Then, each pattern is encoded into the phase-only masks by making use of an iterative phase retrieval algorithm. These specially designed masks can be wholly or partially used in the process of computational ghost imaging to reconstruct the original information with high quality. When a significantly small number of phase-only masks are used to record the measured intensities in a single-pixel bucket detector, the information can be authenticated without clear visualization by calculating the nonlinear correlation map between the original image and its reconstruction. The results illustrate the feasibility and effectiveness of the proposed computational ghost imaging mechanism, which will provide an effective alternative for enriching the related research on the computational ghost imaging technique.

Terrain type recognition using ERTS-1 MSS images

NASA Technical Reports Server (NTRS)

Gramenopoulos, N.

1973-01-01

For the automatic recognition of earth resources from ERTS-1 digital tapes, both multispectral and spatial pattern recognition techniques are important. Recognition of terrain types is based on spatial signatures that become evident by processing small portions of an image through selected algorithms. An investigation of spatial signatures that are applicable to ERTS-1 MSS images is described. Artifacts in the spatial signatures seem to be related to the multispectral scanner. A method for suppressing such artifacts is presented. Finally, results of terrain type recognition for one ERTS-1 image are presented.

Neural network-based system for pattern recognition through a fiber optic bundle

NASA Astrophysics Data System (ADS)

Gamo-Aranda, Javier; Rodriguez-Horche, Paloma; Merchan-Palacios, Miguel; Rosales-Herrera, Pablo; Rodriguez, M.

2001-04-01

A neural network based system to identify images transmitted through a Coherent Fiber-optic Bundle (CFB) is presented. Patterns are generated in a computer, displayed on a Spatial Light Modulator, imaged onto the input face of the CFB, and recovered optically by a CCD sensor array for further processing. Input and output optical subsystems were designed and used to that end. The recognition step of the transmitted patterns is made by a powerful, widely-used, neural network simulator running on the control PC. A complete PC-based interface was developed to control the different tasks involved in the system. An optical analysis of the system capabilities was carried out prior to performing the recognition step. Several neural network topologies were tested, and the corresponding numerical results are also presented and discussed.

Beyond the ridge pattern: multi-informative analysis of latent fingermarks by MALDI mass spectrometry.

PubMed

Francese, S; Bradshaw, R; Ferguson, L S; Wolstenholme, R; Clench, M R; Bleay, S

2013-08-07

After over a century, fingerprints are still one of the most powerful means of biometric identification. The conventional forensic workflow for suspect identification consists of (i) recovering latent marks from crime scenes using the appropriate enhancement technique and (ii) obtaining an image of the mark to compare either against known suspect prints and/or to search in a Fingerprint Database. The suspect is identified through matching the ridge pattern and local characteristics of the ridge pattern (minutiae). However successful, there are a number of scenarios in which this process may fail; they include the recovery of partial, distorted or smudged marks, poor quality of the image resulting from inadequacy of the enhancement technique applied, extensive scarring/abrasion of the fingertips or absence of suspect's fingerprint records in the database. In all of these instances it would be very desirable to have a technology able to provide additional information from a fingermark exploiting its endogenous and exogenous chemical content. This opportunity could potentially provide new investigative leads, especially when the fingermark comparison and match process fails. We have demonstrated that Matrix Assisted Laser Desorption Ionisation Mass Spectrometry and Mass Spectrometry Imaging (MALDI MSI) can provide multiple images of the same fingermark in one analysis simultaneous with additional intelligence. Here, a review on the pioneering use and development of MALDI MSI for the analysis of latent fingermarks is presented along with the latest achievements on the forensic intelligence retrievable.

Digital mammography, cancer screening: Factors important for image compression

NASA Technical Reports Server (NTRS)

Clarke, Laurence P.; Blaine, G. James; Doi, Kunio; Yaffe, Martin J.; Shtern, Faina; Brown, G. Stephen; Winfield, Daniel L.; Kallergi, Maria

1993-01-01

The use of digital mammography for breast cancer screening poses several novel problems such as development of digital sensors, computer assisted diagnosis (CAD) methods for image noise suppression, enhancement, and pattern recognition, compression algorithms for image storage, transmission, and remote diagnosis. X-ray digital mammography using novel direct digital detection schemes or film digitizers results in large data sets and, therefore, image compression methods will play a significant role in the image processing and analysis by CAD techniques. In view of the extensive compression required, the relative merit of 'virtually lossless' versus lossy methods should be determined. A brief overview is presented here of the developments of digital sensors, CAD, and compression methods currently proposed and tested for mammography. The objective of the NCI/NASA Working Group on Digital Mammography is to stimulate the interest of the image processing and compression scientific community for this medical application and identify possible dual use technologies within the NASA centers.

Low-level processing for real-time image analysis

NASA Technical Reports Server (NTRS)

Eskenazi, R.; Wilf, J. M.

1979-01-01

A system that detects object outlines in television images in real time is described. A high-speed pipeline processor transforms the raw image into an edge map and a microprocessor, which is integrated into the system, clusters the edges, and represents them as chain codes. Image statistics, useful for higher level tasks such as pattern recognition, are computed by the microprocessor. Peak intensity and peak gradient values are extracted within a programmable window and are used for iris and focus control. The algorithms implemented in hardware and the pipeline processor architecture are described. The strategy for partitioning functions in the pipeline was chosen to make the implementation modular. The microprocessor interface allows flexible and adaptive control of the feature extraction process. The software algorithms for clustering edge segments, creating chain codes, and computing image statistics are also discussed. A strategy for real time image analysis that uses this system is given.

A Mathematical Model for Storage and Recall of Images using Targeted Synchronization of Coupled Maps.

PubMed

Palaniyandi, P; Rangarajan, Govindan

2017-08-21

We propose a mathematical model for storage and recall of images using coupled maps. We start by theoretically investigating targeted synchronization in coupled map systems wherein only a desired (partial) subset of the maps is made to synchronize. A simple method is introduced to specify coupling coefficients such that targeted synchronization is ensured. The principle of this method is extended to storage/recall of images using coupled Rulkov maps. The process of adjusting coupling coefficients between Rulkov maps (often used to model neurons) for the purpose of storing a desired image mimics the process of adjusting synaptic strengths between neurons to store memories. Our method uses both synchronisation and synaptic weight modification, as the human brain is thought to do. The stored image can be recalled by providing an initial random pattern to the dynamical system. The storage and recall of the standard image of Lena is explicitly demonstrated.

ImgLib2--generic image processing in Java.

PubMed

Pietzsch, Tobias; Preibisch, Stephan; Tomancák, Pavel; Saalfeld, Stephan

2012-11-15

ImgLib2 is an open-source Java library for n-dimensional data representation and manipulation with focus on image processing. It aims at minimizing code duplication by cleanly separating pixel-algebra, data access and data representation in memory. Algorithms can be implemented for classes of pixel types and generic access patterns by which they become independent of the specific dimensionality, pixel type and data representation. ImgLib2 illustrates that an elegant high-level programming interface can be achieved without sacrificing performance. It provides efficient implementations of common data types, storage layouts and algorithms. It is the data model underlying ImageJ2, the KNIME Image Processing toolbox and an increasing number of Fiji-Plugins. ImgLib2 is licensed under BSD. Documentation and source code are available at http://imglib2.net and in a public repository at https://github.com/imagej/imglib. Supplementary data are available at Bioinformatics Online. saalfeld@mpi-cbg.de

Laser Speckle Imaging of Cerebral Blood Flow

NASA Astrophysics Data System (ADS)

Luo, Qingming; Jiang, Chao; Li, Pengcheng; Cheng, Haiying; Wang, Zhen; Wang, Zheng; Tuchin, Valery V.

Monitoring the spatio-temporal characteristics of cerebral blood flow (CBF) is crucial for studying the normal and pathophysiologic conditions of brain metabolism. By illuminating the cortex with laser light and imaging the resulting speckle pattern, relative CBF images with tens of microns spatial and millisecond temporal resolution can be obtained. In this chapter, a laser speckle imaging (LSI) method for monitoring dynamic, high-resolution CBF is introduced. To improve the spatial resolution of current LSI, a modified LSI method is proposed. To accelerate the speed of data processing, three LSI data processing frameworks based on graphics processing unit (GPU), digital signal processor (DSP), and field-programmable gate array (FPGA) are also presented. Applications for detecting the changes in local CBF induced by sensory stimulation and thermal stimulation, the influence of a chemical agent on CBF, and the influence of acute hyperglycemia following cortical spreading depression on CBF are given.

Smart sensor for terminal homing

NASA Astrophysics Data System (ADS)

Panda, D.; Aggarwal, R.; Hummel, R.

1980-01-01

The practical scene matching problem is considered to present certain complications which must extend classical image processing capabilities. Certain aspects of the scene matching problem which must be addressed by a smart sensor for terminal homing are discussed. First a philosophy for treating the matching problem for the terminal homing scenario is outlined. Then certain aspects of the feature extraction process and symbolic pattern matching are considered. It is thought that in the future general ideas from artificial intelligence will be more useful for terminal homing requirements of fast scene recognition and pattern matching.

Electrophysiological brain dynamics during the esthetic judgment of human bodies and faces.

PubMed

Muñoz, Francisco; Martín-Loeches, Manuel

2015-01-12

This experiment investigated how the esthetic judgment of human body and face modulates cognitive and affective processes. We hypothesized that judgments on ugliness and beauty would elicit separable event-related brain potentials (ERP) patterns, depending on the esthetic value of body and faces in both genders. In a pretest session, participants evaluated images in a range from very ugly to very beautiful, what generated three sets of beautiful, ugly and neutral faces and bodies. In the recording session, they performed a task consisting in a beautiful-neutral-ugly judgment. Cognitive and affective effects were observed on a differential pattern of ERP components (P200, P300 and LPC). Main findings revealed a P200 amplitude increase to ugly images, probably the result of a negativity bias in attentional processes. A P300 increase was found mostly to beautiful images, particularly to female bodies, consistent with the salience of these stimuli, particularly for stimulus categorization. LPC appeared significantly larger to both ugly and beautiful images, probably reflecting later, decision processes linked to keeping information in working memory. This finding was especially remarkable for ugly male faces. Our findings are discussed on the ground of evolutionary and adaptive value of esthetics in person evaluation. This article is part of a Special Issue entitled Hold Item. Copyright © 2014 Elsevier B.V. All rights reserved.

EUV phase-shifting masks and aberration monitors

NASA Astrophysics Data System (ADS)

Deng, Yunfei; Neureuther, Andrew R.

2002-07-01

Rigorous electromagnetic simulation with TEMPEST is used to examine the use of phase-shifting masks in EUV lithography. The effects of oblique incident illumination and mask patterning by ion-mixing of multilayers are analyzed. Oblique incident illumination causes streamers at absorber edges and causes position shifting in aerial images. The diffraction waves between ion-mixed and pristine multilayers are observed. The phase-shifting caused by stepped substrates is simulated and images show that it succeeds in creation of phase-shifting effects. The diffraction process at the phase boundary is also analyzed. As an example of EUV phase-shifting masks, a coma pattern and probe based aberration monitor is simulated and aerial images are formed under different levels of coma aberration. The probe signal rises quickly as coma increases as designed.

Correcting geometric and photometric distortion of document images on a smartphone

NASA Astrophysics Data System (ADS)

Simon, Christian; Williem; Park, In Kyu

2015-01-01

A set of document image processing algorithms for improving the optical character recognition (OCR) capability of smartphone applications is presented. The scope of the problem covers the geometric and photometric distortion correction of document images. The proposed framework was developed to satisfy industrial requirements. It is implemented on an off-the-shelf smartphone with limited resources in terms of speed and memory. Geometric distortions, i.e., skew and perspective distortion, are corrected by sending horizontal and vertical vanishing points toward infinity in a downsampled image. Photometric distortion includes image degradation from moiré pattern noise and specular highlights. Moiré pattern noise is removed using low-pass filters with different sizes independently applied to the background and text region. The contrast of the text in a specular highlighted area is enhanced by locally enlarging the intensity difference between the background and text while the noise is suppressed. Intensive experiments indicate that the proposed methods show a consistent and robust performance on a smartphone with a runtime of less than 1 s.

Inviscid Limit for Damped and Driven Incompressible Navier-Stokes Equations in mathbb R^2

NASA Astrophysics Data System (ADS)

Ramanah, D.; Raghunath, S.; Mee, D. J.; Rösgen, T.; Jacobs, P. A.

2007-08-01

Experiments to demonstrate the use of the background-oriented schlieren (BOS) technique in hypersonic impulse facilities are reported. BOS uses a simple optical set-up consisting of a structured background pattern, an electronic camera with a high shutter speed and a high intensity light source. The visualization technique is demonstrated in a small reflected shock tunnel with a Mach 4 conical nozzle, nozzle supply pressure of 2.2 MPa and nozzle supply enthalpy of 1.8 MJ/kg. A 20° sharp circular cone and a model of the MUSES-C re-entry body were tested. Images captured were processed using PIV-style image analysis to visualize variations in the density field. The shock angle on the cone measured from the BOS images agreed with theoretical calculations to within 0.5°. Shock standoff distances could be measured from the BOS image for the re-entry body. Preliminary experiments are also reported in higher enthalpy facilities where flow luminosity can interfere with imaging of the background pattern.

Automated quantitative histology reveals vascular morphodynamics during Arabidopsis hypocotyl secondary growth.

PubMed

Sankar, Martial; Nieminen, Kaisa; Ragni, Laura; Xenarios, Ioannis; Hardtke, Christian S

2014-02-11

Among various advantages, their small size makes model organisms preferred subjects of investigation. Yet, even in model systems detailed analysis of numerous developmental processes at cellular level is severely hampered by their scale. For instance, secondary growth of Arabidopsis hypocotyls creates a radial pattern of highly specialized tissues that comprises several thousand cells starting from a few dozen. This dynamic process is difficult to follow because of its scale and because it can only be investigated invasively, precluding comprehensive understanding of the cell proliferation, differentiation, and patterning events involved. To overcome such limitation, we established an automated quantitative histology approach. We acquired hypocotyl cross-sections from tiled high-resolution images and extracted their information content using custom high-throughput image processing and segmentation. Coupled with automated cell type recognition through machine learning, we could establish a cellular resolution atlas that reveals vascular morphodynamics during secondary growth, for example equidistant phloem pole formation. DOI: http://dx.doi.org/10.7554/eLife.01567.001.

Automated quantitative histology reveals vascular morphodynamics during Arabidopsis hypocotyl secondary growth

PubMed Central

Sankar, Martial; Nieminen, Kaisa; Ragni, Laura; Xenarios, Ioannis; Hardtke, Christian S

2014-01-01

Among various advantages, their small size makes model organisms preferred subjects of investigation. Yet, even in model systems detailed analysis of numerous developmental processes at cellular level is severely hampered by their scale. For instance, secondary growth of Arabidopsis hypocotyls creates a radial pattern of highly specialized tissues that comprises several thousand cells starting from a few dozen. This dynamic process is difficult to follow because of its scale and because it can only be investigated invasively, precluding comprehensive understanding of the cell proliferation, differentiation, and patterning events involved. To overcome such limitation, we established an automated quantitative histology approach. We acquired hypocotyl cross-sections from tiled high-resolution images and extracted their information content using custom high-throughput image processing and segmentation. Coupled with automated cell type recognition through machine learning, we could establish a cellular resolution atlas that reveals vascular morphodynamics during secondary growth, for example equidistant phloem pole formation. DOI: http://dx.doi.org/10.7554/eLife.01567.001 PMID:24520159

PCA-based spatially adaptive denoising of CFA images for single-sensor digital cameras.

PubMed

Zheng, Lei; Lukac, Rastislav; Wu, Xiaolin; Zhang, David

2009-04-01

Single-sensor digital color cameras use a process called color demosiacking to produce full color images from the data captured by a color filter array (CAF). The quality of demosiacked images is degraded due to the sensor noise introduced during the image acquisition process. The conventional solution to combating CFA sensor noise is demosiacking first, followed by a separate denoising processing. This strategy will generate many noise-caused color artifacts in the demosiacking process, which are hard to remove in the denoising process. Few denoising schemes that work directly on the CFA images have been presented because of the difficulties arisen from the red, green and blue interlaced mosaic pattern, yet a well-designed "denoising first and demosiacking later" scheme can have advantages such as less noise-caused color artifacts and cost-effective implementation. This paper presents a principle component analysis (PCA)-based spatially-adaptive denoising algorithm, which works directly on the CFA data using a supporting window to analyze the local image statistics. By exploiting the spatial and spectral correlations existing in the CFA image, the proposed method can effectively suppress noise while preserving color edges and details. Experiments using both simulated and real CFA images indicate that the proposed scheme outperforms many existing approaches, including those sophisticated demosiacking and denoising schemes, in terms of both objective measurement and visual evaluation.

Masking Strategies for Image Manifolds.

PubMed

Dadkhahi, Hamid; Duarte, Marco F

2016-07-07

We consider the problem of selecting an optimal mask for an image manifold, i.e., choosing a subset of the pixels of the image that preserves the manifold's geometric structure present in the original data. Such masking implements a form of compressive sensing through emerging imaging sensor platforms for which the power expense grows with the number of pixels acquired. Our goal is for the manifold learned from masked images to resemble its full image counterpart as closely as possible. More precisely, we show that one can indeed accurately learn an image manifold without having to consider a large majority of the image pixels. In doing so, we consider two masking methods that preserve the local and global geometric structure of the manifold, respectively. In each case, the process of finding the optimal masking pattern can be cast as a binary integer program, which is computationally expensive but can be approximated by a fast greedy algorithm. Numerical experiments show that the relevant manifold structure is preserved through the datadependent masking process, even for modest mask sizes.

