Image Feature Detection and Matching for Biological Object Recognition

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ISBN 13 :
Total Pages : 292 pages
Book Rating : 4.:/5 (173 download)

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Book Synopsis Image Feature Detection and Matching for Biological Object Recognition by : Hongli Deng

Download or read book Image Feature Detection and Matching for Biological Object Recognition written by Hongli Deng and published by . This book was released on 2008 with total page 292 pages. Available in PDF, EPUB and Kindle. Book excerpt: Image feature detection and matching are two critical processes for many computer vision tasks. Currently, intensity-based local interest region detectors and local feature-based matching methods are used widely in computer vision applications. But in some applications, such as biological object recognition tasks, within-class changes in pose, lighting, color, and texture can cause considerable variation of local intensity. Consequently, object recognition systems based on intensity-based interest region detectors often fail. This dissertation proposes a new structure-based local interest region detector called principal curvature-based region detector (PCBR) that detects stable watershed regions within the multi-scale principal curvature images. This detector typically detects distinctive patterns distributed evenly on the objects and it shows significant robustness to local intensity perturbation and intra-class variation. Second, this thesis develops a local feature matching algorithm that augments the SIFT descriptor with a global context feature vector containing curvilinear shape information from a much larger neighborhood to resolve ambiguity in matching. Moreover, this thesis further improves the matching method to make it robust to occlusion, clutter, and non-rigid transformation by defining affine-invariant log-polar elliptical context and employing a reinforcement matching scheme. Results show that our new detector and matching algorithms improve recognition accuracy and are well suited for biological object recognition tasks.

Matching Algorithms and Feature Match Quality Measures for Model-based Object Recognition with Applications to Automatic Target Recognition

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ISBN 13 :
Total Pages : 196 pages
Book Rating : 4.:/5 (549 download)

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Book Synopsis Matching Algorithms and Feature Match Quality Measures for Model-based Object Recognition with Applications to Automatic Target Recognition by : Martin Garcia Keller

Download or read book Matching Algorithms and Feature Match Quality Measures for Model-based Object Recognition with Applications to Automatic Target Recognition written by Martin Garcia Keller and published by . This book was released on 1999 with total page 196 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Image Feature Detectors and Descriptors

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Publisher : Springer
ISBN 13 : 3319288547
Total Pages : 437 pages
Book Rating : 4.3/5 (192 download)

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Book Synopsis Image Feature Detectors and Descriptors by : Ali Ismail Awad

Download or read book Image Feature Detectors and Descriptors written by Ali Ismail Awad and published by Springer. This book was released on 2016-02-22 with total page 437 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides readers with a selection of high-quality chapters that cover both theoretical concepts and practical applications of image feature detectors and descriptors. It serves as reference for researchers and practitioners by featuring survey chapters and research contributions on image feature detectors and descriptors. Additionally, it emphasizes several keywords in both theoretical and practical aspects of image feature extraction. The keywords include acceleration of feature detection and extraction, hardware implantations, image segmentation, evolutionary algorithm, ordinal measures, as well as visual speech recognition.

Image Analysis and Recognition

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Publisher : Springer
ISBN 13 : 3540698124
Total Pages : 1146 pages
Book Rating : 4.5/5 (46 download)

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Book Synopsis Image Analysis and Recognition by : Aurelio Campilho

Download or read book Image Analysis and Recognition written by Aurelio Campilho and published by Springer. This book was released on 2008-06-25 with total page 1146 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refereed proceedings of the 5th International Conference on Image Analysis and Recognition, ICIAR 2008, held in Póvoa do Varzim, Portugal, in June 2008. The 110 revised full papers presented together with 2 invited papers were carefully reviewed and selected from 226 submissions. The papers are organized in topical sections on image restoration and enhancement, image and video segmentation, non-linear image processing, image and video coding and encryption, indexing and retrieval, computer vision, feature extraction and classification, shape representation and matching, object recognition, character recognition, texture and motion analysis, tracking, biomedical image analysis, biometrics, face recognition, and a special session on recent advances in multimodal biometric systems and applications.

