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Conference on image Sensing Technologies - Materials, Devices, systems, and applications ii

作者： Fang, Joyce Savransky, Dmitry Cornell Univ Sibley Sch Mech & Aerosp Engn Ithaca NY 14853 USA

ISBN: (纸本)9781628415971

An automated alignment optical system will greatly simplify alignment tasks, increase the flexibility and utility of reconfigurable optical systems, and allow for the quick and efficient set up distributed optical systems. In this work, we demonstrate automated alignment of a tilted and decentered focal lens using only focal plane imaging by exploiting the aberration effects caused by the misalignment. A Gaussian beam is passed through the lens with 4 degrees of freedom and onto a science camera. The deformation of the spot image is analyzed to determine the tilt and shift misalignments on the lens. Corrections based on these measurements are applied in closed loop to align the system. We discuss various techniques for mitigating measurement errors, characterizing the system and operating the control loop and present results from the experiment.

关键词： Optical alignment image processing control systems tilt decenter

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Bayesian classifier applications of airborne hyperspectral imagery processing for forested areas

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ADVANCES IN SPACE RESEARCH 2015年第11期55卷 2657-2667页

作者： Kozoderov, Vladimir Kondranin, Timofei Dmitriev, Egor Kamentsev, Vladimir Moscow MV Lomonosov State Univ Moscow Russia Moscow Inst Phys & Technol Dolgoprudnyi Moscow Reg Russia Russian Acad Sci Inst Numer Math Moscow Russia Tver State Univ Tver 170013 Russia

Pattern recognition problem is outlined in the context of textural and spectral analysis of remote sensing imagery processing. Main attention is paid to Bayesian classifier that can be used to realize the processing procedures based on parallel machine-learning algorithms and high-productive computers. We consider the maximum of the posterior probability principle and the formalism of Markov random fields for the neighborhood description of the pixels for the related classes of objects with the emphasis on forests of different species and ages. The energy category of the selected classes serves to account for the likelihood measure between the registered radiances and the theoretical distribution functions approximating remotely sensed data. Optimization procedures are undertaken to solve the pattern recognition problem of the texture description for the forest classes together with finding thin nuances of their spectral distribution in the feature space. As a result, possible redundancy of the channels for imaging spectrometer due to their correlations is removed. Difficulties are revealed due to different sampling data while separating pixels, which characterize the sunlit tops, shaded space and intermediate cases of the Sun illumination conditions on the hyperspectral images. Such separation of pixels for the forest classes is maintained to enhance the recognition accuracy, but learning ensembles of data need to be agreed for these categories of pixels. We present some results of the Bayesian classifier applicability for recognizing airborne hyperspectral images using the relevant improvements in separating such pixels for the forest classes on a test area of the 4 x 10 km size encompassed by 13 airborne tracks, each forming the images by 500 pixels across the track and from 10,000 to 14,000 pixels along the track. The spatial resolution of each image is near to 1 m from the altitude near to 2 km above the ground level. The results of the hyperspectral imagery pr

关键词： Optical remote sensing Pattern recognition Forest classes of different species and ages

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What Can Neuromorphic Event-Driven Precise Timing Add to Spike-Based Pattern Recognition?

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NEURAL COMPUTATION 2015年第3期27卷 561-593页

作者： Akolkar, Himanshu Meyer, Cedric Clady, Zavier Marre, Olivier Bartolozzi, Chiara Panzeri, Stefano Benosman, Ryad Ist Italiano Tecnol ICub Facil I-16163 Genoa Italy Univ Paris 06 Vis Inst F-75252 Paris France Inst Italiano Technol Ctr Neurosci & Cognit Syst I-38068 Rovereto Italy Univ Glasgow Inst Neurosci & Psychol Glasgow G12 8QB Lanark Scotland