NeuroPG: open source software for optical pattern generation and data acquisition

PubMed Central

Avants, Benjamin W.; Murphy, Daniel B.; Dapello, Joel A.; Robinson, Jacob T.

2015-01-01

Patterned illumination using a digital micromirror device (DMD) is a powerful tool for optogenetics. Compared to a scanning laser, DMDs are inexpensive and can easily create complex illumination patterns. Combining these complex spatiotemporal illumination patterns with optogenetics allows DMD-equipped microscopes to probe neural circuits by selectively manipulating the activity of many individual cells or many subcellular regions at the same time. To use DMDs to study neural activity, scientists must develop specialized software to coordinate optical stimulation patterns with the acquisition of electrophysiological and fluorescence data. To meet this growing need we have developed an open source optical pattern generation software for neuroscience—NeuroPG—that combines, DMD control, sample visualization, and data acquisition in one application. Built on a MATLAB platform, NeuroPG can also process, analyze, and visualize data. The software is designed specifically for the Mightex Polygon400; however, as an open source package, NeuroPG can be modified to incorporate any data acquisition, imaging, or illumination equipment that is compatible with MATLAB’s Data Acquisition and Image Acquisition toolboxes. PMID:25784873

Brain responses to body image stimuli but not food are altered in women with bulimia nervosa

PubMed Central

2013-01-01

Background Research into the neural correlates of bulimia nervosa (BN) psychopathology remains limited. Methods In this functional magnetic resonance imaging study, 21 BN patients and 23 healthy controls (HCs) completed two paradigms: 1) processing of visual food stimuli and 2) comparing their own appearance with that of slim women. Participants also rated food craving and anxiety levels. Results Brain activation patterns in response to food cues did not differ between women with and without BN. However, when evaluating themselves against images of slim women, BN patients engaged the insula more and the fusiform gyrus less, compared to HCs, suggesting increased self-focus among women with BN whilst comparing themselves to a ‘slim ideal’. In these BN patients, exposure to food and body image stimuli increased self-reported levels of anxiety, but not craving. Conclusions Our findings suggest that women with BN differ from HCs in the way they process body image, but not in the way they process food stimuli. PMID:24238299

Optical and digital pattern recognition; Proceedings of the Meeting, Los Angeles, CA, Jan. 13-15, 1987

NASA Technical Reports Server (NTRS)

Liu, Hua-Kuang (Editor); Schenker, Paul (Editor)

1987-01-01

The papers presented in this volume provide an overview of current research in both optical and digital pattern recognition, with a theme of identifying overlapping research problems and methodologies. Topics discussed include image analysis and low-level vision, optical system design, object analysis and recognition, real-time hybrid architectures and algorithms, high-level image understanding, and optical matched filter design. Papers are presented on synthetic estimation filters for a control system; white-light correlator character recognition; optical AI architectures for intelligent sensors; interpreting aerial photographs by segmentation and search; and optical information processing using a new photopolymer.

Incoherent imaging of radar targets

NASA Astrophysics Data System (ADS)

van Ommen, A.; van der Spek, G. A.

1986-05-01

Theory suggests that, if a target can be modeled as a rigid constellation of point scatterers, the RCS pattern over a certain aspect change can be used to produce a one-dimensional image. The results for actual measured RCS patterns, however, are not promising. This is illustrated by processing on 4 s of echo data obtained from a Boeing 737 in straight flight, during which its aspect change is 2 deg. The conclusion might be that, for the application considered, aircraft cannot be modeled as a rigid constellation of point scatterers; this is partly due to the treatment of a three-dimensional target as a line target.

Progressive Recruitment of Mesenchymal Progenitors Reveals a Time-Dependent Process of Cell Fate Acquisition in Mouse and Human Nephrogenesis.

PubMed

Lindström, Nils O; De Sena Brandine, Guilherme; Tran, Tracy; Ransick, Andrew; Suh, Gio; Guo, Jinjin; Kim, Albert D; Parvez, Riana K; Ruffins, Seth W; Rutledge, Elisabeth A; Thornton, Matthew E; Grubbs, Brendan; McMahon, Jill A; Smith, Andrew D; McMahon, Andrew P

2018-06-04

Mammalian nephrons arise from a limited nephron progenitor pool through a reiterative inductive process extending over days (mouse) or weeks (human) of kidney development. Here, we present evidence that human nephron patterning reflects a time-dependent process of recruitment of mesenchymal progenitors into an epithelial nephron precursor. Progressive recruitment predicted from high-resolution image analysis and three-dimensional reconstruction of human nephrogenesis was confirmed through direct visualization and cell fate analysis of mouse kidney organ cultures. Single-cell RNA sequencing of the human nephrogenic niche provided molecular insights into these early patterning processes and predicted developmental trajectories adopted by nephron progenitor cells in forming segment-specific domains of the human nephron. The temporal-recruitment model for nephron polarity and patterning suggested by direct analysis of human kidney development provides a framework for integrating signaling pathways driving mammalian nephrogenesis. Copyright © 2018 Elsevier Inc. All rights reserved.

Artificial intelligence and signal processing for infrastructure assessment

NASA Astrophysics Data System (ADS)

Assaleh, Khaled; Shanableh, Tamer; Yehia, Sherif

2015-04-01

The Ground Penetrating Radar (GPR) is being recognized as an effective nondestructive evaluation technique to improve the inspection process. However, data interpretation and complexity of the results impose some limitations on the practicality of using this technique. This is mainly due to the need of a trained experienced person to interpret images obtained by the GPR system. In this paper, an algorithm to classify and assess the condition of infrastructures utilizing image processing and pattern recognition techniques is discussed. Features extracted form a dataset of images of defected and healthy slabs are used to train a computer vision based system while another dataset is used to evaluate the proposed algorithm. Initial results show that the proposed algorithm is able to detect the existence of defects with about 77% success rate.

Behavioral similarity measurement based on image processing for robots that use imitative learning

NASA Astrophysics Data System (ADS)

Sterpin B., Dante G.; Martinez S., Fernando; Jacinto G., Edwar

2017-02-01

In the field of the artificial societies, particularly those are based on memetics, imitative behavior is essential for the development of cultural evolution. Applying this concept for robotics, through imitative learning, a robot can acquire behavioral patterns from another robot. Assuming that the learning process must have an instructor and, at least, an apprentice, the fact to obtain a quantitative measurement for their behavioral similarity, would be potentially useful, especially in artificial social systems focused on cultural evolution. In this paper the motor behavior of both kinds of robots, for two simple tasks, is represented by 2D binary images, which are processed in order to measure their behavioral similarity. The results shown here were obtained comparing some similarity measurement methods for binary images.

Intra- and interspecific variation in tropical tree and liana phenology derived from Unmanned Aerial Vehicle images

NASA Astrophysics Data System (ADS)

Bohlman, S.; Park, J.; Muller-Landau, H. C.; Rifai, S. W.; Dandois, J. P.

2017-12-01

Phenology is a critical driver of ecosystem processes. There is strong evidence that phenology is shifting in temperate ecosystems in response to climate change, but tropical tree and liana phenology remains poorly quantified and understood. A key challenge is that tropical forests contain hundreds of plant species with a wide variety of phenological patterns. Satellite-based observations, an important source of phenology data in northern latitudes, are hindered by frequent cloud cover in the tropics. To quantify phenology over a large number of individuals and species, we collected bi-weekly images from unmanned aerial vehicles (UAVs) in the well-studied 50-ha forest inventory plot on Barro Colorado Island, Panama. Between October 2014 and December 2015 and again in May 2015, we collected a total of 35 sets of UAV images, each with continuous coverage of the 50-ha plot, where every tree ≥ 1 cm DBH is mapped. Spectral, texture, and image information was extracted from the UAV images for individual tree crowns, which was then used as inputs for a machine learning algorithm to predict percent leaf and branch cover. We obtained the species identities of 2000 crowns in the images via field mapping. The objectives of this study are to (1) determined if machine learning algorithms, applied to UAV images, can effectively quantify changes in leaf cover, which we term "deciduousness; (2) determine how liana cover effects deciduousness and (3) test how well UAV-derived deciduousness patterns match satellite-derived temporal patterns. Machine learning algorithms trained on a variety of image parameters could effectively determine leaf cover, despite variation in lighting and viewing angles. Crowns with higher liana cover have less overall deciduousness (tree + liana together) than crowns with lower liana cover. Individual crown deciduousness, summed over all crowns measured in the 50-ha plot, showed a similar seasonal pattern as MODIS EVI composited over 10 years. However, MODIS EVI phenology was "greened" up earlier than UAV-based deciduousness, perhaps reflecting the new late dry season leaf flush that increases EVI but not overall leaf cover. We discuss how the potential mechanisms that explain variation among species and between trees and lianas and the consequences for these variation for ecosystem processes and modeling.

Development of inorganic resists for electron beam lithography: Novel materials and simulations

NASA Astrophysics Data System (ADS)

Jeyakumar, Augustin

Electron beam lithography is gaining widespread utilization as the semiconductor industry progresses towards both advanced optical and non-optical lithographic technologies for high resolution patterning. The current resist technologies are based on organic systems that are imaged most commonly through chain scission, networking, or a chemically amplified polarity change in the material. Alternative resists based on inorganic systems were developed and characterized in this research for high resolution electron beam lithography and their interactions with incident electrons were investigated using Monte Carlo simulations. A novel inorganic resist imaging scheme was developed using metal-organic precursors which decompose to form metal oxides upon electron beam irradiation that can serve as inorganic hard masks for hybrid bilayer inorganic-organic imaging systems and also as directly patternable high resolution metal oxide structures. The electron beam imaging properties of these metal-organic materials were correlated to the precursor structure by studying effects such as interactions between high atomic number species and the incident electrons. Optimal single and multicomponent precursors were designed for utilization as viable inorganic resist materials for sub-50nm patterning in electron beam lithography. The electron beam imaging characteristics of the most widely used inorganic resist material, hydrogen silsesquioxane (HSQ), was also enhanced using a dual processing imaging approach with thermal curing as well as a sensitizer catalyzed imaging approach. The interaction between incident electrons and the high atomic number species contained in these inorganic resists was also studied using Monte Carlo simulations. The resolution attainable using inorganic systems as compared to organic systems can be greater for accelerating voltages greater than 50 keV due to minimized lateral scattering in the high density inorganic systems. The effects of loading nanoparticles in an electron beam resist was also investigated using a newly developed hybrid Monte Carlo approach that accounts for multiple components in a solid film. The resolution of the nanocomposite resist process was found to degrade with increasing nanoparticle loading. Finally, the electron beam patterning of self-assembled monolayers, which were found to primarily utilize backscattered electrons from the high atomic number substrate materials to form images, was also investigated and characterized. It was found that backscattered electrons limit the resolution attainable at low incident electron energies.

Improvement of resist profile roughness in bilayer resist process

NASA Astrophysics Data System (ADS)

Jeong, Chang-Young; Ryu, Sang-Wook; Park, Ki-Yeop; Lee, Won-Kyu; Lee, Seung-Woog; Lee, Dai-Hoon

2000-06-01

The bi-layer resist (BLR) process, which first accomplish imaging on a thin top layer and transfer it down to a thick organic layer, is one of newly emerging patterning techniques in silicon processing. In this work, we studied the lithographic performance of the BLR process adopting FK- SPTM (Fujifilm Olin Co.) as top layer material and various organic material as bottom layer. Generally, considerable advantages of planarization, reduced substrate reflection, improved process latitude, and of enhanced resolution are achieved. However, the resolution and the process latitude are highly affected by surface interaction between the top resist and the bottom material. Moreover, the BLR process has a sidewall roughness problem related to the material factors of the resist and the degraded aerial image contrast, which can affect the reliability of the device. We found that thermal curing treatment applied after development with the consideration of the glass transition temperature are very effective in reducing the line edge roughness. More smooth and steep patterning is achieved by the thermal treatment. The linewidth controllability is below 10 nm and the k1 value is reduced from 0.5 down to 0.32 in this process. The reactive ion etching adopting O2 gas demonstrated selectivity of the top resist over bottom material more than 15:1, together with residue-free and vertical wall profile.

Mirror-Image Equivalence and Interhemispheric Mirror-Image Reversal

PubMed Central

Corballis, Michael C.

2018-01-01

Mirror-image confusions are common, especially in children and in some cases of neurological impairment. They can be a special impediment in activities such as reading and writing directional scripts, where mirror-image patterns (such as b and d) must be distinguished. Treating mirror images as equivalent, though, can also be adaptive in the natural world, which carries no systematic left-right bias and where the same object or event can appear in opposite viewpoints. Mirror-image equivalence and confusion are natural consequences of a bilaterally symmetrical brain. In the course of learning, mirror-image equivalence may be established through a process of symmetrization, achieved through homotopic interhemispheric exchange in the formation of memory circuits. Such circuits would not distinguish between mirror images. Learning to discriminate mirror-image discriminations may depend either on existing brain asymmetries, or on extensive learning overriding the symmetrization process. The balance between mirror-image equivalence and mirror-image discrimination may nevertheless be precarious, with spontaneous confusions or reversals, such as mirror writing, sometimes appearing naturally or as a manifestation of conditions like dyslexia. PMID:29706878

Mirror-Image Equivalence and Interhemispheric Mirror-Image Reversal.

PubMed

Corballis, Michael C

2018-01-01

Mirror-image confusions are common, especially in children and in some cases of neurological impairment. They can be a special impediment in activities such as reading and writing directional scripts, where mirror-image patterns (such as b and d ) must be distinguished. Treating mirror images as equivalent, though, can also be adaptive in the natural world, which carries no systematic left-right bias and where the same object or event can appear in opposite viewpoints. Mirror-image equivalence and confusion are natural consequences of a bilaterally symmetrical brain. In the course of learning, mirror-image equivalence may be established through a process of symmetrization, achieved through homotopic interhemispheric exchange in the formation of memory circuits. Such circuits would not distinguish between mirror images. Learning to discriminate mirror-image discriminations may depend either on existing brain asymmetries, or on extensive learning overriding the symmetrization process. The balance between mirror-image equivalence and mirror-image discrimination may nevertheless be precarious, with spontaneous confusions or reversals, such as mirror writing, sometimes appearing naturally or as a manifestation of conditions like dyslexia.

Associative Pattern Recognition In Analog VLSI Circuits

NASA Technical Reports Server (NTRS)

Tawel, Raoul

1995-01-01

Winner-take-all circuit selects best-match stored pattern. Prototype cascadable very-large-scale integrated (VLSI) circuit chips built and tested to demonstrate concept of electronic associative pattern recognition. Based on low-power, sub-threshold analog complementary oxide/semiconductor (CMOS) VLSI circuitry, each chip can store 128 sets (vectors) of 16 analog values (vector components), vectors representing known patterns as diverse as spectra, histograms, graphs, or brightnesses of pixels in images. Chips exploit parallel nature of vector quantization architecture to implement highly parallel processing in relatively simple computational cells. Through collective action, cells classify input pattern in fraction of microsecond while consuming power of few microwatts.

Scale dependency of forest functional diversity assessed using imaging spectroscopy and airborne laser scanning

NASA Astrophysics Data System (ADS)

Schneider, F. D.; Morsdorf, F.; Schmid, B.; Petchey, O. L.; Hueni, A.; Schimel, D.; Schaepman, M. E.

2016-12-01

Forest functional traits offer a mechanistic link between ecological processes and community structure and assembly rules. However, measuring functional traits of forests in a continuous and consistent way is particularly difficult due to the complexity of in-situ measurements and geo-referencing. New imaging spectroscopy measurements overcome these limitations allowing to map physiological traits on broad spatial scales. We mapped leaf chlorophyll, carotenoids and leaf water content over 900 ha of temperate mixed forest (Fig. 1a). The selected traits are functionally important because they are indicating the photosynthetic potential of trees, leaf longevity and protection, as well as tree water and drought stress. Spatially continuous measurements on the scale of individual tree crowns allowed to assess functional diversity patterns on a range of ecological extents. We used indexes of functional richness, divergence and evenness to map different aspects of diversity. Fig. 1b shows an example of physiological richness at an extent of 240 m radius. We compared physiological to morphological diversity patterns, derived based on plant area index, canopy height and foliage height diversity. Our results show that patterns of physiological and morphological diversity generally agree, independently measured by airborne imaging spectroscopy and airborne laser scanning, respectively. The occurrence of disturbance areas and mixtures of broadleaf and needle trees were the main drivers of the observed diversity patterns. Spatial patterns at varying extents and richness-area relationships indicated that environmental filtering is the predominant community assembly process. Our results demonstrate the potential for mapping physiological and morphological diversity in a temperate mixed forest between and within species on scales relevant to study community assembly and structure from space and test the corresponding measurement schemes.

MRI findings in eastern equine encephalitis: the "parenthesis" sign.