Image Features and Learning Algorithms for Biological, Generic and Social Object Recognition

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ISBN 13 :
Total Pages : 274 pages
Book Rating : 4.:/5 (317 download)

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Book Synopsis Image Features and Learning Algorithms for Biological, Generic and Social Object Recognition by : Wei Zhang

Download or read book Image Features and Learning Algorithms for Biological, Generic and Social Object Recognition written by Wei Zhang and published by . This book was released on 2009 with total page 274 pages. Available in PDF, EPUB and Kindle. Book excerpt: Automated recognition of object categories in images is a critical step for many real-world computer vision applications. Interest region detectors and region descriptors have been widely employed to tackle the variability of objects in pose, scale, lighting, texture, color, and so on. Different types of object recognition problems usually require different image features and corresponding learning algorithms. This dissertation focuses on the design, evaluation and application of new image features and learning algorithms for the recognition of biological, generic and social objects. The first part of the dissertation introduces a new structure-based interest region detector called the principal curvature-based region detector (PCBR) which detects stable watershed regions that are robust to local intensity perturbations. This detector is specifically designed for region detection for biological objects. Several recognition architectures are then developed that fuse visual information from disparate types of image features for the categorization of complex objects. The described image features and learning algorithms achieve excellent performance on the difficult stonefly larvae dataset. The second part of the dissertation presents studies of methods for visual codebook learning and their application to object recognition. The dissertation first introduces the methodology and application of generative visual codebooks for stonefly recognition and introduces a discriminative evaluation methodology based on a maximum mutual information criterion. Then a new generative/discriminative visual codebook learning algorithm, called iterative discriminative clustering (IDC), is presented that refines the centers and the shapes of the generative codewords for improved discriminative power. It is followed by a novel codebook learning algorithm that builds multiple codebooks that are non-redundant in discriminative power. All these visual codebook learning algorithms achieve high performance on both biological and generic object recognition tasks. The final part of the dissertation describes a socially-driven clothes recognition system for an intelligent fitting-room system. The dissertation presents the results of a user study to identify the key factors for clothes recognition. It then describes learning algorithms for recognizing these key factors from clothes images using various image features. The clothes recognition system successfully enables automated social fashion information retrieval for an enhanced clothes shopping experience.

Feature Extraction and Image Processing for Computer Vision

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Publisher : Academic Press
ISBN 13 : 0123978246
Total Pages : 629 pages
Book Rating : 4.1/5 (239 download)

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Book Synopsis Feature Extraction and Image Processing for Computer Vision by : Mark Nixon

Download or read book Feature Extraction and Image Processing for Computer Vision written by Mark Nixon and published by Academic Press. This book was released on 2012-12-18 with total page 629 pages. Available in PDF, EPUB and Kindle. Book excerpt: Feature Extraction and Image Processing for Computer Vision is an essential guide to the implementation of image processing and computer vision techniques, with tutorial introductions and sample code in Matlab. Algorithms are presented and fully explained to enable complete understanding of the methods and techniques demonstrated. As one reviewer noted, "The main strength of the proposed book is the exemplar code of the algorithms." Fully updated with the latest developments in feature extraction, including expanded tutorials and new techniques, this new edition contains extensive new material on Haar wavelets, Viola-Jones, bilateral filtering, SURF, PCA-SIFT, moving object detection and tracking, development of symmetry operators, LBP texture analysis, Adaboost, and a new appendix on color models. Coverage of distance measures, feature detectors, wavelets, level sets and texture tutorials has been extended. - Named a 2012 Notable Computer Book for Computing Methodologies by Computing Reviews - Essential reading for engineers and students working in this cutting-edge field - Ideal module text and background reference for courses in image processing and computer vision - The only currently available text to concentrate on feature extraction with working implementation and worked through derivation

Object Recognition

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Publisher : Springer Science & Business Media
ISBN 13 : 9781852333980
Total Pages : 376 pages
Book Rating : 4.3/5 (339 download)

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Book Synopsis Object Recognition by : M. Bennamoun