This letter introduces a study to precisely measure what an increase in spike timing precision can add to spike-driven pattern recognition algorithms. The concept of generating spikes from images by converting gray levels into spike timings is currently at the basis of almost every spike-based modeling of biological visual systems. The use of images naturally leads to generating incorrect artificial and redundant spike timings and, more important, also contradicts biological findings indicating that visual processing is massively parallel, asynchronous with high temporal resolution. A new concept for acquiring visual information through pixel-individual asynchronous level-crossing sampling has been proposed in a recent generation of asynchronous neuromorphic visual sensors. Unlike conventional cameras, these sensors acquire data not at fixed points in time for the entire array but at fixed amplitude changes of their input, resulting optimally sparse in space and timepixel individually and precisely timed only if new, (previously unknown) information is available (event based). This letter uses the high temporal resolution spiking output of neuromorphic event-based visual sensors to show that lowering time precision degrades performance on several recognition tasks specifically when reaching the conventional range of machine vision acquisition frequencies (30-60Hz). The use of information theory to characterize separability between classes for each temporal resolution shows that high temporal acquisition provides up to 70% more information that conventional spikes generated from frame-based acquisition as used in standard artificial vision, thus drastically increasing the separability between classes of objects. Experiments on real data show that the amount of information loss is correlated with temporal precision. Our information-theoretic study highlights the potentials of neuromorphic asynchronous visual sensors for both practical applications and theoretical inve

关键词： NEURAL networks (Computer science) PATTERN recognition systems COMPUTER algorithms image processing HIGH resolution imaging

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Artificial Intelligence and Soft Computing: 14th International Conference, ICAISC 2015, Zakopane, Poland, June 14-28, 2015, Proceedings, Part ii 1

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丛书名： Lecture Notes in Computer Science 9119

2015年

作者： Leszek Rutkowski, Marcin Korytkowski, Rafal Scherer, Ryszard Tadeusiewicz, Lotfi A. Zadeh, Jacek M. Zurada (eds.)

ISBN: (数字)9783319193687;9783319193694

ISBN: (纸本)9783319193687;9783319193694

The two-volume set LNAI 9119 and LNAI 9120 constitutes the refereed proceedings of the 14th International Conference on Artificial Intelligence and Soft Computing, ICAISC 2015, held in Zakopane, Poland in June 2015. The 142 revised full papers presented in the volumes, were carefully reviewed and selected from 322 submissions. These proceedings present both traditional artificial intelligence methods and soft computing techniques. The goal is to bring together scientists representing both areas of research. The first volume covers topics as follows neural networks and their applications, fuzzy systems and their applications, evolutionary algorithms and their applications, classification and estimation, computer vision, image and speech analysis and the workshop: large-scale visual recognition and machine learning. The second volume has the focus on the following subjects: data mining, bioinformatics, biometrics and medical applications, concurrent and parallel processing, agent systems, robotics and control, artificial intelligence in modeling and simulation and various problems of artificial intelligence.

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image Boundaries Detection: From Thresholding to Implicit Curve Evolution 7

Image Boundaries Detection: From Thresholding to Implicit Cu...

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7th International Conference on Machine Vision (ICMV)

作者： Balla-Arabe, Souleymane Brost, Vincent Yang, Fan Univ Burgundy CNRS UMR LE2I Lab Elect Comp & Imaging Sci Dijon France

ISBN: (纸本)9781628415605

The development of high dimensional large-scale imaging devices increases the need of fast, robust and accurate image segmentation methods. Due to its intrinsic advantages such as the ability to extract complex boundaries, while handling topological changes automatically, the level set method (LSM) has been widely used in boundaries detection. Nevertheless, their computational complexity limits their use for real time systems. Furthermore, most of the LSMs share the limit of leading very often to a local minimum, while the effectiveness of many computer vision applications depends on the whole image boundaries. In this paper, using the image thresholding and the implicit curve evolution frameworks, we design a novel boundaries detection model which handles the above related drawbacks of the LSMs. In order to accelerate the method using the graphics processing units, we use the explicit and highly parallelizable lattice Boltzmann method to solve the level set equation. The introduced algorithm is fast and achieves global image segmentation in a spectacular manner. Experimental results on various kinds of images demonstrate the effectiveness and the efficiency of the proposed method.

关键词： image segmentation partial differential equations implicit curve parallel implementation Thresholding

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A GPU Accelerated Moving Mesh Correspondence Algorithm with applications to RV Segmentation 37

A GPU Accelerated Moving Mesh Correspondence Algorithm with ...