PubMed

Nickerson, Joshua P; Kannabiran, Suma; Burbank, Heather N

2016-01-01

Two patients with eastern equine encephalitis (EEE) presented to a tertiary referral center. Both subjects' brain magnetic resonance imaging showed T2/FLAIR (fluid-attenuated inversion recovery) hyperintensities including linear areas of hyperintensity in the external and internal capsules with sparing of the lentiform nuclei. Single case reports of imaging findings in EEE exist with nonspecific patterns of abnormality. We propose that this "( ) parentheses sign" on T2 or FLAIR imaging may distinguish EEE from other processes. Copyright © 2015 Elsevier Inc. All rights reserved.

Optical computing.

NASA Technical Reports Server (NTRS)

Stroke, G. W.

1972-01-01

Applications of the optical computer include an approach for increasing the sharpness of images obtained from the most powerful electron microscopes and fingerprint/credit card identification. The information-handling capability of the various optical computing processes is very great. Modern synthetic-aperture radars scan upward of 100,000 resolvable elements per second. Fields which have assumed major importance on the basis of optical computing principles are optical image deblurring, coherent side-looking synthetic-aperture radar, and correlative pattern recognition. Some examples of the most dramatic image deblurring results are shown.

Adaptive Texture Synthesis for Large Scale City Modeling

NASA Astrophysics Data System (ADS)

Despine, G.; Colleu, T.

2015-02-01

Large scale city models textured with aerial images are well suited for bird-eye navigation but generally the image resolution does not allow pedestrian navigation. One solution to face this problem is to use high resolution terrestrial photos but it requires huge amount of manual work to remove occlusions. Another solution is to synthesize generic textures with a set of procedural rules and elementary patterns like bricks, roof tiles, doors and windows. This solution may give realistic textures but with no correlation to the ground truth. Instead of using pure procedural modelling we present a method to extract information from aerial images and adapt the texture synthesis to each building. We describe a workflow allowing the user to drive the information extraction and to select the appropriate texture patterns. We also emphasize the importance to organize the knowledge about elementary pattern in a texture catalogue allowing attaching physical information, semantic attributes and to execute selection requests. Roofs are processed according to the detected building material. Façades are first described in terms of principal colours, then opening positions are detected and some window features are computed. These features allow selecting the most appropriate patterns from the texture catalogue. We experimented this workflow on two samples with 20 cm and 5 cm resolution images. The roof texture synthesis and opening detection were successfully conducted on hundreds of buildings. The window characterization is still sensitive to the distortions inherent to the projection of aerial images onto the facades.

Art, outreach and geopattern formation

NASA Astrophysics Data System (ADS)

Morris, S. W.; Chen, A. S. H.; Rogers, M. C.; Goehring, L.

2014-12-01

For the past several years, I have been exhibiting images and videos of natural and laboratory geopatterns in art galleries and outdoor shows. I have also brought artists into my research lab for hands-on workshops. My experience shows that scientific images can be well received as art and generate wide-ranging discussions across traditionally separate disciplines. The art world offers an interesting new venue for outreach activities, as well as being a lot of fun to explore. Artists Statement:I am interested in self-organized, emergent patterns and textures. I take photos of patterns both from the natural world and of experiments in my laboratory in the department of Physics at the University of Toronto. Patterns naturally attract casual attention but are also the subject of serious scientific research. Some things just evolve all by themselves into strikingly regular shapes and textures. Why? These shapes emerge spontaneously from a dynamic process of growing, folding, cracking, wrinkling, branching, flowing and other kinds of morphological development. My photos are informed by the scientific aesthetic of nonlinear physics, and mathematics lurks behind every image for those who know where to look for it. But no special knowledge is required to appreciate the results. Each image shows an object, sometimes quite small and often familiar, with a self-composed regular structure. Some images are from laboratory physics experiments and some are from Nature, and all celebrate the subtle interplay of order and complexity in emergent patterns.

Co-optimization of lithographic and patterning processes for improved EPE performance

NASA Astrophysics Data System (ADS)

Maslow, Mark J.; Timoshkov, Vadim; Kiers, Ton; Jee, Tae Kwon; de Loijer, Peter; Morikita, Shinya; Demand, Marc; Metz, Andrew W.; Okada, Soichiro; Kumar, Kaushik A.; Biesemans, Serge; Yaegashi, Hidetami; Di Lorenzo, Paolo; Bekaert, Joost P.; Mao, Ming; Beral, Christophe; Larivière, Stephane

2017-03-01

Complimentary lithography is already being used for advanced logic patterns. The tight pitches for 1D Metal layers are expected to be created using spacer based multiple patterning ArF-i exposures and the more complex cut/block patterns are made using EUV exposures. At the same time, control requirements of CDU, pattern shift and pitch-walk are approaching sub-nanometer levels to meet edge placement error (EPE) requirements. Local variability, such as Line Edge Roughness (LER), Local CDU, and Local Placement Error (LPE), are dominant factors in the total Edge Placement error budget. In the lithography process, improving the imaging contrast when printing the core pattern has been shown to improve the local variability. In the etch process, it has been shown that the fusion of atomic level etching and deposition can also improve these local variations. Co-optimization of lithography and etch processing is expected to further improve the performance over individual optimizations alone. To meet the scaling requirements and keep process complexity to a minimum, EUV is increasingly seen as the platform for delivering the exposures for both the grating and the cut/block patterns beyond N7. In this work, we evaluated the overlay and pattern fidelity of an EUV block printed in a negative tone resist on an ArF-i SAQP grating. High-order Overlay modeling and corrections during the exposure can reduce overlay error after development, a significant component of the total EPE. During etch, additional degrees of freedom are available to improve the pattern placement error in single layer processes. Process control of advanced pitch nanoscale-multi-patterning techniques as described above is exceedingly complicated in a high volume manufacturing environment. Incorporating potential patterning optimizations into both design and HVM controls for the lithography process is expected to bring a combined benefit over individual optimizations. In this work we will show the EPE performance improvement for a 32nm pitch SAQP + block patterned Metal 2 layer by cooptimizing the lithography and etch processes. Recommendations for further improvements and alternative processes will be given.

Patterning of Spiral Structure on Optical Fiber by Focused-Ion-Beam Etching

NASA Astrophysics Data System (ADS)

Mekaru, Harutaka; Yano, Takayuki

2012-06-01

We produce patterns on minute and curved surfaces of optical fibers, and develop a processing technology for fabricating sensors, antennas, electrical circuits, and other devices on such patterned surfaces by metallization. A three-dimensional processing technology can be used to fabricate a spiral coil on the surface of cylindrical quartz materials, and then the microcoils can also be applied to capillaries of micro-fluid devices, as well as to receiver coils connected to a catheter and an endoscope of nuclear magnetic resonance imaging (MRI) systems used in imaging blood vessels. To create a spiral line pattern with a small linewidth on a full-circumference surface of an optical fiber, focused-ion-beam (FIB) etching was employed. Here, a simple rotation stage comprising a dc motor and an LR3 battery was built. However, during the development of a prototype rotation stage before finalizing a large-scale remodelling of our FIB etching system, a technical problem was encountered where a spiral line could not be processed without running into breaks and notches in the features. It turned out that the problem was caused by axis blur resulting from an eccentric spinning (or wobbling) of the axis of the fiber caused by its unrestrained free end. The problem was solved by installing a rotation guide and an axis suppression device onto the rotation stage. Using this improved rotation stage. we succeeded in the seamless patterning of 1-µm-wide features on the full-circumference surface of a 250-µm-diameter quartz optical fiber (QOF) by FIB etching.

Advances in molecular labeling, high throughput imaging and machine intelligence portend powerful functional cellular biochemistry tools.

PubMed

Price, Jeffrey H; Goodacre, Angela; Hahn, Klaus; Hodgson, Louis; Hunter, Edward A; Krajewski, Stanislaw; Murphy, Robert F; Rabinovich, Andrew; Reed, John C; Heynen, Susanne

2002-01-01

Cellular behavior is complex. Successfully understanding systems at ever-increasing complexity is fundamental to advances in modern science and unraveling the functional details of cellular behavior is no exception. We present a collection of prospectives to provide a glimpse of the techniques that will aid in collecting, managing and utilizing information on complex cellular processes via molecular imaging tools. These include: 1) visualizing intracellular protein activity with fluorescent markers, 2) high throughput (and automated) imaging of multilabeled cells in statistically significant numbers, and 3) machine intelligence to analyze subcellular image localization and pattern. Although not addressed here, the importance of combining cell-image-based information with detailed molecular structure and ligand-receptor binding models cannot be overlooked. Advanced molecular imaging techniques have the potential to impact cellular diagnostics for cancer screening, clinical correlations of tissue molecular patterns for cancer biology, and cellular molecular interactions for accelerating drug discovery. The goal of finally understanding all cellular components and behaviors will be achieved by advances in both instrumentation engineering (software and hardware) and molecular biochemistry. Copyright 2002 Wiley-Liss, Inc.

Controlled power delivery for super-resolution imaging of biological samples using digital micromirror device

NASA Astrophysics Data System (ADS)

Valiya Peedikakkal, Liyana; Cadby, Ashley

2017-02-01

Localization based super resolution images of a biological sample is generally achieved by using high power laser illumination with long exposure time which unfortunately increases photo-toxicity of a sample, making super resolution microscopy, in general, incompatible with live cell imaging. Furthermore, the limitation of photobleaching reduces the ability to acquire time lapse images of live biological cells using fluorescence microscopy. Digital Light Processing (DLP) technology can deliver light at grey scale levels by flickering digital micromirrors at around 290 Hz enabling highly controlled power delivery to samples. In this work, Digital Micromirror Device (DMD) is implemented in an inverse Schiefspiegler telescope setup to control the power and pattern of illumination for super resolution microscopy. We can achieve spatial and temporal patterning of illumination by controlling the DMD pixel by pixel. The DMD allows us to control the power and spatial extent of the laser illumination. We have used this to show that we can reduce the power delivered to the sample to allow for longer time imaging in one area while achieving sub-diffraction STORM imaging in another using higher power densities.

Land classification of south-central Iowa from computer enhanced images

NASA Technical Reports Server (NTRS)

Lucas, J. R.; Taranik, J. V.; Billingsley, F. C. (Principal Investigator)

1977-01-01

The author has identified the following significant results. Enhanced LANDSAT imagery was most useful for land classification purposes, because these images could be photographically printed at large scales such as 1:63,360. The ability to see individual picture elements was no hindrance as long as general image patterns could be discerned. Low cost photographic processing systems for color printings have proved to be effective in the utilization of computer enhanced LANDSAT products for land classification purposes. The initial investment for this type of system was very low, ranging from $100 to $200 beyond a black and white photo lab. The technical expertise can be acquired from reading a color printing and processing manual.

Spatio-spectral color filter array design for optimal image recovery.

PubMed

Hirakawa, Keigo; Wolfe, Patrick J

2008-10-01

In digital imaging applications, data are typically obtained via a spatial subsampling procedure implemented as a color filter array-a physical construction whereby only a single color value is measured at each pixel location. Owing to the growing ubiquity of color imaging and display devices, much recent work has focused on the implications of such arrays for subsequent digital processing, including in particular the canonical demosaicking task of reconstructing a full color image from spatially subsampled and incomplete color data acquired under a particular choice of array pattern. In contrast to the majority of the demosaicking literature, we consider here the problem of color filter array design and its implications for spatial reconstruction quality. We pose this problem formally as one of simultaneously maximizing the spectral radii of luminance and chrominance channels subject to perfect reconstruction, and-after proving sub-optimality of a wide class of existing array patterns-provide a constructive method for its solution that yields robust, new panchromatic designs implementable as subtractive colors. Empirical evaluations on multiple color image test sets support our theoretical results, and indicate the potential of these patterns to increase spatial resolution for fixed sensor size, and to contribute to improved reconstruction fidelity as well as significantly reduced hardware complexity.

Flightspeed Integral Image Analysis Toolkit

NASA Technical Reports Server (NTRS)

Thompson, David R.

2009-01-01

The Flightspeed Integral Image Analysis Toolkit (FIIAT) is a C library that provides image analysis functions in a single, portable package. It provides basic low-level filtering, texture analysis, and subwindow descriptor for applications dealing with image interpretation and object recognition. Designed with spaceflight in mind, it addresses: Ease of integration (minimal external dependencies) Fast, real-time operation using integer arithmetic where possible (useful for platforms lacking a dedicated floatingpoint processor) Written entirely in C (easily modified) Mostly static memory allocation 8-bit image data The basic goal of the FIIAT library is to compute meaningful numerical descriptors for images or rectangular image regions. These n-vectors can then be used directly for novelty detection or pattern recognition, or as a feature space for higher-level pattern recognition tasks. The library provides routines for leveraging training data to derive descriptors that are most useful for a specific data set. Its runtime algorithms exploit a structure known as the "integral image." This is a caching method that permits fast summation of values within rectangular regions of an image. This integral frame facilitates a wide range of fast image-processing functions. This toolkit has applicability to a wide range of autonomous image analysis tasks in the space-flight domain, including novelty detection, object and scene classification, target detection for autonomous instrument placement, and science analysis of geomorphology. It makes real-time texture and pattern recognition possible for platforms with severe computational restraints. The software provides an order of magnitude speed increase over alternative software libraries currently in use by the research community. FIIAT can commercially support intelligent video cameras used in intelligent surveillance. It is also useful for object recognition by robots or other autonomous vehicles

Sensor feature fusion for detecting buried objects

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

Clark, G.A.; Sengupta, S.K.; Sherwood, R.J.

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 amore » 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.« less

Diagnosis of Tempromandibular Disorders Using Local Binary Patterns.

PubMed

Haghnegahdar, A A; Kolahi, S; Khojastepour, L; Tajeripour, F

2018-03-01

Temporomandibular joint disorder (TMD) might be manifested as structural changes in bone through modification, adaptation or direct destruction. We propose to use Local Binary Pattern (LBP) characteristics and histogram-oriented gradients on the recorded images as a diagnostic tool in TMD assessment. CBCT images of 66 patients (132 joints) with TMD and 66 normal cases (132 joints) were collected and 2 coronal cut prepared from each condyle, although images were limited to head of mandibular condyle. In order to extract features of images, first we use LBP and then histogram of oriented gradients. To reduce dimensionality, the linear algebra Singular Value Decomposition (SVD) is applied to the feature vectors matrix of all images. For evaluation, we used K nearest neighbor (K-NN), Support Vector Machine, Naïve Bayesian and Random Forest classifiers. We used Receiver Operating Characteristic (ROC) to evaluate the hypothesis. K nearest neighbor classifier achieves a very good accuracy (0.9242), moreover, it has desirable sensitivity (0.9470) and specificity (0.9015) results, when other classifiers have lower accuracy, sensitivity and specificity. We proposed a fully automatic approach to detect TMD using image processing techniques based on local binary patterns and feature extraction. K-NN has been the best classifier for our experiments in detecting patients from healthy individuals, by 92.42% accuracy, 94.70% sensitivity and 90.15% specificity. The proposed method can help automatically diagnose TMD at its initial stages.

Cell-free protein synthesis and assembly on a biochip

NASA Astrophysics Data System (ADS)

Heyman, Yael; Buxboim, Amnon; Wolf, Sharon G.; Daube, Shirley S.; Bar-Ziv, Roy H.

2012-06-01

Biologically active complexes such as ribosomes and bacteriophages are formed through the self-assembly of proteins and nucleic acids. Recapitulating these biological self-assembly processes in a cell-free environment offers a way to develop synthetic biodevices. To visualize and understand the assembly process, a platform is required that enables simultaneous synthesis, assembly and imaging at the nanoscale. Here, we show that a silicon dioxide grid, used to support samples in transmission electron microscopy, can be modified into a biochip to combine in situ protein synthesis, assembly and imaging. Light is used to pattern the biochip surface with genes that encode specific proteins, and antibody traps that bind and assemble the nascent proteins. Using transmission electron microscopy imaging we show that protein nanotubes synthesized on the biochip surface in the presence of antibody traps efficiently assembled on these traps, but pre-assembled nanotubes were not effectively captured. Moreover, synthesis of green fluorescent protein from its immobilized gene generated a gradient of captured proteins decreasing in concentration away from the gene source. This biochip could be used to create spatial patterns of proteins assembled on surfaces.

Image pattern recognition supporting interactive analysis and graphical visualization

NASA Technical Reports Server (NTRS)

Coggins, James M.

1992-01-01

Image Pattern Recognition attempts to infer properties of the world from image data. Such capabilities are crucial for making measurements from satellite or telescope images related to Earth and space science problems. Such measurements can be the required product itself, or the measurements can be used as input to a computer graphics system for visualization purposes. At present, the field of image pattern recognition lacks a unified scientific structure for developing and evaluating image pattern recognition applications. The overall goal of this project is to begin developing such a structure. This report summarizes results of a 3-year research effort in image pattern recognition addressing the following three principal aims: (1) to create a software foundation for the research and identify image pattern recognition problems in Earth and space science; (2) to develop image measurement operations based on Artificial Visual Systems; and (3) to develop multiscale image descriptions for use in interactive image analysis.

Cryo-imaging of fluorescently labeled single cells in a mouse

NASA Astrophysics Data System (ADS)

Steyer, Grant J.; Roy, Debashish; Salvado, Olivier; Stone, Meredith E.; Wilson, David L.