Download or read book Object Recognition written by M. Bennamoun and published by Springer Science & Business Media. This book was released on 2001-12-12 with total page 376 pages. Available in PDF, EPUB and Kindle. Book excerpt: Automatie object recognition is a multidisciplinary research area using con cepts and tools from mathematics, computing, optics, psychology, pattern recognition, artificial intelligence and various other disciplines. The purpose of this research is to provide a set of coherent paradigms and algorithms for the purpose of designing systems that will ultimately emulate the functions performed by the Human Visual System (HVS). Hence, such systems should have the ability to recognise objects in two or three dimensions independently of their positions, orientations or scales in the image. The HVS is employed for tens of thousands of recognition events each day, ranging from navigation (through the recognition of landmarks or signs), right through to communication (through the recognition of characters or people themselves). Hence, the motivations behind the construction of recognition systems, which have the ability to function in the real world, is unquestionable and would serve industrial (e.g. quality control), military (e.g. automatie target recognition) and community needs (e.g. aiding the visually impaired). Scope, Content and Organisation of this Book This book provides a comprehensive, yet readable foundation to the field of object recognition from which research may be initiated or guided. It repre sents the culmination of research topics that I have either covered personally or in conjunction with my PhD students. These areas include image acqui sition, 3-D object reconstruction, object modelling, and the matching of ob jects, all of which are essential in the construction of an object recognition system.

Advances in Computer Vision and Computational Biology

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Publisher : Springer Nature
ISBN 13 : 3030710513
Total Pages : 903 pages
Book Rating : 4.0/5 (37 download)

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Book Synopsis Advances in Computer Vision and Computational Biology by : Hamid R. Arabnia

Download or read book Advances in Computer Vision and Computational Biology written by Hamid R. Arabnia and published by Springer Nature. This book was released on 2021-08-05 with total page 903 pages. Available in PDF, EPUB and Kindle. Book excerpt: The book presents the proceedings of four conferences: The 24th International Conference on Image Processing, Computer Vision, & Pattern Recognition (IPCV'20), The 6th International Conference on Health Informatics and Medical Systems (HIMS'20), The 21st International Conference on Bioinformatics & Computational Biology (BIOCOMP'20), and The 6th International Conference on Biomedical Engineering and Sciences (BIOENG'20). The conferences took place in Las Vegas, NV, USA, July 27-30, 2020, and are part of the larger 2020 World Congress in Computer Science, Computer Engineering, & Applied Computing (CSCE'20), which features 20 major tracks. Authors include academics, researchers, professionals, and students. Presents the proceedings of four conferences as part of the 2020 World Congress in Computer Science, Computer Engineering, & Applied Computing (CSCE'20); Includes the tracks on Image Processing, Computer Vision, & Pattern Recognition, Health Informatics & Medical Systems, Bioinformatics, Computational Biology & Biomedical Engineering; Features papers from IPCV'20, HIMS'20, BIOCOMP'20, and BIOENG'20.

Object Recognition Of Digital Images In Wavelet Neural Network

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Publisher : Archers & Elevators Publishing House
ISBN 13 : 9386501244
Total Pages : pages
Book Rating : 4.3/5 (865 download)

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Book Synopsis Object Recognition Of Digital Images In Wavelet Neural Network by : Arul Murugan R

Download or read book Object Recognition Of Digital Images In Wavelet Neural Network written by Arul Murugan R and published by Archers & Elevators Publishing House. This book was released on with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:

Object Detection and Recognition in Digital Images

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Publisher : John Wiley & Sons
ISBN 13 : 111861836X
Total Pages : 518 pages
Book Rating : 4.1/5 (186 download)

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Book Synopsis Object Detection and Recognition in Digital Images by : Boguslaw Cyganek

Download or read book Object Detection and Recognition in Digital Images written by Boguslaw Cyganek and published by John Wiley & Sons. This book was released on 2013-05-20 with total page 518 pages. Available in PDF, EPUB and Kindle. Book excerpt: Object detection, tracking and recognition in images are key problems in computer vision. This book provides the reader with a balanced treatment between the theory and practice of selected methods in these areas to make the book accessible to a range of researchers, engineers, developers and postgraduate students working in computer vision and related fields. Key features: Explains the main theoretical ideas behind each method (which are augmented with a rigorous mathematical derivation of the formulas), their implementation (in C++) and demonstrated working in real applications. Places an emphasis on tensor and statistical based approaches within object detection and recognition. Provides an overview of image clustering and classification methods which includes subspace and kernel based processing, mean shift and Kalman filter, neural networks, and k-means methods. Contains numerous case study examples of mainly automotive applications. Includes a companion website hosting full C++ implementation, of topics presented in the book as a software library, and an accompanying manual to the software platform.