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37th Annual International Conference of the IEEE-Engineering-in-Medicine-and-Biology-Society (EMBC)

作者： Punithakumar, Kumaradevan Noga, Michelle Boulanger, Pierre Univ Alberta Dept Radiol & Diagnost Imaging Edmonton AB T6G 2M7 Canada Mazankowski Alberta Heart Inst Servier Virtual Cardiac Ctr Edmonton AB Canada Univ Alberta Dept Comp Sci Edmonton AB T6G 2M7 Canada

ISBN: (纸本)9781424492701

This study proposes a parallel nonrigid registration algorithm to obtain point correspondence between a sequence of images. Several recent studies have shown that computation of point correspondence is an excellent way to delineate organs from a sequence of images, for example, delineation of cardiac right ventricle (RV) from a series of magnetic resonance (MR) images. However, nonrigid registration algorithms involve optimization of similarity functions, and are therefore, computationally expensive. We propose Graphics processing Unit (GPU) computing to accelerate the algorithm. The proposed approach consists of two parallelization components: 1) parallel Compute Unified Device Architecture (CUDA) version of the non-rigid registration algorithm;and 2) application of an image concatenation approach to further parallelize the algorithm. The proposed approach was evaluated over a data set of 16 subjects and took an average of 4.36 seconds to segment a sequence of 19 MR images, a significant performance improvement over serial image registration approach.

关键词： GPU computing image registration cardiac functional analysis segmentation moving mesh magnetic resonance imaging

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Error analysis for creating 3D face templates based on cylindrical quad-tree structure

Error analysis for creating 3D face templates based on cylin...

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Conference on Photonics applications in Astronomy, Communications, Industry, and High-Energy Physics Experiments

作者： Gutfeter, Weronika Warsaw Univ Technol Inst Control & Computat Engn Warsaw Poland Res & Acad Comp Network NASK Biometr Lab Warsaw Poland

ISBN: (纸本)9781628418804

Development of new biometric algorithms is parallel to advances in technology of sensing devices. Some of the limitations of the current face recognition systems may be eliminated by integrating 3D sensors into these systems. Depth sensing devices can capture a spatial structure of the face in addition to the texture and color. This kind of data is yet usually very voluminous and requires large amount of computer resources for being processed (face scans obtained with typical depth cameras contain more than 150 000 points per face). That is why defining efficient data structures for processing spatial images is crucial for further development of 3D face recognition methods. The concept described in this work fulfills the aforementioned demands. Modification of the quad-tree structure was chosen because it can be easily transformed into less dimensional data structures and maintains spatial relations between data points. We are able to interpret data stored in the tree as a pyramid of features which allow us to analyze face images using coarse-to-fine strategy, often exploited in biometric recognition systems.

关键词： 3D biometrics face recognition spatial image processing RGBD depth cameras

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parallel Implementation of the Multiple Endmember Spectral Mixture Analysis Algorithm for Hyperspectral Unmixing 5

Parallel Implementation of the Multiple Endmember Spectral M...

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Conference on High-Performance Computing in Remote Sensing V

作者： Bernabe, Sergio Igual, Francisco D. Botella, Guillermo Prieto-Matias, Manuel Plaza, Antonio Univ Complutense E-28040 Madrid Spain Univ Extremadura Hyperspectral Comp Lab Caceres Spain

ISBN: (纸本)9781628418569

In the last decade, the issue of endmember variability has received considerable attention, particularly when each pixel is modeled as a linear combination of endmembers or pure materials. As a result, several models and algorithms have been developed for considering the effect of endmember variability in spectral unmixing and possibly include multiple endmembers in the spectral unmixing stage. One of the most popular approach for this purpose is the multiple endmember spectral mixture analysis (MESMA) algorithm. The procedure executed by MESMA can be summarized as follows: (i) First, a standard linear spectral unmixing (LSU) or fully constrained linear spectral unmixing (FCLSU) algorithm is run in an iterative fashion;(ii) Then, we use different endmember combinations, randomly selected from a spectral library, to decompose each mixed pixel;(iii) Finally, the model with the best fit, i.e., with the lowest root mean square error (RMSE) in the reconstruction of the original pixel, is adopted. However, this procedure can be computationally very expensive due to the fact that several endmember combinations need to be tested and several abundance estimation steps need to be conducted, a fact that compromises the use of MESMA in applications under real-time constraints. In this paper we develop (for the first time in the literature) an efficient implementation of MESMA on different platforms using OpenCL, an open standard for parallel programing on heterogeneous systems. Our experiments have been conducted using a simulated data set and the cIMAGMA mathematical library. This kind of implementations with the same descriptive language on different architectures are very important in order to actually calibrate the possibility of using heterogeneous platforms for efficient hyperspectral imaging processing in real remote sensing missions.