2009-02-01

We developed a cryo-imaging system to provide single-cell detection of fluorescently labeled cells in mouse, with particular applicability to stem cells and metastatic cancer. The Case cryoimaging system consists of a fluorescence microscope, robotic imaging positioner, customized cryostat, PC-based control system, and visualization/analysis software. The system alternates between sectioning (10-40 μm) and imaging, collecting color brightfield and fluorescent blockface image volumes >60GB. In mouse experiments, we imaged quantum-dot labeled stem cells, GFP-labeled cancer and stem cells, and cell-size fluorescent microspheres. To remove subsurface fluorescence, we used a simplified model of light-tissue interaction whereby the next image was scaled, blurred, and subtracted from the current image. We estimated scaling and blurring parameters by minimizing entropy of subtracted images. Tissue specific attenuation parameters were found [uT : heart (267 +/- 47.6 μm), liver (218 +/- 27.1 μm), brain (161 +/- 27.4 μm)] to be within the range of estimates in the literature. "Next image" processing removed subsurface fluorescence equally well across multiple tissues (brain, kidney, liver, adipose tissue, etc.), and analysis of 200 microsphere images in the brain gave 97+/-2% reduction of subsurface fluorescence. Fluorescent signals were determined to arise from single cells based upon geometric and integrated intensity measurements. Next image processing greatly improved axial resolution, enabled high quality 3D volume renderings, and improved enumeration of single cells with connected component analysis by up to 24%. Analysis of image volumes identified metastatic cancer sites, found homing of stem cells to injury sites, and showed microsphere distribution correlated with blood flow patterns. We developed and evaluated cryo-imaging to provide single-cell detection of fluorescently labeled cells in mouse. Our cryo-imaging system provides extreme (>60GB), micron-scale, fluorescence, and bright field image data. Here we describe our image preprocessing, analysis, and visualization techniques. Processing improves axial resolution, reduces subsurface fluorescence by 97%, and enables single cell detection and counting. High quality 3D volume renderings enable us to evaluate cell distribution patterns. Applications include the myriad of biomedical experiments using fluorescent reporter gene and exogenous fluorophore labeling of cells in applications such as stem cell regenerative medicine, cancer, tissue engineering, etc.

Real-time polarization imaging algorithm for camera-based polarization navigation sensors.

PubMed

Lu, Hao; Zhao, Kaichun; You, Zheng; Huang, Kaoli

2017-04-10

Biologically inspired polarization navigation is a promising approach due to its autonomous nature, high precision, and robustness. Many researchers have built point source-based and camera-based polarization navigation prototypes in recent years. Camera-based prototypes can benefit from their high spatial resolution but incur a heavy computation load. The pattern recognition algorithm in most polarization imaging algorithms involves several nonlinear calculations that impose a significant computation burden. In this paper, the polarization imaging and pattern recognition algorithms are optimized through reduction to several linear calculations by exploiting the orthogonality of the Stokes parameters without affecting precision according to the features of the solar meridian and the patterns of the polarized skylight. The algorithm contains a pattern recognition algorithm with a Hough transform as well as orientation measurement algorithms. The algorithm was loaded and run on a digital signal processing system to test its computational complexity. The test showed that the running time decreased to several tens of milliseconds from several thousand milliseconds. Through simulations and experiments, it was found that the algorithm can measure orientation without reducing precision. It can hence satisfy the practical demands of low computational load and high precision for use in embedded systems.

Detecting spatial defects in colored patterns using self-oscillating gels

NASA Astrophysics Data System (ADS)

Fang, Yan; Yashin, Victor V.; Dickerson, Samuel J.; Balazs, Anna C.

2018-06-01

With the growing demand for wearable computers, there is a need for material systems that can perform computational tasks without relying on external electrical power. Using theory and simulation, we design a material system that "computes" by integrating the inherent behavior of self-oscillating gels undergoing the Belousov-Zhabotinsky (BZ) reaction and piezoelectric (PZ) plates. These "BZ-PZ" units are connected electrically to form a coupled oscillator network, which displays specific modes of synchronization. We exploit this attribute in employing multiple BZ-PZ networks to perform pattern matching on complex multi-dimensional data, such as colored images. By decomposing a colored image into sets of binary vectors, we use each BZ-PZ network, or "channel," to store distinct information about the color and the shape of the image and perform the pattern matching operation. Our simulation results indicate that the multi-channel BZ-PZ device can detect subtle differences between the input and stored patterns, such as the color variation of one pixel or a small change in the shape of an object. To demonstrate a practical application, we utilize our system to process a colored Quick Response code and show its potential in cryptography and steganography.

GUIDOS: tools for the assessment of pattern, connectivity, and fragmentation

NASA Astrophysics Data System (ADS)

Vogt, Peter

2013-04-01

Pattern, connectivity, and fragmentation can be considered as pillars for a quantitative analysis of digital landscape images. The free software toolbox GUIDOS (http://forest.jrc.ec.europa.eu/download/software/guidos) includes a variety of dedicated methodologies for the quantitative assessment of these features. Amongst others, Morphological Spatial Pattern Analysis (MSPA) is used for an intuitive description of image pattern structures and the automatic detection of connectivity pathways. GUIDOS includes tools for the detection and quantitative assessment of key nodes and links as well as to define connectedness in raster images and to setup appropriate input files for an enhanced network analysis using Conefor Sensinode. Finally, fragmentation is usually defined from a species point of view but a generic and quantifiable indicator is needed to measure fragmentation and its changes. Some preliminary results for different conceptual approaches will be shown for a sample dataset. Complemented by pre- and post-processing routines and a complete GIS environment the portable GUIDOS Toolbox may facilitate a holistic assessment in risk assessment studies, landscape planning, and conservation/restoration policies. Alternatively, individual analysis components may contribute to or enhance studies conducted with other software packages in landscape ecology.

Rotation Covariant Image Processing for Biomedical Applications

PubMed Central

Reisert, Marco

2013-01-01

With the advent of novel biomedical 3D image acquisition techniques, the efficient and reliable analysis of volumetric images has become more and more important. The amount of data is enormous and demands an automated processing. The applications are manifold, ranging from image enhancement, image reconstruction, and image description to object/feature detection and high-level contextual feature extraction. In most scenarios, it is expected that geometric transformations alter the output in a mathematically well-defined manner. In this paper we emphasis on 3D translations and rotations. Many algorithms rely on intensity or low-order tensorial-like descriptions to fulfill this demand. This paper proposes a general mathematical framework based on mathematical concepts and theories transferred from mathematical physics and harmonic analysis into the domain of image analysis and pattern recognition. Based on two basic operations, spherical tensor differentiation and spherical tensor multiplication, we show how to design a variety of 3D image processing methods in an efficient way. The framework has already been applied to several biomedical applications ranging from feature and object detection tasks to image enhancement and image restoration techniques. In this paper, the proposed methods are applied on a variety of different 3D data modalities stemming from medical and biological sciences. PMID:23710255

Calibrated Multi-Temporal Edge Images for City Infrastructure Growth Assessment and Prediction

NASA Astrophysics Data System (ADS)

Al-Ruzouq, R.; Shanableh, A.; Boharoon, Z.; Khalil, M.

2018-03-01

Urban Growth or urbanization can be defined as the gradual process of city's population growth and infrastructure development. It is typically demonstrated by the expansion of a city's infrastructure, mainly development of its roads and buildings. Uncontrolled urban Growth in cities has been responsible for several problems that include living environment, drinking water, noise and air pollution, waste management, traffic congestion and hydraulic processes. Accurate identification of urban growth is of great importance for urban planning and water/land management. Recent advances in satellite imagery, in terms of improved spatial and temporal resolutions, allows for efficient identification of change patterns and the prediction of built-up areas. In this study, two approaches were adapted to quantify and assess the pattern of urbanization, in Ajman City at UAE, during the last three decades. The first approach relies on image processing techniques and multi-temporal Landsat satellite images with ground resolution varying between 15 to 60 meters. In this approach, the derived edge images (roads and buildings) were used as the basis of change detection. The second approach relies on digitizing features from high-resolution images captured at different years. The latest approach was adopted, as a reference and ground truth, to calibrate extracted edges from Landsat images. It has been found that urbanized area almost increased by 12 folds during the period 1975-2015 where the growth of buildings and roads were almost parallel until 2005 when the roads spatial expansion witnessed a steep increase due to the vertical expansion of the City. Extracted Edges features, were successfully used for change detection and quantification in term of buildings and roads.

Riding the Right Wavelet: Quantifying Scale Transitions in Fractured Rocks

NASA Astrophysics Data System (ADS)

Rizzo, Roberto E.; Healy, David; Farrell, Natalie J.; Heap, Michael J.

2017-12-01

The mechanics of brittle failure is a well-described multiscale process that involves a rapid transition from distributed microcracks to localization along a single macroscopic rupture plane. However, considerable uncertainty exists regarding both the length scale at which this transition occurs and the underlying causes that prompt this shift from a distributed to a localized assemblage of cracks or fractures. For the first time, we used an image analysis tool developed to investigate orientation changes at different scales in images of fracture patterns in faulted materials, based on a two-dimensional continuous wavelet analysis. We detected the abrupt change in the fracture pattern from distributed tensile microcracks to localized shear failure in a fracture network produced by triaxial deformation of a sandstone core plug. The presented method will contribute to our ability of unraveling the physical processes at the base of catastrophic rock failure, including the nucleation of earthquakes, landslides, and volcanic eruptions.

Pattern recognition of concrete surface cracks and defects using integrated image processing algorithms

NASA Astrophysics Data System (ADS)

Balbin, Jessie R.; Hortinela, Carlos C.; Garcia, Ramon G.; Baylon, Sunnycille; Ignacio, Alexander Joshua; Rivera, Marco Antonio; Sebastian, Jaimie

2017-06-01

Pattern recognition of concrete surface crack defects is very important in determining stability of structure like building, roads or bridges. Surface crack is one of the subjects in inspection, diagnosis, and maintenance as well as life prediction for the safety of the structures. Traditionally determining defects and cracks on concrete surfaces are done manually by inspection. Moreover, any internal defects on the concrete would require destructive testing for detection. The researchers created an automated surface crack detection for concrete using image processing techniques including Hough transform, LoG weighted, Dilation, Grayscale, Canny Edge Detection and Haar Wavelet Transform. An automatic surface crack detection robot is designed to capture the concrete surface by sectoring method. Surface crack classification was done with the use of Haar trained cascade object detector that uses both positive samples and negative samples which proved that it is possible to effectively identify the surface crack defects.

Holography and optical information processing; Proceedings of the Soviet-Chinese Joint Seminar, Bishkek, Kyrgyzstan, Sept. 21-26, 1991

NASA Astrophysics Data System (ADS)

Mikaelian, Andrei L.

Attention is given to data storage, devices, architectures, and implementations of optical memory and neural networks; holographic optical elements and computer-generated holograms; holographic display and materials; systems, pattern recognition, interferometry, and applications in optical information processing; and special measurements and devices. Topics discussed include optical immersion as a new way to increase information recording density, systems for data reading from optical disks on the basis of diffractive lenses, a new real-time optical associative memory system, an optical pattern recognition system based on a WTA model of neural networks, phase diffraction grating for the integral transforms of coherent light fields, holographic recording with operated sensitivity and stability in chalcogenide glass layers, a compact optical logic processor, a hybrid optical system for computing invariant moments of images, optical fiber holographic inteferometry, and image transmission through random media in single pass via optical phase conjugation.

Multimodality imaging and state-of-art GPU technology in discriminating benign from malignant breast lesions on real time decision support system

NASA Astrophysics Data System (ADS)

Kostopoulos, S.; Sidiropoulos, K.; Glotsos, D.; Dimitropoulos, N.; Kalatzis, I.; Asvestas, P.; Cavouras, D.

2014-03-01

The aim of this study was to design a pattern recognition system for assisting the diagnosis of breast lesions, using image information from Ultrasound (US) and Digital Mammography (DM) imaging modalities. State-of-art computer technology was employed based on commercial Graphics Processing Unit (GPU) cards and parallel programming. An experienced radiologist outlined breast lesions on both US and DM images from 59 patients employing a custom designed computer software application. Textural features were extracted from each lesion and were used to design the pattern recognition system. Several classifiers were tested for highest performance in discriminating benign from malignant lesions. Classifiers were also combined into ensemble schemes for further improvement of the system's classification accuracy. Following the pattern recognition system optimization, the final system was designed employing the Probabilistic Neural Network classifier (PNN) on the GPU card (GeForce 580GTX) using CUDA programming framework and C++ programming language. The use of such state-of-art technology renders the system capable of redesigning itself on site once additional verified US and DM data are collected. Mixture of US and DM features optimized performance with over 90% accuracy in correctly classifying the lesions.

Optical correlator method and apparatus for particle image velocimetry processing

NASA Technical Reports Server (NTRS)

Farrell, Patrick V. (Inventor)

1991-01-01

Young's fringes are produced from a double exposure image of particles in a flowing fluid by passing laser light through the film and projecting the light onto a screen. A video camera receives the image from the screen and controls a spatial light modulator. The spatial modulator has a two dimensional array of cells the transmissiveness of which are controlled in relation to the brightness of the corresponding pixel of the video camera image of the screen. A collimated beam of laser light is passed through the spatial light modulator to produce a diffraction pattern which is focused onto another video camera, with the output of the camera being digitized and provided to a microcomputer. The diffraction pattern formed when the laser light is passed through the spatial light modulator and is focused to a point corresponds to the two dimensional Fourier transform of the Young's fringe pattern projected onto the screen. The data obtained fro This invention was made with U.S. Government support awarded by the Department of the Army (DOD) and NASA grand number(s): DOD #DAAL03-86-K0174 and NASA #NAG3-718. The U.S. Government has certain rights in this invention.

Geomorphological analysis of boulders and polygons on Martian periglacial patterned ground terrains

NASA Astrophysics Data System (ADS)

Orloff, Travis C.

Images from the High Resolution Imaging Science Experiment Camera onboard the Mars Reconnaisance Orbiter show the surface in higher detail than previously capable. I look at a landscape on Mars called permafrost patterned ground which covers ˜10 million square kilometers of the surface at high latitudes (>50°). Using the new high resolution images available we objectively characterize permafrost patterned ground terrains as an alternative to observational surveys which while detailed suffer from subjective bias. I take two dimensional Fourier transforms of individual images of Martian permafrost patterned ground to find the scale most representative of the terrain. This scale acts as a proxy for the size of the polygons themselves. Then I look at the distribution of spectral scales in the northern hemisphere between 50-70° and find correlations to previous studies and with the extent of ground ice in the surface. The high resolution images also show boulders clustering with respect to the underlying pattern. I make the first detailed observations of these clustered boulders and use crater counting to place constraints on the time it takes for boulders to cluster. Finally, I present a potential mechanism for the process that clusters the boulders that takes the specifics of the Martian environment to account. Boulders lying on the surface get trapped in seasonal CO2 frost while ice in the near surface contracts in the winter. The CO2 frost sublimates in spring/summer allowing the boulders to move when the near surface ice expands in summer. Repeated iterations lead to boulders that cluster in the polygon edges. Using a thermal model of the subsurface with Mars conditions and an elastic model of a polygon I show boulders could move as much as ˜0.1mm per year in the present day.

An Approach to Improve the Quality of Infrared Images of Vein-Patterns

PubMed Central

Lin, Chih-Lung

2011-01-01

This study develops an approach to improve the quality of infrared (IR) images of vein-patterns, which usually have noise, low contrast, low brightness and small objects of interest, thus requiring preprocessing to improve their quality. The main characteristics of the proposed approach are that no prior knowledge about the IR image is necessary and no parameters must be preset. Two main goals are sought: impulse noise reduction and adaptive contrast enhancement technologies. In our study, a fast median-based filter (FMBF) is developed as a noise reduction method. It is based on an IR imaging mechanism to detect the noisy pixels and on a modified median-based filter to remove the noisy pixels in IR images. FMBF has the advantage of a low computation load. In addition, FMBF can retain reasonably good edges and texture information when the size of the filter window increases. The most important advantage is that the peak signal-to-noise ratio (PSNR) caused by FMBF is higher than the PSNR caused by the median filter. A hybrid cumulative histogram equalization (HCHE) is proposed for adaptive contrast enhancement. HCHE can automatically generate a hybrid cumulative histogram (HCH) based on two different pieces of information about the image histogram. HCHE can improve the enhancement effect on hot objects rather than background. The experimental results are addressed and demonstrate that the proposed approach is feasible for use as an effective and adaptive process for enhancing the quality of IR vein-pattern images. PMID:22247674

An approach to improve the quality of infrared images of vein-patterns.

PubMed

Lin, Chih-Lung

2011-01-01

This study develops an approach to improve the quality of infrared (IR) images of vein-patterns, which usually have noise, low contrast, low brightness and small objects of interest, thus requiring preprocessing to improve their quality. The main characteristics of the proposed approach are that no prior knowledge about the IR image is necessary and no parameters must be preset. Two main goals are sought: impulse noise reduction and adaptive contrast enhancement technologies. In our study, a fast median-based filter (FMBF) is developed as a noise reduction method. It is based on an IR imaging mechanism to detect the noisy pixels and on a modified median-based filter to remove the noisy pixels in IR images. FMBF has the advantage of a low computation load. In addition, FMBF can retain reasonably good edges and texture information when the size of the filter window increases. The most important advantage is that the peak signal-to-noise ratio (PSNR) caused by FMBF is higher than the PSNR caused by the median filter. A hybrid cumulative histogram equalization (HCHE) is proposed for adaptive contrast enhancement. HCHE can automatically generate a hybrid cumulative histogram (HCH) based on two different pieces of information about the image histogram. HCHE can improve the enhancement effect on hot objects rather than background. The experimental results are addressed and demonstrate that the proposed approach is feasible for use as an effective and adaptive process for enhancing the quality of IR vein-pattern images.