Visual Object Recognition

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Publisher : Morgan & Claypool Publishers
ISBN 13 : 1598299689
Total Pages : 184 pages
Book Rating : 4.5/5 (982 download)

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Book Synopsis Visual Object Recognition by : Kristen Grauman

Download or read book Visual Object Recognition written by Kristen Grauman and published by Morgan & Claypool Publishers. This book was released on 2011 with total page 184 pages. Available in PDF, EPUB and Kindle. Book excerpt: The visual recognition problem is central to computer vision research. From robotics to information retrieval, many desired applications demand the ability to identify and localize categories, places, and objects. This tutorial overviews computer vision algorithms for visual object recognition and image classification. We introduce primary representations and learning approaches, with an emphasis on recent advances in the field. The target audience consists of researchers or students working in AI, robotics, or vision who would like to understand what methods and representations are available for these problems. This lecture summarizes what is and isn't possible to do reliably today, and overviews key concepts that could be employed in systems requiring visual categorization. Table of Contents: Introduction / Overview: Recognition of Specific Objects / Local Features: Detection and Description / Matching Local Features / Geometric Verification of Matched Features / Example Systems: Specific-Object Recognition / Overview: Recognition of Generic Object Categories / Representations for Object Categories / Generic Object Detection: Finding and Scoring Candidates / Learning Generic Object Category Models / Example Systems: Generic Object Recognition / Other Considerations and Current Challenges / Conclusions

A Biological Model of Object Recognition with Feature Learning

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Publisher :
ISBN 13 :
Total Pages : 59 pages
Book Rating : 4.:/5 (53 download)

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Book Synopsis A Biological Model of Object Recognition with Feature Learning by : Jennifer Louie

Download or read book A Biological Model of Object Recognition with Feature Learning written by Jennifer Louie and published by . This book was released on 2003 with total page 59 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Image Analysis for the Biological Sciences

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Publisher :
ISBN 13 :
Total Pages : 248 pages
Book Rating : 4.3/5 (91 download)

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Book Synopsis Image Analysis for the Biological Sciences by : C. A. Glasbey

Download or read book Image Analysis for the Biological Sciences written by C. A. Glasbey and published by . This book was released on 1995-08-08 with total page 248 pages. Available in PDF, EPUB and Kindle. Book excerpt: Covering the basics of quantitative image analysis - the extraction of information from data in the form of pictures - this study places special emphasis on methods relevant to environmental scientists. Practical examples from various fields are introduced to demonstrate applications.

An Introduction to Object Recognition

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Publisher : Springer Science & Business Media
ISBN 13 : 1849962359
Total Pages : 210 pages
Book Rating : 4.8/5 (499 download)

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Book Synopsis An Introduction to Object Recognition by : Marco Alexander Treiber

Download or read book An Introduction to Object Recognition written by Marco Alexander Treiber and published by Springer Science & Business Media. This book was released on 2010-07-23 with total page 210 pages. Available in PDF, EPUB and Kindle. Book excerpt: Rapid development of computer hardware has enabled usage of automatic object recognition in an increasing number of applications, ranging from industrial image processing to medical applications, as well as tasks triggered by the widespread use of the internet. Each area of application has its specific requirements, and consequently these cannot all be tackled appropriately by a single, general-purpose algorithm. This easy-to-read text/reference provides a comprehensive introduction to the field of object recognition (OR). The book presents an overview of the diverse applications for OR and highlights important algorithm classes, presenting representative example algorithms for each class. The presentation of each algorithm describes the basic algorithm flow in detail, complete with graphical illustrations. Pseudocode implementations are also included for many of the methods, and definitions are supplied for terms which may be unfamiliar to the novice reader. Supporting a clear and intuitive tutorial style, the usage of mathematics is kept to a minimum. Topics and features: presents example algorithms covering global approaches, transformation-search-based methods, geometrical model driven methods, 3D object recognition schemes, flexible contour fitting algorithms, and descriptor-based methods; explores each method in its entirety, rather than focusing on individual steps in isolation, with a detailed description of the flow of each algorithm, including graphical illustrations; explains the important concepts at length in a simple-to-understand style, with a minimum usage of mathematics; discusses a broad spectrum of applications, including some examples from commercial products; contains appendices discussing topics related to OR and widely used in the algorithms, (but not at the core of the methods described in the chapters). Practitioners of industrial image processing will find this simple introduction and overview to OR a valuable reference, as will graduate students in computer vision courses. Marco Treiber is a software developer at Siemens Electronics Assembly Systems, Munich, Germany, where he is Technical Lead in Image Processing for the Vision System of SiPlace placement machines, used in SMT assembly.