关键词： Hyperspectral imaging endmember variability spectral mixture analysis (SMA) multiple endmember spectral mixture analysis (MESMA) high performance computing (HPC) OpenCL

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Can we match Ultraviolet Face images against their Visible Counterparts? 21

Can we match Ultraviolet Face Images against their Visible C...

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Conference on algorithms and Technologies for Multispectral, Hyperspectral, and Ultraspectral imagery xxI

作者： Narang, Neeru Bourlai, Thirimachos Hornak, Lawrence A. W Virginia Univ MILab LCSEE Morgantown WV 26506 USA Univ Georgia Paul D Coverdell Ctr Athens GA 30602 USA

ISBN: (纸本)9781628415889

In law enforcement and security applications, the acquisition of face images is critical in producing key trace evidence for the successful identification of potential threats. However, face recognition (FR) for face images captured using different camera sensors, and under variable illumination conditions, and expressions is very challenging. In this paper, we investigate the advantages and limitations of the heterogeneous problem of matching ultra violet (from 100 nm to 400 mm in wavelength) or UV, face images against their visible (VIS) counterparts, when all face images are captured under controlled conditions. The contributions of our work are three-fold;(i) We used a camera sensor designed with the capability to acquire UV images at short-ranges, and generated a dual-band (VIS and UV) database that is composed of multiple, full frontal, face images of 50 subjects. Two sessions were collected that span over the period of 2 months. (ii) For each dataset, we determined which set of face image pre-processing algorithms are more suitable for face matching, and, finally, (iii) we determined which FR algorithm better matches cross-band face images, resulting in high rank-1 identification rates. Experimental results show that our cross spectral matching (the heterogeneous problem, where gallery and probe sets consist of face images acquired in different spectral bands) algorithms achieve sufficient identification performance. However, we also conclude that the problem under study, is very challenging, and it requires further investigation to address real-world law enforcement or military applications. To the best of our knowledge, this is first time in the open literature the problem of cross-spectral matching of UV against VIS band face images is being investigated.

关键词： Ultra-Violet (UV) imaging Face Recognition image Preprocessing Intra-spectral Cross-spectral Distance Metrics

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Integration of optical functionality for image sensing through sub-wavelength geometry design 2

Integration of optical functionality for image sensing throu...

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Conference on image Sensing Technologies - Materials, Devices, systems, and applications ii

作者： Catrysse, Peter B. Stanford Univ Edward L Ginzton Lab Stanford CA 94305 USA Stanford Univ Dept Elect Engn Stanford CA 94305 USA

ISBN: (纸本)9781628415971

Integration and pixel scaling are enabling trends for low-cost, small form-factor, light-weight, and low-power camera systems across all optical frequency bands. Integration allows on-chip implementations of optical functionalities, e.g., polarization, color and spectral selectivity, which were previously achieved using bulky external components (e.g., prisms, filter wheels). Wavelength-size pixels require focusing and guiding of light at the pixel-level (e.g., micro-lenses, light guides), which was not necessary for larger pixels. On-chip integration of optical functionalities and pixel-level light control is often based on miniaturized versions of conventional optical components. These components derive their functionality from material properties or shapes, but do not lend themselves well to integration or scale to wavelengthsize pixels. Here, I present an overview of innovative integrated optical devices that overcome the problems associated with the integration and scaling of conventional components. They are enabled by scaling of imager and focal plane array technology, and by advanced nanofabrication. Wafer-scale processing and nanofabrication have made nano-scale patterning possible, while recent discoveries regarding the optical properties of nano-patterned structures have opened up important opportunities to develop ultra-compact photonic devices. I discuss design implementations for the visible (VIS) and infrared (IR) wavelength bands, including VIS integrated color pixels (ICPs) in a complementary metal-oxide semiconductor (CMOS) technology with geometry-based color filters, micro-lens functionality based on planar nanoaperture designs, and metal-based spectral filters for mid-wave IR (MWIR) multispectral imaging that can be implemented using standard nanofabrication methods. The devices are planar and/or ultra-thin, rely on process-compatible materials only, and derive their functionality from sub-wavelength geometry design.

关键词： Nanophotonics image sensors focal plane arrays integrated micro-optical devices sub-wavelength structures

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