The developing human connectome project: A minimal processing pipeline for neonatal cortical surface reconstruction.

PubMed

Makropoulos, Antonios; Robinson, Emma C; Schuh, Andreas; Wright, Robert; Fitzgibbon, Sean; Bozek, Jelena; Counsell, Serena J; Steinweg, Johannes; Vecchiato, Katy; Passerat-Palmbach, Jonathan; Lenz, Gregor; Mortari, Filippo; Tenev, Tencho; Duff, Eugene P; Bastiani, Matteo; Cordero-Grande, Lucilio; Hughes, Emer; Tusor, Nora; Tournier, Jacques-Donald; Hutter, Jana; Price, Anthony N; Teixeira, Rui Pedro A G; Murgasova, Maria; Victor, Suresh; Kelly, Christopher; Rutherford, Mary A; Smith, Stephen M; Edwards, A David; Hajnal, Joseph V; Jenkinson, Mark; Rueckert, Daniel

2018-06-01

The Developing Human Connectome Project (dHCP) seeks to create the first 4-dimensional connectome of early life. Understanding this connectome in detail may provide insights into normal as well as abnormal patterns of brain development. Following established best practices adopted by the WU-MINN Human Connectome Project (HCP), and pioneered by FreeSurfer, the project utilises cortical surface-based processing pipelines. In this paper, we propose a fully automated processing pipeline for the structural Magnetic Resonance Imaging (MRI) of the developing neonatal brain. This proposed pipeline consists of a refined framework for cortical and sub-cortical volume segmentation, cortical surface extraction, and cortical surface inflation, which has been specifically designed to address considerable differences between adult and neonatal brains, as imaged using MRI. Using the proposed pipeline our results demonstrate that images collected from 465 subjects ranging from 28 to 45 weeks post-menstrual age (PMA) can be processed fully automatically; generating cortical surface models that are topologically correct, and correspond well with manual evaluations of tissue boundaries in 85% of cases. Results improve on state-of-the-art neonatal tissue segmentation models and significant errors were found in only 2% of cases, where these corresponded to subjects with high motion. Downstream, these surfaces will enhance comparisons of functional and diffusion MRI datasets, supporting the modelling of emerging patterns of brain connectivity. Copyright © 2018 Elsevier Inc. All rights reserved.

Uses of software in digital image analysis: a forensic report

NASA Astrophysics Data System (ADS)

Sharma, Mukesh; Jha, Shailendra

2010-02-01

Forensic image analysis is required an expertise to interpret the content of an image or the image itself in legal matters. Major sub-disciplines of forensic image analysis with law enforcement applications include photo-grammetry, photographic comparison, content analysis and image authentication. It has wide applications in forensic science range from documenting crime scenes to enhancing faint or indistinct patterns such as partial fingerprints. The process of forensic image analysis can involve several different tasks, regardless of the type of image analysis performed. Through this paper authors have tried to explain these tasks, which are described in to three categories: Image Compression, Image Enhancement & Restoration and Measurement Extraction. With the help of examples like signature comparison, counterfeit currency comparison and foot-wear sole impression using the software Canvas and Corel Draw.

Technical Note: Detection of gas bubble leakage via correlation of water column multibeam images

NASA Astrophysics Data System (ADS)

Schneider von Deimling, J.; Papenberg, C.

2011-07-01

Hydroacoustic detection of natural gas release from the seafloor has been conducted in the past by using singlebeam echosounders. In contrast modern multibeam swath mapping systems allow much wider coverage, higher resolution, and offer 3-D spatial correlation. However, up to the present, the extremely high data rate hampers water column backscatter investigations. More sophisticated visualization and processing techniques for water column backscatter analysis are still under development. We here present such water column backscattering data gathered with a 50 kHz prototype multibeam system. Water column backscattering data is presented in videoframes grabbed over 75 s and a "re-sorted" singlebeam presentation. Thus individual gas bubbles rising from the 24 m deep seafloor clearly emerge in the acoustic images and rise velocities can be determined. A sophisticated processing scheme is introduced to identify those rising gas bubbles in the hydroacoustic data. It applies a cross-correlation technique similar to that used in Particle Imaging Velocimetry (PIV) to the acoustic backscatter images. Tempo-spatial drift patterns of the bubbles are assessed and match very well measured and theoretical rise patterns. The application of this processing scheme to our field data gives impressive results with respect to unambiguous bubble detection and remote bubble rise velocimetry. The method can identify and exclude the main driver for misinterpretations, i.e. fish-mediated echoes. Even though image-based cross-correlation techniques are well known in the field of fluid mechanics for high resolution and non-inversive current flow field analysis, this technique was never applied in the proposed sense for an acoustic bubble detector.

Growth studies at bulk III-Vs by image processing

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

Donecker, J.; Hempel, G.; Kluge, J.

1996-12-01

The patterns of inhomogeneities in GaAs and InP are studied by scattering and diffraction of light. An adapted version of laser scattering tomography is used for observations with short exposure times and large fields. The information about the three-dimensional distribution of the scatterers in GaAs are evaluated by video travels through the crystal and images of intensities added in interesting directions. Near-infrared transmission and striation distance mapping act like special data compression techniques due to their optical principles. In general, columnar extension of cellular patterns and striations could not be detected in s.i. GaAs. Long-range correlations exist for lineages andmore » slip lines. The comparison with the behavior of striations in doped InP cannot confirm the idea that cellular patterns in GaAs originate from constitutional supercooling during solidification.« less

Abnormalities of Object Visual Processing in Body Dysmorphic Disorder

PubMed Central

Feusner, Jamie D.; Hembacher, Emily; Moller, Hayley; Moody, Teena D.

2013-01-01

Background Individuals with body dysmorphic disorder may have perceptual distortions for their appearance. Previous studies suggest imbalances in detailed relative to configural/holistic visual processing when viewing faces. No study has investigated the neural correlates of processing non-symptom-related stimuli. The objective of this study was to determine whether individuals with body dysmorphic disorder have abnormal patterns of brain activation when viewing non-face/non-body object stimuli. Methods Fourteen medication-free participants with DSM-IV body dysmorphic disorder and 14 healthy controls participated. We performed functional magnetic resonance imaging while participants matched photographs of houses that were unaltered, contained only high spatial frequency (high detail) information, or only low spatial frequency (low detail) information. The primary outcome was group differences in blood oxygen level-dependent signal changes. Results The body dysmorphic disorder group showed lesser activity in the parahippocampal gyrus, lingual gyrus, and precuneus for low spatial frequency images. There were greater activations in medial prefrontal regions for high spatial frequency images, although no significant differences when compared to a low-level baseline. Greater symptom severity was associated with lesser activity in dorsal occipital cortex and ventrolateral prefrontal cortex for normal and high spatial frequency images. Conclusions Individuals with body dysmorphic disorder have abnormal brain activation patterns when viewing objects. Hypoactivity in visual association areas for configural and holistic (low detail) elements and abnormal allocation of prefrontal systems for details is consistent with a model of imbalances in global vs. local processing. This may occur not only for appearance but also for general stimuli unrelated to their symptoms. PMID:21557897

Executive-affective connectivity in smokers viewing anti-smoking images: an fMRI study.

PubMed

Dinh-Williams, Laurence; Mendrek, Adrianna; Dumais, Alexandre; Bourque, Josiane; Potvin, Stéphane

2014-12-30

Despite knowledge of the harmful consequences of smoking on health, tobacco users continue to smoke. Neuroimaging studies have begun to provide insight into the mechanisms underlying this response. Regions involved in executive control and affective processing/persuasion are activated when viewing the negative value of smoking, but these systems can interact in ways that promote or hinder its impact on behavior. The goal of this functional magnetic resonance imaging (fMRI) study was to examine the dynamics between these systems during the processing of images designed to elicit a negative emotional response regarding tobacco smoking in a group of current smokers. Thirty chronic smokers passively viewed aversive smoking-related, aversive nonsmoking-related and neutral images presented in a block design while being scanned. Functional connectivity analyses showed that the left inferior frontal gyrus (IFG) is negatively associated to activity in medial frontal, cingulate, limbic, subcortical and parietal regions in chronic smokers during the processing of aversive smoking-related material, a pattern that was significantly greater when stimuli were drug-related compared with when they were nondrug-related. Our results suggest that individuals with tobacco dependence present different patterns of functional connectivity depending on whether the aversive stimuli are smoking- or nonsmoking-related. Activity in the left inferior frontal gyrus may act to down-regulate corresponding activity in regions key to an affective and persuasive response during the processing of anti-smoking material. This mechanism may reduce the extent to which "feeling bad" brings about a change in behavior. Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.

Field theory of pattern identification

NASA Astrophysics Data System (ADS)

Agu, Masahiro

1988-06-01

Based on the psychological experimental fact that images in mental space are transformed into other images for pattern identification, a field theory of pattern identification of geometrical patterns is developed with the use of gauge field theory in Euclidean space. Here, the ``image'' or state function ψ[χ] of the brain reacting to a geometrical pattern χ is made to correspond to the electron's wave function in Minkowski space. The pattern identification of the pattern χ with the modified pattern χ+Δχ is assumed to be such that their images ψ[χ] and ψ[χ+Δχ] in the brain are transformable with each other through suitable transformation groups such as parallel transformation, dilatation, or rotation. The transformation group is called the ``image potential'' which corresponds to the vector potential of the gauge field. An ``image field'' derived from the image potential is found to be induced in the brain when the two images ψ[χ] and ψ[χ+Δχ] are not transformable through suitable transformation groups or gauge transformations. It is also shown that, when the image field exists, the final state of the image ψ[χ] is expected to be different, depending on the paths of modifications of the pattern χ leading to a final pattern. The above fact is interpreted as a version of the Aharonov and Bohm effect of the electron's wave function [A. Aharonov and D. Bohm, Phys. Rev. 115, 485 (1959)]. An excitation equation of the image field is also derived by postulating that patterns are identified maximally for the purpose of minimizing the number of memorized standard patterns.

Focused electron beam based direct-write fabrication of graphene and amorphous carbon from oxo-functionalized graphene on silicon dioxide.

PubMed

Schindler, Severin; Vollnhals, Florian; Halbig, Christian E; Marbach, Hubertus; Steinrück, Hans-Peter; Papp, Christian; Eigler, Siegfried

2017-01-25

Controlled patterning of graphene is an important task towards device fabrication and thus is the focus of current research activities. Graphene oxide (GO) is a solution-processible precursor of graphene. It can be patterned by thermal processing. However, thermal processing of GO leads to decomposition and CO 2 formation. Alternatively, focused electron beam induced processing (FEBIP) techniques can be used to pattern graphene with high spatial resolution. Based on this approach, we explore FEBIP of GO deposited on SiO 2 . Using oxo-functionalized graphene (oxo-G) with an in-plane lattice defect density of 1% we are able to image the electron beam-induced effects by scanning Raman microscopy for the first time. Depending on electron energy (2-30 keV) and doses (50-800 mC m -2 ) either reduction of GO or formation of permanent lattice defects occurs. This result reflects a step towards controlled FEBIP processing of oxo-G.

A real-time 3D range image sensor based on a novel tip-tilt-piston micromirror and dual frequency phase shifting

NASA Astrophysics Data System (ADS)

Skotheim, Øystein; Schumann-Olsen, Henrik; Thorstensen, Jostein; Kim, Anna N.; Lacolle, Matthieu; Haugholt, Karl-Henrik; Bakke, Thor

2015-03-01

Structured light is a robust and accurate method for 3D range imaging in which one or more light patterns are projected onto the scene and observed with an off-axis camera. Commercial sensors typically utilize DMD- or LCD-based LED projectors, which produce good results but have a number of drawbacks, e.g. limited speed, limited depth of focus, large sensitivity to ambient light and somewhat low light efficiency. We present a 3D imaging system based on a laser light source and a novel tip-tilt-piston micro-mirror. Optical interference is utilized to create sinusoidal fringe patterns. The setup allows fast and easy control of both the frequency and the phase of the fringe patterns by altering the axes of the micro-mirror. For 3D reconstruction we have adapted a Dual Frequency Phase Shifting method which gives robust range measurements with sub-millimeter accuracy. The use of interference for generating sine patterns provides high light efficiency and good focusing properties. The use of a laser and a bandpass filter allows easy removal of ambient light. The fast response of the micro-mirror in combination with a high-speed camera and real-time processing on the GPU allows highly accurate 3D range image acquisition at video rates.

Image texture segmentation using a neural network

NASA Astrophysics Data System (ADS)

Sayeh, Mohammed R.; Athinarayanan, Ragu; Dhali, Pushpuak

1992-09-01

In this paper we use a neural network called the Lyapunov associative memory (LYAM) system to segment image texture into different categories or clusters. The LYAM system is constructed by a set of ordinary differential equations which are simulated on a digital computer. The clustering can be achieved by using a single tuning parameter in the simplest model. Pattern classes are represented by the stable equilibrium states of the system. Design of the system is based on synthesizing two local energy functions, namely, the learning and recall energy functions. Before the implementation of the segmentation process, a Gauss-Markov random field (GMRF) model is applied to the raw image. This application suitably reduces the image data and prepares the texture information for the neural network process. We give a simple image example illustrating the capability of the technique. The GMRF-generated features are also used for a clustering, based on the Euclidean distance.

Image restoration approach to address reduced modulation contrast in structured illumination microscopy

PubMed Central

Patwary, Nurmohammed; Doblas, Ana; Preza, Chrysanthe

2018-01-01

The performance of structured illumination microscopy (SIM) is hampered in many biological applications due to the inability to modulate the light when imaging deep into the sample. This is in part because sample-induced aberration reduces the modulation contrast of the structured pattern. In this paper, we present an image restoration approach suitable for processing raw incoherent-grid-projection SIM data with a low fringe contrast. Restoration results from simulated and experimental ApoTome SIM data show results with improved signal-to-noise ratio (SNR) and optical sectioning compared to the results obtained from existing methods, such as 2D demodulation and 3D SIM deconvolution. Our proposed method provides satisfactory results (quantified by the achieved SNR and normalized mean square error) even when the modulation contrast of the illumination pattern is as low as 7%. PMID:29675307

Energy-resolved coherent diffraction from laser-driven electronic motion in atoms

NASA Astrophysics Data System (ADS)

Shao, Hua-Chieh; Starace, Anthony F.

2017-10-01

We investigate theoretically the use of energy-resolved ultrafast electron diffraction to image laser-driven electronic motion in atoms. A chirped laser pulse is used to transfer the valence electron of the lithium atom from the ground state to the first excited state. During this process, the electronic motion is imaged by 100-fs and 1-fs electron pulses in energy-resolved diffraction measurements. Simulations show that the angle-resolved spectra reveal the time evolution of the energy content and symmetry of the electronic state. The time-dependent diffraction patterns are further interpreted in terms of the momentum transfer. For the case of incident 1-fs electron pulses, the rapid 2 s -2 p quantum beat motion of the target electron is imaged as a time-dependent asymmetric oscillation of the diffraction pattern.

Verification Image of The Veins on The Back Palm with Modified Local Line Binary Pattern (MLLBP) and Histogram

NASA Astrophysics Data System (ADS)

Prijono, Agus; Darmawan Hangkawidjaja, Aan; Ratnadewi; Saleh Ahmar, Ansari

2018-01-01

The verification to person who is used today as a fingerprint, signature, personal identification number (PIN) in the bank system, identity cards, attendance, easily copied and forged. This causes the system not secure and is vulnerable to unauthorized persons to access the system. In this research will be implemented verification system using the image of the blood vessels in the back of the palms as recognition more difficult to imitate because it is located inside the human body so it is safer to use. The blood vessels located at the back of the human hand is unique, even humans twins have a different image of the blood vessels. Besides the image of the blood vessels do not depend on a person’s age, so it can be used for long term, except in the case of an accident, or disease. Because of the unique vein pattern recognition can be used in a person. In this paper, we used a modification method to perform the introduction of a person based on the image of the blood vessel that is using Modified Local Line Binary Pattern (MLLBP). The process of matching blood vessel image feature extraction using Hamming Distance. Test case of verification is done by calculating the percentage of acceptance of the same person. Rejection error occurs if a person was not matched by the system with the data itself. The 10 person with 15 image compared to 5 image vein for each person is resulted 80,67% successful Another test case of the verification is done by verified two image from different person that is forgery, and the verification will be true if the system can rejection the image forgery. The ten different person is not verified and the result is obtained 94%.

Intricate Clouds of Jupiter

NASA Image and Video Library

2018-04-06

See intricate cloud patterns in the northern hemisphere of Jupiter in this new view taken by NASA's Juno spacecraft. The color-enhanced image was taken on April 1, 2018 at 2:32 a.m. PST (5:32 a.m. EST), as Juno performed its twelfth close flyby of Jupiter. At the time the image was taken, the spacecraft was about 7,659 miles (12,326 kilometers) from the tops of the clouds of the planet at a northern latitude of 50.2 degrees. Citizen scientist Kevin M. Gill processed this image using data from the JunoCam imager. https://photojournal.jpl.nasa.gov/catalog/PIA21984

Optical smart packaging to reduce transmitted information.