A Selection of Image Analysis Techniques

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Publisher : CRC Press
ISBN 13 : 1000689425
Total Pages : 363 pages
Book Rating : 4.0/5 (6 download)

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Book Synopsis A Selection of Image Analysis Techniques by : Yu-Jin Zhang

Download or read book A Selection of Image Analysis Techniques written by Yu-Jin Zhang and published by CRC Press. This book was released on 2022-10-05 with total page 363 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book focuses on seven commonly used image analysis techniques. It covers aspects from basic principles and practical methods, to new advancement of each selected technique to help readers solve image‐processing related problems in real-life situations. The selected techniques include image segmentation, segmentation evaluation and comparison, saliency object detection, motion analysis, mathematical morphology methods, face recognition and expression classification. The author offers readers a three‐step strategy toward problem‐solving: first, essential principles; then, a detailed explanation; and finally, a discussion on practical and working techniques for specific tasks. He also encourages readers to make full use of available materials from the latest developments and trends. This is an excellent book for those who do not have a complete foundation in image technology but need to use image analysis techniques to perform specific tasks in particular applications.

Toward Category-Level Object Recognition

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Publisher : Springer
ISBN 13 : 3540687955
Total Pages : 622 pages
Book Rating : 4.5/5 (46 download)

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Book Synopsis Toward Category-Level Object Recognition by : Jean Ponce

Download or read book Toward Category-Level Object Recognition written by Jean Ponce and published by Springer. This book was released on 2007-01-25 with total page 622 pages. Available in PDF, EPUB and Kindle. Book excerpt: This volume is a post-event proceedings volume and contains selected papers based on presentations given, and vivid discussions held, during two workshops held in Taormina in 2003 and 2004. The 30 thoroughly revised papers presented are organized in the following topical sections: recognition of specific objects, recognition of object categories, recognition of object categories with geometric relations, and joint recognition and segmentation.

Shape Detection in Computer Vision Using the Hough Transform

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Publisher : Springer Science & Business Media
ISBN 13 : 1447119401
Total Pages : 210 pages
Book Rating : 4.4/5 (471 download)

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Book Synopsis Shape Detection in Computer Vision Using the Hough Transform by : V.F. Leavers

Download or read book Shape Detection in Computer Vision Using the Hough Transform written by V.F. Leavers and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 210 pages. Available in PDF, EPUB and Kindle. Book excerpt: Shape detection techniques are an important aspect of computer vision and are used to transform raw image data into the symbolic representations needed for object recognition and location. However, the availability and application of research data relating to shape detection has traditionally been limited by a lack of computational and mathematical skill on the part of the intended end-user. As a result progress in areas such as the automation of visual inspection techniques, where shape detection couls play a pivotal role, has been relatively slow. In this volume, Violet Leavers, an established author and researcher in the field, examines the Hough Transform, a technique which is particularly relevant to industrial applications. By making computational recipes and advice available to the non-specialist, the book aims to popularize the technique, and to provide a bridge between low level computer vision tasks and specialist applications. In addition, Shape Detection in Computer Vision Using the Hough Transform assesses practical and theoretical issues which were previously only available in scientific literature in a way which is easily accessible to the non-specialist user. Shape Detection in Computer Vision Using the Hough Transform fills an obvious gap in the existing market. It is an important textbook which will provide postgraduate students with a thorough grounding in the field, and will also be of interest to junior research staff and program designers.