PubMed

Cabezas, Luisa; Tebaldi, Myrian; Barrera, John Fredy; Bolognini, Néstor; Torroba, Roberto

2012-01-02

We demonstrate a smart image-packaging optical technique that uses what we believe is a new concept to save byte space when transmitting data. The technique supports a large set of images mapped into modulated speckle patterns. Then, they are multiplexed into a single package. This operation results in a substantial decreasing of the final amount of bytes of the package with respect to the amount resulting from the addition of the images without using the method. Besides, there are no requirements on the type of images to be processed. We present results that proof the potentiality of the technique.

Software and Algorithms for Biomedical Image Data Processing and Visualization

NASA Technical Reports Server (NTRS)

Talukder, Ashit; Lambert, James; Lam, Raymond

2004-01-01

A new software equipped with novel image processing algorithms and graphical-user-interface (GUI) tools has been designed for automated analysis and processing of large amounts of biomedical image data. The software, called PlaqTrak, has been specifically used for analysis of plaque on teeth of patients. New algorithms have been developed and implemented to segment teeth of interest from surrounding gum, and a real-time image-based morphing procedure is used to automatically overlay a grid onto each segmented tooth. Pattern recognition methods are used to classify plaque from surrounding gum and enamel, while ignoring glare effects due to the reflection of camera light and ambient light from enamel regions. The PlaqTrak system integrates these components into a single software suite with an easy-to-use GUI (see Figure 1) that allows users to do an end-to-end run of a patient s record, including tooth segmentation of all teeth, grid morphing of each segmented tooth, and plaque classification of each tooth image. The automated and accurate processing of the captured images to segment each tooth [see Figure 2(a)] and then detect plaque on a tooth-by-tooth basis is a critical component of the PlaqTrak system to do clinical trials and analysis with minimal human intervention. These features offer distinct advantages over other competing systems that analyze groups of teeth or synthetic teeth. PlaqTrak divides each segmented tooth into eight regions using an advanced graphics morphing procedure [see results on a chipped tooth in Figure 2(b)], and a pattern recognition classifier is then used to locate plaque [red regions in Figure 2(d)] and enamel regions. The morphing allows analysis within regions of teeth, thereby facilitating detailed statistical analysis such as the amount of plaque present on the biting surfaces on teeth. This software system is applicable to a host of biomedical applications, such as cell analysis and life detection, or robotic applications, such as product inspection or assembly of parts in space and industry.

COMPUTATIONAL ANALYSIS BASED ON ARTIFICIAL NEURAL NETWORKS FOR AIDING IN DIAGNOSING OSTEOARTHRITIS OF THE LUMBAR SPINE

PubMed Central

Veronezi, Carlos Cassiano Denipotti; de Azevedo Simões, Priscyla Waleska Targino; dos Santos, Robson Luiz; da Rocha, Edroaldo Lummertz; Meláo, Suelen; de Mattos, Merisandra Côrtes; Cechinel, Cristian

2015-01-01

Objective: To ascertain the advantages of applying artificial neural networks to recognize patterns on lumbar spine radiographies in order to aid in the process of diagnosing primary osteoarthritis. Methods: This was a cross-sectional descriptive analytical study with a quantitative approach and an emphasis on diagnosis. The training set was composed of images collected between January and July 2009 from patients who had undergone lateral-view digital radiographies of the lumbar spine, which were provided by a radiology clinic located in the municipality of Criciúma (SC). Out of the total of 260 images gathered, those with distortions, those presenting pathological conditions that altered the architecture of the lumbar spine and those with patterns that were difficult to characterize were discarded, resulting in 206 images. The image data base (n = 206) was then subdivided, resulting in 68 radiographies for the training stage, 68 images for tests and 70 for validation. A hybrid neural network based on Kohonen self-organizing maps and on Multilayer Perceptron networks was used. Results: After 90 cycles, the validation was carried out on the best results, achieving accuracy of 62.85%, sensitivity of 65.71% and specificity of 60%. Conclusions: Even though the effectiveness shown was moderate, this study is still innovative. The values show that the technique used has a promising future, pointing towards further studies on image and cycle processing methodology with a larger quantity of radiographies. PMID:27027010

Target acquisition modeling over the exact optical path: extending the EOSTAR TDA with the TOD sensor performance model

NASA Astrophysics Data System (ADS)

Dijk, J.; Bijl, P.; Oppeneer, M.; ten Hove, R. J. M.; van Iersel, M.

2017-10-01

The Electro-Optical Signal Transmission and Ranging (EOSTAR) model is an image-based Tactical Decision Aid (TDA) for thermal imaging systems (MWIR/LWIR) developed for a sea environment with an extensive atmosphere model. The Triangle Orientation Discrimination (TOD) Target Acquisition model calculates the sensor and signal processing effects on a set of input triangle test pattern images, judges their orientation using humans or a Human Visual System (HVS) model and derives the system image quality and operational field performance from the correctness of the responses. Combination of the TOD model and EOSTAR, basically provides the possibility to model Target Acquisition (TA) performance over the exact path from scene to observer. In this method ship representative TOD test patterns are placed at the position of the real target, subsequently the combined effects of the environment (atmosphere, background, etc.), sensor and signal processing on the image are calculated using EOSTAR and finally the results are judged by humans. The thresholds are converted into Detection-Recognition-Identification (DRI) ranges of the real target. In experiments is shown that combination of the TOD model and the EOSTAR model is indeed possible. The resulting images look natural and provide insight in the possibilities of combining the two models. The TOD observation task can be done well by humans, and the measured TOD is consistent with analytical TOD predictions for the same camera that was modeled in the ECOMOS project.

Fixed-pattern noise correction method based on improved moment matching for a TDI CMOS image sensor.

PubMed

Xu, Jiangtao; Nie, Huafeng; Nie, Kaiming; Jin, Weimin

2017-09-01

In this paper, an improved moment matching method based on a spatial correlation filter (SCF) and bilateral filter (BF) is proposed to correct the fixed-pattern noise (FPN) of a time-delay-integration CMOS image sensor (TDI-CIS). First, the values of row FPN (RFPN) and column FPN (CFPN) are estimated and added to the original image through SCF and BF, respectively. Then the filtered image will be processed by an improved moment matching method with a moving window. Experimental results based on a 128-stage TDI-CIS show that, after correcting the FPN in the image captured under uniform illumination, the standard deviation of row mean vector (SDRMV) decreases from 5.6761 LSB to 0.1948 LSB, while the standard deviation of the column mean vector (SDCMV) decreases from 15.2005 LSB to 13.1949LSB. In addition, for different images captured by different TDI-CISs, the average decrease of SDRMV and SDCMV is 5.4922/2.0357 LSB, respectively. Comparative experimental results indicate that the proposed method can effectively correct the FPNs of different TDI-CISs while maintaining image details without any auxiliary equipment.

Boltzmann Energy-based Image Analysis Demonstrates that Extracellular Domain Size Differences Explain Protein Segregation at Immune Synapses

PubMed Central

Burroughs, Nigel J.; Köhler, Karsten; Miloserdov, Vladimir; Dustin, Michael L.; van der Merwe, P. Anton; Davis, Daniel M.

2011-01-01

Immune synapses formed by T and NK cells both show segregation of the integrin ICAM1 from other proteins such as CD2 (T cell) or KIR (NK cell). However, the mechanism by which these proteins segregate remains unclear; one key hypothesis is a redistribution based on protein size. Simulations of this mechanism qualitatively reproduce observed segregation patterns, but only in certain parameter regimes. Verifying that these parameter constraints in fact hold has not been possible to date, this requiring a quantitative coupling of theory to experimental data. Here, we address this challenge, developing a new methodology for analysing and quantifying image data and its integration with biophysical models. Specifically we fit a binding kinetics model to 2 colour fluorescence data for cytoskeleton independent synapses (2 and 3D) and test whether the observed inverse correlation between fluorophores conforms to size dependent exclusion, and further, whether patterned states are predicted when model parameters are estimated on individual synapses. All synapses analysed satisfy these conditions demonstrating that the mechanisms of protein redistribution have identifiable signatures in their spatial patterns. We conclude that energy processes implicit in protein size based segregation can drive the patternation observed in individual synapses, at least for the specific examples tested, such that no additional processes need to be invoked. This implies that biophysical processes within the membrane interface have a crucial impact on cell∶cell communication and cell signalling, governing protein interactions and protein aggregation. PMID:21829338

What Not To Do: Anti-patterns for Developing Scientific Workflow Software Components

NASA Astrophysics Data System (ADS)

Futrelle, J.; Maffei, A. R.; Sosik, H. M.; Gallager, S. M.; York, A.

2013-12-01

Scientific workflows promise to enable efficient scaling-up of researcher code to handle large datasets and workloads, as well as documentation of scientific processing via standardized provenance records, etc. Workflow systems and related frameworks for coordinating the execution of otherwise separate components are limited, however, in their ability to overcome software engineering design problems commonly encountered in pre-existing components, such as scripts developed externally by scientists in their laboratories. In practice, this often means that components must be rewritten or replaced in a time-consuming, expensive process. In the course of an extensive workflow development project involving large-scale oceanographic image processing, we have begun to identify and codify 'anti-patterns'--problematic design characteristics of software--that make components fit poorly into complex automated workflows. We have gone on to develop and document low-effort solutions and best practices that efficiently address the anti-patterns we have identified. The issues, solutions, and best practices can be used to evaluate and improve existing code, as well as guiding the development of new components. For example, we have identified a common anti-pattern we call 'batch-itis' in which a script fails and then cannot perform more work, even if that work is not precluded by the failure. The solution we have identified--removing unnecessary looping over independent units of work--is often easier to code than the anti-pattern, as it eliminates the need for complex control flow logic in the component. Other anti-patterns we have identified are similarly easy to identify and often easy to fix. We have drawn upon experience working with three science teams at Woods Hole Oceanographic Institution, each of which has designed novel imaging instruments and associated image analysis code. By developing use cases and prototypes within these teams, we have undertaken formal evaluations of software components developed by programmers with widely varying levels of expertise, and have been able to discover and characterize a number of anti-patterns. Our evaluation methodology and testbed have also enabled us to assess the efficacy of strategies to address these anti-patterns according to scientifically relevant metrics, such as ability of algorithms to perform faster than the rate of data acquisition and the accuracy of workflow component output relative to ground truth. The set of anti-patterns and solutions we have identified augments of the body of more well-known software engineering anti-patterns by addressing additional concerns that obtain when a software component has to function as part of a workflow assembled out of independently-developed codebases. Our experience shows that identifying and resolving these anti-patterns reduces development time and improves performance without reducing component reusability.

Evidence for Rhythmicity Pacemaker in the Calcification Process of Scleractinian Coral

NASA Astrophysics Data System (ADS)

Gutner-Hoch, Eldad; Schneider, Kenneth; Stolarski, Jaroslaw; Domart-Coulon, Isabelle; Yam, Ruth; Meibom, Anders; Shemesh, Aldo; Levy, Oren

2016-02-01

Reef-building scleractinian (stony) corals are among the most efficient bio-mineralizing organisms in nature. The calcification rate of scleractinian corals oscillates under ambient light conditions, with a cyclic, diurnal pattern. A fundamental question is whether this cyclic pattern is controlled by exogenous signals or by an endogenous ‘biological-clock’ mechanism, or both. To address this problem, we have studied calcification patterns of the Red Sea scleractinian coral Acropora eurystoma with frequent measurements of total alkalinity (AT) under different light conditions. Additionally, skeletal extension and ultra-structure of newly deposited calcium carbonate were elucidated with 86Sr isotope labeling analysis, combined with NanoSIMS ion microprobe and scanning electron microscope imaging. Our results show that the calcification process persists with its cyclic pattern under constant light conditions while dissolution takes place within one day of constant dark conditions, indicating that an intrinsic, light-entrained mechanism may be involved in controlling the calcification process in photosymbiotic corals.

Ultimate patterning limits for EUV at 5nm node and beyond

NASA Astrophysics Data System (ADS)

Ali, Rehab Kotb; Hamed Fatehy, Ahmed; Lafferty, Neal; Word, James

2018-03-01

The 5nm technology node introduces more aggressive geometries than previous nodes. In this paper, we are introducing a comprehensive study to examine the pattering limits of EUV at 0.33NA. The study is divided into two main approaches: (A) Exploring pattering limits of Single Exposure EUV Cut/Block mask in Self-Aligned-Multi-Patterning (SAMP) process, and (B) Exploring the pattering limits of a Single Exposure EUV printing of metal Layers. The printability of the resulted OPC masks is checked through a model based manufacturing flow for the two pattering approaches. The final manufactured patterns are quantified by Edge Placement Error (EPE), Process Variation Band (PVBand), soft/hard bridging and pinching, Image Log Slope (ILS) and Common Depth of Focus (CDOF)

Message framing and defensive processing: a cultural examination.

PubMed

Ko, Deborah M; Kim, Heejung S

2010-01-01

Past research has shown that health messages on safer sexual practices that focus on relational consequences are more persuasive than messages that focus on personal consequences. However, we theorize that it is defensiveness against personal risk framing that threatens the self among people from more individualistic cultures. Two studies tested this idea. Study 1 showed that European Americans were less persuaded by personal framing than by relational framing but that this pattern was not found for Asian Americans, who are more collectivistic. Study 2 showed that these defensive patterns were eliminated among European American participants when a person's self-image was affirmed. These results suggest defensive processes as the mechanism behind the differences in message framing effectiveness and motivate a closer look at cultural patterns.

Noninvasive imaging of hepatocellular carcinoma: From diagnosis to prognosis

PubMed Central

Jiang, Han-Yu; Chen, Jie; Xia, Chun-Chao; Cao, Li-Kun; Duan, Ting; Song, Bin

2018-01-01

Hepatocellular carcinoma (HCC) is the most common primary liver cancer and a major public health problem worldwide. Hepatocarcinogenesis is a complex multistep process at molecular, cellular, and histologic levels with key alterations that can be revealed by noninvasive imaging modalities. Therefore, imaging techniques play pivotal roles in the detection, characterization, staging, surveillance, and prognosis evaluation of HCC. Currently, ultrasound is the first-line imaging modality for screening and surveillance purposes. While based on conclusive enhancement patterns comprising arterial phase hyperenhancement and portal venous and/or delayed phase wash-out, contrast enhanced dynamic computed tomography and magnetic resonance imaging (MRI) are the diagnostic tools for HCC without requirements for histopathologic confirmation. Functional MRI techniques, including diffusion-weighted imaging, MRI with hepatobiliary contrast agents, perfusion imaging, and magnetic resonance elastography, show promise in providing further important information regarding tumor biological behaviors. In addition, evaluation of tumor imaging characteristics, including nodule size, margin, number, vascular invasion, and growth patterns, allows preoperative prediction of tumor microvascular invasion and patient prognosis. Therefore, the aim of this article is to review the current state-of-the-art and recent advances in the comprehensive noninvasive imaging evaluation of HCC. We also provide the basic key concepts of HCC development and an overview of the current practice guidelines. PMID:29904242

Application of imaging technology to improve the laboratory and field compaction of HMA.

DOT National Transportation Integrated Search

2009-04-01

Field compaction of asphalt mixtures is an important process that influences performance of asphalt : pavements. This study evaluates the relationship between different field compaction patterns and the : uniformity of air void distribution in asphal...

Classifying adolescent attention-deficit/hyperactivity disorder (ADHD) based on functional and structural imaging.

PubMed

Iannaccone, Reto; Hauser, Tobias U; Ball, Juliane; Brandeis, Daniel; Walitza, Susanne; Brem, Silvia

2015-10-01

Attention-deficit/hyperactivity disorder (ADHD) is a common disabling psychiatric disorder associated with consistent deficits in error processing, inhibition and regionally decreased grey matter volumes. The diagnosis is based on clinical presentation, interviews and questionnaires, which are to some degree subjective and would benefit from verification through biomarkers. Here, pattern recognition of multiple discriminative functional and structural brain patterns was applied to classify adolescents with ADHD and controls. Functional activation features in a Flanker/NoGo task probing error processing and inhibition along with structural magnetic resonance imaging data served to predict group membership using support vector machines (SVMs). The SVM pattern recognition algorithm correctly classified 77.78% of the subjects with a sensitivity and specificity of 77.78% based on error processing. Predictive regions for controls were mainly detected in core areas for error processing and attention such as the medial and dorsolateral frontal areas reflecting deficient processing in ADHD (Hart et al., in Hum Brain Mapp 35:3083-3094, 2014), and overlapped with decreased activations in patients in conventional group comparisons. Regions more predictive for ADHD patients were identified in the posterior cingulate, temporal and occipital cortex. Interestingly despite pronounced univariate group differences in inhibition-related activation and grey matter volumes the corresponding classifiers failed or only yielded a poor discrimination. The present study corroborates the potential of task-related brain activation for classification shown in previous studies. It remains to be clarified whether error processing, which performed best here, also contributes to the discrimination of useful dimensions and subtypes, different psychiatric disorders, and prediction of treatment success across studies and sites.

Optical-Correlator Neural Network Based On Neocognitron

NASA Technical Reports Server (NTRS)

Chao, Tien-Hsin; Stoner, William W.

1994-01-01

Multichannel optical correlator implements shift-invariant, high-discrimination pattern-recognizing neural network based on paradigm of neocognitron. Selected as basic building block of this neural network because invariance under shifts is inherent advantage of Fourier optics included in optical correlators in general. Neocognitron is conceptual electronic neural-network model for recognition of visual patterns. Multilayer processing achieved by iteratively feeding back output of feature correlator to input spatial light modulator and updating Fourier filters. Neural network trained by use of characteristic features extracted from target images. Multichannel implementation enables parallel processing of large number of selected features.

Modeling of biologically motivated self-learning equivalent-convolutional recurrent-multilayer neural structures (BLM_SL_EC_RMNS) for image fragments clustering and recognition

NASA Astrophysics Data System (ADS)

Krasilenko, Vladimir G.; Lazarev, Alexander A.; Nikitovich, Diana V.

2018-03-01

The biologically-motivated self-learning equivalence-convolutional recurrent-multilayer neural structures (BLM_SL_EC_RMNS) for fragments images clustering and recognition will be discussed. We shall consider these neural structures and their spatial-invariant equivalental models (SIEMs) based on proposed equivalent two-dimensional functions of image similarity and the corresponding matrix-matrix (or tensor) procedures using as basic operations of continuous logic and nonlinear processing. These SIEMs can simply describe the signals processing during the all training and recognition stages and they are suitable for unipolar-coding multilevel signals. The clustering efficiency in such models and their implementation depends on the discriminant properties of neural elements of hidden layers. Therefore, the main models and architecture parameters and characteristics depends on the applied types of non-linear processing and function used for image comparison or for adaptive-equivalent weighing of input patterns. We show that these SL_EC_RMNSs have several advantages, such as the self-study and self-identification of features and signs of the similarity of fragments, ability to clustering and recognize of image fragments with best efficiency and strong mutual correlation. The proposed combined with learning-recognition clustering method of fragments with regard to their structural features is suitable not only for binary, but also color images and combines self-learning and the formation of weight clustered matrix-patterns. Its model is constructed and designed on the basis of recursively continuous logic and nonlinear processing algorithms and to k-average method or method the winner takes all (WTA). The experimental results confirmed that fragments with a large numbers of elements may be clustered. For the first time the possibility of generalization of these models for space invariant case is shown. The experiment for an images of different dimensions (a reference array) and fragments with diferent dimensions for clustering is carried out. The experiments, using the software environment Mathcad showed that the proposed method is universal, has a significant convergence, the small number of iterations is easily, displayed on the matrix structure, and confirmed its prospects. Thus, to understand the mechanisms of self-learning equivalence-convolutional clustering, accompanying her to the competitive processes in neurons, and the neural auto-encoding-decoding and recognition principles with the use of self-learning cluster patterns is very important which used the algorithm and the principles of non-linear processing of two-dimensional spatial functions of images comparison. The experimental results show that such models can be successfully used for auto- and hetero-associative recognition. Also they can be used to explain some mechanisms, known as "the reinforcementinhibition concept". Also we demonstrate a real model experiments, which confirm that the nonlinear processing by equivalent function allow to determine the neuron-winners and customize the weight matrix. At the end of the report, we will show how to use the obtained results and to propose new more efficient hardware architecture of SL_EC_RMNS based on matrix-tensor multipliers. Also we estimate the parameters and performance of such architectures.

Accelerating image recognition on mobile devices using GPGPU

NASA Astrophysics Data System (ADS)

Bordallo López, Miguel; Nykänen, Henri; Hannuksela, Jari; Silvén, Olli; Vehviläinen, Markku

2011-01-01

The future multi-modal user interfaces of battery-powered mobile devices are expected to require computationally costly image analysis techniques. The use of Graphic Processing Units for computing is very well suited for parallel processing and the addition of programmable stages and high precision arithmetic provide for opportunities to implement energy-efficient complete algorithms. At the moment the first mobile graphics accelerators with programmable pipelines are available, enabling the GPGPU implementation of several image processing algorithms. In this context, we consider a face tracking approach that uses efficient gray-scale invariant texture features and boosting. The solution is based on the Local Binary Pattern (LBP) features and makes use of the GPU on the pre-processing and feature extraction phase. We have implemented a series of image processing techniques in the shader language of OpenGL ES 2.0, compiled them for a mobile graphics processing unit and performed tests on a mobile application processor platform (OMAP3530). In our contribution, we describe the challenges of designing on a mobile platform, present the performance achieved and provide measurement results for the actual power consumption in comparison to using the CPU (ARM) on the same platform.

In-die mask registration measurement on 28nm-node and beyond

NASA Astrophysics Data System (ADS)

Chen, Shen Hung; Cheng, Yung Feng; Chen, Ming Jui

2013-09-01

As semiconductor go to smaller node, the critical dimension (CD) of process become more and more small. For lithography, RET (Resolution Enhancement Technology) applications can be used for wafer printing of smaller CD/pitch on 28nm node and beyond. SMO (Source Mask Optimization), DPT (Double Patterning Technology) and SADP (Self-Align Double Patterning) can provide lower k1 value for lithography. In another way, image placement error and overlay control also become more and more important for smaller chip size (advanced node). Mask registration (image placement error) and mask overlay are important factors to affect wafer overlay control/performance especially for DPT or SADP. In traditional method, the designed registration marks (cross type, square type) with larger CD were put into scribe-line of mask frame for registration and overlay measurement. However, these patterns are far way from real patterns. It does not show the registration of real pattern directly and is not a convincing method. In this study, the in-die (in-chip) registration measurement is introduced. We extract the dummy patterns that are close to main pattern from post-OPC (Optical Proximity Correction) gds by our desired rule and choose the patterns that distribute over whole mask uniformly. The convergence test shows 100 points measurement has a reliable result.

The study of cognitive processes in the brain EEG during the perception of bistable images using wavelet skeleton

NASA Astrophysics Data System (ADS)

Runnova, Anastasiya E.; Zhuravlev, Maksim O.; Pysarchik, Alexander N.; Khramova, Marina V.; Grubov, Vadim V.

2017-03-01

In the paper we study the appearance of the complex patterns in human EEG data during a psychophysiological experiment by stimulating cognitive activity with the perception of ambiguous object. A new method based on the calculation of the maximum energy component for the continuous wavelet transform (skeletons) is proposed. Skeleton analysis allows us to identify specific patterns in the EEG data set, appearing in the perception of ambiguous objects. Thus, it becomes possible to diagnose some cognitive processes associated with the concentration of attention and recognition of complex visual objects. The article presents the processing results of experimental data for 6 male volunteers.

Colorimetric Topography of Atherosclerotic Lesions by Television Image Processing

DTIC Science & Technology

1979-06-15

image. Indeed, the system is capable of detecting such fine dynamics that epidemiologic factors effecting those changes can not be measured...different occurance patterns and development of clinical atherosclerosis (30). Numerous risk factors have been determined by group comparison and some...techniques and scanners today are much more uniform, and these errors are no longer limiting factors . Since the films were "black and white," and scanned as

Two-photon speckle illumination for super-resolution microscopy.

PubMed

Negash, Awoke; Labouesse, Simon; Chaumet, Patrick C; Belkebir, Kamal; Giovannini, Hugues; Allain, Marc; Idier, Jérôme; Sentenac, Anne

2018-06-01

We present a numerical study of a microscopy setup in which the sample is illuminated with uncontrolled speckle patterns and the two-photon excitation fluorescence is collected on a camera. We show that, using a simple deconvolution algorithm for processing the speckle low-resolution images, this wide-field imaging technique exhibits resolution significantly better than that of two-photon excitation scanning microscopy or one-photon excitation bright-field microscopy.

X-Ray Detector for 1 to 30 keV

NASA Technical Reports Server (NTRS)

Alcorn, G.; Jackson, J., Jr; Grant, P.; Marshall, F.

1983-01-01

Array of silicon X-ray detecting diodes measures photon energy and provides image of X-ray pattern. Regardless of thickness of new X-ray detector, depletion region extends through it. Impinging X-rays generate electrons in quantities proportional to X-ray energy. X-ray detector is mated to chargecoupled-device array for image generation and processing. Useful in industrial part inspection, pulsed-plasma research and medical application.

Artificial Immune System for Recognizing Patterns

NASA Technical Reports Server (NTRS)

Huntsberger, Terrance

2005-01-01

A method of recognizing or classifying patterns is based on an artificial immune system (AIS), which includes an algorithm and a computational model of nonlinear dynamics inspired by the behavior of a biological immune system. The method has been proposed as the theoretical basis of the computational portion of a star-tracking system aboard a spacecraft. In that system, a newly acquired star image would be treated as an antigen that would be matched by an appropriate antibody (an entry in a star catalog). The method would enable rapid convergence, would afford robustness in the face of noise in the star sensors, would enable recognition of star images acquired in any sensor or spacecraft orientation, and would not make an excessive demand on the computational resources of a typical spacecraft. Going beyond the star-tracking application, the AIS-based pattern-recognition method is potentially applicable to pattern- recognition and -classification processes for diverse purposes -- for example, reconnaissance, detecting intruders, and mining data.

Imaging of gamma-Irradiated Regions of a Crystal

NASA Technical Reports Server (NTRS)

Dragoi, Danut; McClure, Steven; Johnston, Allan; Chao, Tien-Hsin

2004-01-01

A holographic technique has been devised for generating a visible display of the effect of exposure of a photorefractive crystal to gamma rays. The technique exploits the space charge that results from trapping of electrons in defects induced by gamma rays. The technique involves a three-stage process. In the first stage, one writes a holographic pattern in the crystal by use of the apparatus shown in Figure 1. A laser beam of 532-nm wavelength is collimated and split into signal and reference beams by use of a polarizing beam splitter. On its way to the crystal, the reference beam goes through a two-dimensional optical scanner that contains two pairs of lenses (L1y, L2y and L1x,L2x) and mirrors M1 and M2, which can be rotated by use of micrometer drives to make fine adjustments. The signal beam is sent through a spatial light modulator that imposes the holographic pattern, then through two imaging lenses L(sub img) on its way to the crystal. An aperture is placed at the common focus of lenses Limg to suppress high-order diffraction from the spatial light modulator. The hologram is formed by interference between the signal and reference beams. A camera lens focuses an image of the interior of the crystal onto a charge-coupled device (CCD). If the crystal is illuminated by only the reference beam once the hologram has been formed, then an image of the hologram is formed on the CCD: this phenomenon is exploited to make visible the pattern of gamma irradiation of the crystal, as described next. In the second stage of the process, the crystal is removed from the holographic apparatus and irradiated with rays at a dose of about 100 krad. In the third stage of the process, the crystal is remounted in the holographic apparatus in the same position as in the first stage and illuminated with only the reference beam to obtain the image of the hologram as modified by the effect of the rays. The orientations of M1 and M2 can be adjusted slightly, if necessary, to maximize the intensity of the image. Figure 2 shows such an image that was formed in a crystal of Fe:LiNbO3.

Preservation of visual cortical function following retinal pigment epithelium transplantation in the RCS rat using optical imaging techniques.

PubMed

Gias, Carlos; Jones, Myles; Keegan, David; Adamson, Peter; Greenwood, John; Lund, Ray; Martindale, John; Johnston, David; Berwick, Jason; Mayhew, John; Coffey, Peter

2007-04-01

The aim of this study was to determine the extent of cortical functional preservation following retinal pigment epithelium (RPE) transplantation in the Royal College of Surgeons (RCS) rat using single-wavelength optical imaging and spectroscopy. The cortical responses to visual stimulation in transplanted rats at 6 months post-transplantation were compared with those from age-matched untreated dystrophic and non-dystrophic rats. Our results show that cortical responses were evoked in non-dystrophic rats to both luminance changes and pattern stimulation, whereas no response was found in untreated dystrophic animals to any of the visual stimuli tested. In contrast, a cortical response was elicited in most of the transplanted rats to luminance changes and in many of those a response was also evoked to pattern stimulation. Although the transplanted rats did not respond to high spatial frequency information we found evidence of preservation in the cortical processing of luminance changes and low spatial frequency stimulation. Anatomical sections of transplanted rat retinas confirmed the capacity of RPE transplantation to rescue photoreceptors. Good correlation was found between photoreceptor survival and the extent of cortical function preservation determined with optical imaging techniques. This study determined the efficacy of RPE transplantation to preserve visual cortical processing and established optical imaging as a powerful technique for its assessment.

Characterizing brain patterns in conversion from mild cognitive impairment (MCI) to Alzheimer's disease

NASA Astrophysics Data System (ADS)

Silva R., Santiago S.; Giraldo, Diana L.; Romero, Eduardo

2017-11-01

Structural Magnetic Resonance (MR) brain images should provide quantitative information about the stage and progression of Alzheimer's disease. However, the use of MRI is limited and practically reduced to corroborate a diagnosis already performed with neuropsychological tools. This paper presents an automated strategy for extraction of relevant anatomic patterns related with the conversion from mild cognitive impairment (MCI) to Alzheimer's disease (AD) using T1-weighted MR images. The process starts by representing each of the possible classes with models generated from a linear combination of volumes. The difference between models allows us to establish which are the regions where relevant patterns might be located. The approach searches patterns in a space of brain sulci, herein approximated by the most representative gradients found in regions of interest defined by the difference between the linear models. This hypothesis is assessed by training a conventional SVM model with the found relevant patterns under a leave-one-out scheme. The resultant AUC was 0.86 for the group of women and 0.61 for the group of men.

Nanometer-scale sizing accuracy of particle suspensions on an unmodified cell phone using elastic light scattering.

PubMed

Smith, Zachary J; Chu, Kaiqin; Wachsmann-Hogiu, Sebastian

2012-01-01

We report on the construction of a Fourier plane imaging system attached to a cell phone. By illuminating particle suspensions with a collimated beam from an inexpensive diode laser, angularly resolved scattering patterns are imaged by the phone's camera. Analyzing these patterns with Mie theory results in predictions of size distributions of the particles in suspension. Despite using consumer grade electronics, we extracted size distributions of sphere suspensions with better than 20 nm accuracy in determining the mean size. We also show results from milk, yeast, and blood cells. Performing these measurements on a portable device presents opportunities for field-testing of food quality, process monitoring, and medical diagnosis.

Hierarchical content-based image retrieval by dynamic indexing and guided search

NASA Astrophysics Data System (ADS)

You, Jane; Cheung, King H.; Liu, James; Guo, Linong

2003-12-01

This paper presents a new approach to content-based image retrieval by using dynamic indexing and guided search in a hierarchical structure, and extending data mining and data warehousing techniques. The proposed algorithms include: a wavelet-based scheme for multiple image feature extraction, the extension of a conventional data warehouse and an image database to an image data warehouse for dynamic image indexing, an image data schema for hierarchical image representation and dynamic image indexing, a statistically based feature selection scheme to achieve flexible similarity measures, and a feature component code to facilitate query processing and guide the search for the best matching. A series of case studies are reported, which include a wavelet-based image color hierarchy, classification of satellite images, tropical cyclone pattern recognition, and personal identification using multi-level palmprint and face features.

Associations between the oxytocin receptor gene (OXTR) rs53576 polymorphism and emotional processing of social and nonsocial cues: an event-related potential (ERP) study.

PubMed

Choi, Damee; Minote, Natsumi; Watanuki, Shigeki

2017-01-26

Oxytocin receptor (OXTR) gene polymorphisms are related to individual differences in emotional processing of social cues. However, whether OXTR polymorphisms affect emotional processing of nonsocial cues remains unclear. The present study investigated the relationship between the OXTR rs53576 polymorphism and emotional processing of social cues and nonsocial cues. Event-related potentials were recorded from 88 male participants while images of humans and images of objects were presented as social cues and nonsocial cues, respectively. First, the results showed that GG carriers of OXTR rs53576 showed more negative N1 (50-200 ms) than AA carriers in response to images of both humans and objects. Second, GG carriers showed more negative N2 (200-320 ms) than AA carriers in response to images of humans but not in response to images of objects. Third, GG carriers showed more negative N2 in response to images of humans than images of objects, whereas AA carriers showed the opposite pattern. Fourth, we observed no difference in late positive potential (600-1000 ms) to images of humans or objects that depended on the OXTR rs53576 polymorphism. These results suggest that the OXTR rs53576 polymorphism affects emotional processing of not only social cues but also nonsocial cues in the very early stage (reflected in N1); however, the data also suggest that the OXTR rs53576 polymorphism is related specifically to increased emotional processing of social cues in the middle stage (reflected in N2).

An image-processing strategy to extract important information suitable for a low-size stimulus pattern in a retinal prosthesis.

PubMed

Chen, Yili; Fu, Jixiang; Chu, Dawei; Li, Rongmao; Xie, Yaoqin

2017-11-27

A retinal prosthesis is designed to help the blind to obtain some sight. It consists of an external part and an internal part. The external part is made up of a camera, an image processor and an RF transmitter. The internal part is made up of an RF receiver, implant chip and microelectrode. Currently, the number of microelectrodes is in the hundreds, and we do not know the mechanism for using an electrode to stimulate the optic nerve. A simple hypothesis is that the pixels in an image correspond to the electrode. The images captured by the camera should be processed by suitable strategies to correspond to stimulation from the electrode. Thus, it is a question of how to obtain the important information from the image captured in the picture. Here, we use the region of interest (ROI), a useful algorithm for extracting the ROI, to retain the important information, and to remove the redundant information. This paper explains the details of the principles and functions of the ROI. Because we are investigating a real-time system, we need a fast processing ROI as a useful algorithm to extract the ROI. Thus, we simplified the ROI algorithm and used it in an outside image-processing digital signal processing (DSP) system of the retinal prosthesis. The results show that our image-processing strategies are suitable for a real-time retinal prosthesis and can eliminate redundant information and provide useful information for expression in a low-size image.

Algorithms of Crescent Structure Detection in Human Biological Fluid Facies

NASA Astrophysics Data System (ADS)

Krasheninnikov, V. R.; Malenova, O. E.; Yashina, A. S.

2017-05-01

One of the effective methods of early medical diagnosis is based on the image analysis of human biological fluids. In the process of fluid crystallization there appear characteristic patterns (markers) in the resulting layer (facies). Each marker is a highly probable sign of some pathology even at an early stage of a disease development. When mass health examination is carried out, it is necessary to analyze a large number of images. That is why, the problem of algorithm and software development for automated processing of images is rather urgent nowadays. This paper presents algorithms to detect a crescent structures in images of blood serum and cervical mucus facies. Such a marker indicates the symptoms of ischemic disease. The algorithm presented detects this marker with high probability when the probability of false alarm is low.

Uterus segmentation in dynamic MRI using LBP texture descriptors

NASA Astrophysics Data System (ADS)

Namias, R.; Bellemare, M.-E.; Rahim, M.; Pirró, N.

2014-03-01

Pelvic floor disorders cover pathologies of which physiopathology is not well understood. However cases get prevalent with an ageing population. Within the context of a project aiming at modelization of the dynamics of pelvic organs, we have developed an efficient segmentation process. It aims at alleviating the radiologist with a tedious one by one image analysis. From a first contour delineating the uterus-vagina set, the organ border is tracked along a dynamic mri sequence. The process combines movement prediction, local intensity and texture analysis and active contour geometry control. Movement prediction allows a contour intitialization for next image in the sequence. Intensity analysis provides image-based local contour detection enhanced by local binary pattern (lbp) texture descriptors. Geometry control prohibits self intersections and smoothes the contour. Results show the efficiency of the method with images produced in clinical routine.

Determination of traffic intensity from camera images using image processing and pattern recognition techniques

NASA Astrophysics Data System (ADS)

Mehrübeoğlu, Mehrübe; McLauchlan, Lifford

2006-02-01

The goal of this project was to detect the intensity of traffic on a road at different times of the day during daytime. Although the work presented utilized images from a section of a highway, the results of this project are intended for making decisions on the type of intervention necessary on any given road at different times for traffic control, such as installation of traffic signals, duration of red, green and yellow lights at intersections, and assignment of traffic control officers near school zones or other relevant locations. In this project, directional patterns are used to detect and count the number of cars in traffic images over a fixed area of the road to determine local traffic intensity. Directional patterns are chosen because they are simple and common to almost all moving vehicles. Perspective vision effects specific to each camera orientation has to be considered, as they affect the size and direction of patterns to be recognized. In this work, a simple and fast algorithm has been developed based on horizontal directional pattern matching and perspective vision adjustment. The results of the algorithm under various conditions are presented and compared in this paper. Using the developed algorithm, the traffic intensity can accurately be determined on clear days with average sized cars. The accuracy is reduced on rainy days when the camera lens contains raindrops, when there are very long vehicles, such as trucks or tankers, in the view, and when there is very low light around dusk or dawn.

Live biospeckle laser imaging of root tissues.

PubMed

Braga, Roberto A; Dupuy, L; Pasqual, M; Cardoso, R R

2009-06-01

Live imaging is now a central component for the study of plant developmental processes. Currently, most techniques are extremely constraining: they rely on the marking of specific cellular structures which generally apply to model species because they require genetic transformations. The biospeckle laser (BSL) system was evaluated as an instrument to measure biological activity in plant tissues. The system allows collecting biospeckle patterns from roots which are grown in gels. Laser illumination has been optimized to obtain the images without undesirable specular reflections from the glass tube. Data on two different plant species were obtained and the ability of three different methods to analyze the biospeckle patterns are presented. The results showed that the biospeckle could provide quantitative indicators of the molecular activity from roots which are grown in gel substrate in tissue culture. We also presented a particular experimental configuration and the optimal approach to analyze the images. This may serve as a basis to further works on live BSL in order to study root development.

Computed Tomography 3-D Imaging of the Metal Deformation Flow Path in Friction Stir Welding

NASA Technical Reports Server (NTRS)

Schneider, Judy; Beshears, Ronald; Nunes, Arthur C., Jr.

2005-01-01

In friction stir welding (FSW), a rotating threaded pin tool is inserted into a weld seam and literally stirs the edges of the seam together. To determine optimal processing parameters for producing a defect free weld, a better understanding of the resulting metal deformation flow path is required. Marker studies are the principal method of studying the metal deformation flow path around the FSW pin tool. In our study, we have used computed tomography (CT) scans to reveal the flow pattern of a lead wire embedded in a FSW weld seam. At the welding temperature of aluminum, the lead becomes molten and is carried with the macro-flow of the weld metal. By using CT images, a 3-dimensional (3D) image of the lead flow pattern can be reconstructed. CT imaging was found to be a convenient and comprehensive way of collecting and displaying tracer data. It marks an advance over previous more tedious and ambiguous radiographic/metallographic data collection methods.

Strain Rate Tensor Estimation in Cine Cardiac MRI Based on Elastic Image Registration

NASA Astrophysics Data System (ADS)

Sánchez-Ferrero, Gonzalo Vegas; Vega, Antonio Tristán; Grande, Lucilio Cordero; de La Higuera, Pablo Casaseca; Fernández, Santiago Aja; Fernández, Marcos Martín; López, Carlos Alberola

In this work we propose an alternative method to estimate and visualize the Strain Rate Tensor (SRT) in Magnetic Resonance Images (MRI) when Phase Contrast MRI (PCMRI) and Tagged MRI (TMRI) are not available. This alternative is based on image processing techniques. Concretely, image registration algorithms are used to estimate the movement of the myocardium at each point. Additionally, a consistency checking method is presented to validate the accuracy of the estimates when no golden standard is available. Results prove that the consistency checking method provides an upper bound of the mean squared error of the estimate. Our experiments with real data show that the registration algorithm provides a useful deformation field to estimate the SRT fields. A classification between regional normal and dysfunctional contraction patterns, as compared with experts diagnosis, points out that the parameters extracted from the estimated SRT can represent these patterns. Additionally, a scheme for visualizing and analyzing the local behavior of the SRT field is presented.

LBP based detection of intestinal motility in WCE images

NASA Astrophysics Data System (ADS)

Gallo, Giovanni; Granata, Eliana

2011-03-01

In this research study, a system to support medical analysis of intestinal contractions by processing WCE images is presented. Small intestine contractions are among the motility patterns which reveal many gastrointestinal disorders, such as functional dyspepsia, paralytic ileus, irritable bowel syndrome, bacterial overgrowth. The images have been obtained using the Wireless Capsule Endoscopy (WCE) technique, a patented, video colorimaging disposable capsule. Manual annotation of contractions is an elaborating task, since the recording device of the capsule stores about 50,000 images and contractions might represent only the 1% of the whole video. In this paper we propose the use of Local Binary Pattern (LBP) combined with the powerful textons statistics to find the frames of the video related to contractions. We achieve a sensitivity of about 80% and a specificity of about 99%. The achieved high detection accuracy of the proposed system has provided thus an indication that such intelligent schemes could be used as a supplementary diagnostic tool in endoscopy.

A novel methodology for litho-to-etch pattern fidelity correction for SADP process

NASA Astrophysics Data System (ADS)

Chen, Shr-Jia; Chang, Yu-Cheng; Lin, Arthur; Chang, Yi-Shiang; Lin, Chia-Chi; Lai, Jun-Cheng

2017-03-01

For 2x nm node semiconductor devices and beyond, more aggressive resolution enhancement techniques (RETs) such as source-mask co-optimization (SMO), litho-etch-litho-etch (LELE) and self-aligned double patterning (SADP) are utilized for the low k1 factor lithography processes. In the SADP process, the pattern fidelity is extremely critical since a slight photoresist (PR) top-loss or profile roughness may impact the later core trim process, due to its sensitivity to environment. During the subsequent sidewall formation and core removal processes, the core trim profile weakness may worsen and induces serious defects that affect the final electrical performance. To predict PR top-loss, a rigorous lithography simulation can provide a reference to modify mask layouts; but it takes a much longer run time and is not capable of full-field mask data preparation. In this paper, we first brought out an algorithm which utilizes multi-intensity levels from conventional aerial image simulation to assess the physical profile through lithography to core trim etching steps. Subsequently, a novel correction method was utilized to improve the post-etch pattern fidelity without the litho. process window suffering. The results not only matched PR top-loss in rigorous lithography simulation, but also agreed with post-etch wafer data. Furthermore, this methodology can also be incorporated with OPC and post-OPC verification to improve core trim profile and final pattern fidelity at an early stage.

Gas flow dependence for plasma-needle disinfection of S. mutans bacteria

NASA Astrophysics Data System (ADS)

Goree, J.; Liu, Bin; Drake, David

2006-08-01

The role of gas flow and transport mechanisms are studied for a small low-power impinging jet of weakly-ionized helium at atmospheric pressure. This plasma needle produces a non-thermal glow discharge plasma that kills bacteria. A culture of Streptococcus mutans (S. mutans) was plated onto the surface of agar, and spots on this surface were then treated with plasma. Afterwards, the sample was incubated and then imaged. These images, which serve as a biological diagnostic for characterizing the plasma, show a distinctive spatial pattern for killing that depends on the gas flow rate. As the flow is increased, the killing pattern varies from a solid circle to a ring. Images of the glow reveal that the spatial distribution of energetic electrons corresponds to the observed killing pattern. This suggests that a bactericidal species is generated in the gas phase by energetic electrons less than a millimetre from the sample surface. Mixing of air into the helium plasma is required to generate the observed O and OH radicals in the flowing plasma. Hydrodynamic processes involved in this mixing are buoyancy, diffusion and turbulence.

Finger crease pattern recognition using Legendre moments and principal component analysis

NASA Astrophysics Data System (ADS)

Luo, Rongfang; Lin, Tusheng

2007-03-01

The finger joint lines defined as finger creases and its distribution can identify a person. In this paper, we propose a new finger crease pattern recognition method based on Legendre moments and principal component analysis (PCA). After obtaining the region of interest (ROI) for each finger image in the pre-processing stage, Legendre moments under Radon transform are applied to construct a moment feature matrix from the ROI, which greatly decreases the dimensionality of ROI and can represent principal components of the finger creases quite well. Then, an approach to finger crease pattern recognition is designed based on Karhunen-Loeve (K-L) transform. The method applies PCA to a moment feature matrix rather than the original image matrix to achieve the feature vector. The proposed method has been tested on a database of 824 images from 103 individuals using the nearest neighbor classifier. The accuracy up to 98.584% has been obtained when using 4 samples per class for training. The experimental results demonstrate that our proposed approach is feasible and effective in biometrics.

How the blind "see" Braille: lessons from functional magnetic resonance imaging.

PubMed

Sadato, Norihiro

2005-12-01

What does the visual cortex of the blind do during Braille reading? This process involves converting simple tactile information into meaningful patterns that have lexical and semantic properties. The perceptual processing of Braille might be mediated by the somatosensory system, whereas visual letter identity is accomplished within the visual system in sighted people. Recent advances in functional neuroimaging techniques, such as functional magnetic resonance imaging, have enabled exploration of the neural substrates of Braille reading. The primary visual cortex of early-onset blind subjects is functionally relevant to Braille reading, suggesting that the brain shows remarkable plasticity that potentially permits the additional processing of tactile information in the visual cortical areas.

Research as Repatriation.

ERIC Educational Resources Information Center

Plum, Terry; Smalley, Topsy N.

1994-01-01

Discussion of humanities research focuses on the humanist patron as author of the text. Highlights include the research process; style of expression; interpretation; multivocality; reflexivity; social validation; repatriation; the image of the library for the author; patterns of searching behavior; and reference librarian responses. (37…

Mapping landscape corridors

Treesearch

Peter Vogt; Kurt H. Riitters; Marcin Iwanowski; Christine Estreguil; Jacek Kozak; Pierre Soille

2007-01-01

Corridors are important geographic features for biological conservation and biodiversity assessment. The identification and mapping of corridors is usually based on visual interpretations of movement patterns (functional corridors) or habitat maps (structural corridors). We present a method for automated corridor mapping with morphological image processing, and...

Optical character recognition based on nonredundant correlation measurements.

PubMed

Braunecker, B; Hauck, R; Lohmann, A W

1979-08-15

The essence of character recognition is a comparison between the unknown character and a set of reference patterns. Usually, these reference patterns are all possible characters themselves, the whole alphabet in the case of letter characters. Obviously, N analog measurements are highly redundant, since only K = log(2)N binary decisions are enough to identify one out of N characters. Therefore, we devised K reference patterns accordingly. These patterns, called principal components, are found by digital image processing, but used in an optical analog computer. We will explain the concept of principal components, and we will describe experiments with several optical character recognition systems, based on this concept.

Automatic classification of thermal patterns in diabetic foot based on morphological pattern spectrum

NASA Astrophysics Data System (ADS)

Hernandez-Contreras, D.; Peregrina-Barreto, H.; Rangel-Magdaleno, J.; Ramirez-Cortes, J.; Renero-Carrillo, F.

2015-11-01

This paper presents a novel approach to characterize and identify patterns of temperature in thermographic images of the human foot plant in support of early diagnosis and follow-up of diabetic patients. Composed feature vectors based on 3D morphological pattern spectrum (pecstrum) and relative position, allow the system to quantitatively characterize and discriminate non-diabetic (control) and diabetic (DM) groups. Non-linear classification using neural networks is used for that purpose. A classification rate of 94.33% in average was obtained with the composed feature extraction process proposed in this paper. Performance evaluation and obtained results are presented.

EUV multilayer defect compensation (MDC) by absorber pattern modification: from theory to wafer validation

NASA Astrophysics Data System (ADS)

Pang, Linyong; Hu, Peter; Satake, Masaki; Tolani, Vikram; Peng, Danping; Li, Ying; Chen, Dongxue

2011-11-01

According to the ITRS roadmap, mask defects are among the top technical challenges to introduce extreme ultraviolet (EUV) lithography into production. Making a multilayer defect-free extreme ultraviolet (EUV) blank is not possible today, and is unlikely to happen in the next few years. This means that EUV must work with multilayer defects present on the mask. The method proposed by Luminescent is to compensate effects of multilayer defects on images by modifying the absorber patterns. The effect of a multilayer defect is to distort the images of adjacent absorber patterns. Although the defect cannot be repaired, the images may be restored to their desired targets by changing the absorber patterns. This method was first introduced in our paper at BACUS 2010, which described a simple pixel-based compensation algorithm using a fast multilayer model. The fast model made it possible to complete the compensation calculations in seconds, instead of days or weeks required for rigorous Finite Domain Time Difference (FDTD) simulations. Our SPIE 2011 paper introduced an advanced compensation algorithm using the Level Set Method for 2D absorber patterns. In this paper the method is extended to consider process window, and allow repair tool constraints, such as permitting etching but not deposition. The multilayer defect growth model is also enhanced so that the multilayer defect can be "inverted", or recovered from the top layer profile using a calibrated model.

Improvement of Speckle Contrast Image Processing by an Efficient Algorithm.

PubMed

Steimers, A; Farnung, W; Kohl-Bareis, M

2016-01-01

We demonstrate an efficient algorithm for the temporal and spatial based calculation of speckle contrast for the imaging of blood flow by laser speckle contrast analysis (LASCA). It reduces the numerical complexity of necessary calculations, facilitates a multi-core and many-core implementation of the speckle analysis and enables an independence of temporal or spatial resolution and SNR. The new algorithm was evaluated for both spatial and temporal based analysis of speckle patterns with different image sizes and amounts of recruited pixels as sequential, multi-core and many-core code.

Detection and recognition of simple spatial forms

NASA Technical Reports Server (NTRS)

Watson, A. B.

1983-01-01

A model of human visual sensitivity to spatial patterns is constructed. The model predicts the visibility and discriminability of arbitrary two-dimensional monochrome images. The image is analyzed by a large array of linear feature sensors, which differ in spatial frequency, phase, orientation, and position in the visual field. All sensors have one octave frequency bandwidths, and increase in size linearly with eccentricity. Sensor responses are processed by an ideal Bayesian classifier, subject to uncertainty. The performance of the model is compared to that of the human observer in detecting and discriminating some simple images.

Infrared spectroscopic imaging for noninvasive detection of latent fingerprints.

PubMed

Crane, Nicole J; Bartick, Edward G; Perlman, Rebecca Schwartz; Huffman, Scott

2007-01-01

The capability of Fourier transform infrared (FTIR) spectroscopic imaging to provide detailed images of unprocessed latent fingerprints while also preserving important trace evidence is demonstrated. Unprocessed fingerprints were developed on various porous and nonporous substrates. Data-processing methods used to extract the latent fingerprint ridge pattern from the background material included basic infrared spectroscopic band intensities, addition and subtraction of band intensity measurements, principal components analysis (PCA) and calculation of second derivative band intensities, as well as combinations of these various techniques. Additionally, trace evidence within the fingerprints was recovered and identified.