Texture Feature Extraction Techniques For Image Recognition
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Texture Feature Extraction Techniques For Image Recognition
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Author : Jyotismita Chaki
language : en
Publisher: Springer Nature
Release Date : 2019-10-24
Texture Feature Extraction Techniques For Image Recognition written by Jyotismita Chaki and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-10-24 with Technology & Engineering categories.
The book describes various texture feature extraction approaches and texture analysis applications. It introduces and discusses the importance of texture features, and describes various types of texture features like statistical, structural, signal-processed and model-based. It also covers applications related to texture features, such as facial imaging. It is a valuable resource for machine vision researchers and practitioners in different application areas.
Image Texture Analysis
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Author : Chih-Cheng Hung
language : en
Publisher: Springer
Release Date : 2019-06-05
Image Texture Analysis written by Chih-Cheng Hung and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-06-05 with Computers categories.
This useful textbook/reference presents an accessible primer on the fundamentals of image texture analysis, as well as an introduction to the K-views model for extracting and classifying image textures. Divided into three parts, the book opens with a review of existing models and algorithms for image texture analysis, before delving into the details of the K-views model. The work then concludes with a discussion of popular deep learning methods for image texture analysis. Topics and features: provides self-test exercises in every chapter; describes the basics of image texture, texture features, and image texture classification and segmentation; examines a selection of widely-used methods for measuring and extracting texture features, and various algorithms for texture classification; explains the concepts of dimensionality reduction and sparse representation; discusses view-based approaches to classifying images; introduces the template for the K-views algorithm, as well as a range of variants of this algorithm; reviews several neural network models for deep machine learning, and presents a specific focus on convolutional neural networks. This introductory text on image texture analysis is ideally suitable for senior undergraduate and first-year graduate students of computer science, who will benefit from the numerous clarifying examples provided throughout the work.
Image Color Feature Extraction Techniques
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Author : Jyotismita Chaki
language : en
Publisher: Springer Nature
Release Date : 2020-06-03
Image Color Feature Extraction Techniques written by Jyotismita Chaki and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-06-03 with Technology & Engineering categories.
This book introduces a range of image color feature extraction techniques. Readers are encouraged to try implementing the techniques discussed here on their own, all of which are presented in a very simple and step-by-step manner. In addition, the book can be used as an introduction to image color feature techniques for those who are new to the research field and software. The techniques are very easy to understand as most of them are described with pictorial examples. Not only the techniques themselves, but also their applications are covered. Accordingly, the book offers a valuable guide to these tools, which are a vital component of content-based image retrieval (CBIR).
Feature Extraction And Image Processing For Computer Vision
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Author : Mark Nixon
language : en
Publisher: Academic Press
Release Date : 2012-12-18
Feature Extraction And Image Processing For Computer Vision written by Mark Nixon and has been published by Academic Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012-12-18 with Computers categories.
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
Feature Extraction And Image Processing
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Author : Mark Nixon
language : en
Publisher: Elsevier
Release Date : 2013-10-22
Feature Extraction And Image Processing written by Mark Nixon and has been published by Elsevier this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013-10-22 with Computers categories.
Focusing on feature extraction while also covering issues and techniques such as image acquisition, sampling theory, point operations and low-level feature extraction, the authors have a clear and coherent approach that will appeal to a wide range of students and professionals. Ideal module text for courses in artificial intelligence, image processing and computer vision Essential reading for engineers and academics working in this cutting-edge field Supported by free software on a companion website
Handbook Of Pattern Recognition And Computer Vision
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Author : C. H. Chen
language : en
Publisher: World Scientific
Release Date : 1999
Handbook Of Pattern Recognition And Computer Vision written by C. H. Chen and has been published by World Scientific this book supported file pdf, txt, epub, kindle and other format this book has been release on 1999 with Computers categories.
The very significant advances in computer vision and pattern recognition and their applications in the last few years reflect the strong and growing interest in the field as well as the many opportunities and challenges it offers. The second edition of this handbook represents both the latest progress and updated knowledge in this dynamic field. The applications and technological issues are particularly emphasized in this edition to reflect the wide applicability of the field in many practical problems. To keep the book in a single volume, it is not possible to retain all chapters of the first edition. However, the chapters of both editions are well written for permanent reference.
Handbook Of Texture Analysis
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Author : Majid Mirmehdi
language : en
Publisher: World Scientific
Release Date : 2008-10-28
Handbook Of Texture Analysis written by Majid Mirmehdi and has been published by World Scientific this book supported file pdf, txt, epub, kindle and other format this book has been release on 2008-10-28 with Computers categories.
Texture analysis is one of the fundamental aspects of human vision by which we discriminate between surfaces and objects. In a similar manner, computer vision can take advantage of the cues provided by surface texture to distinguish and recognize objects. In computer vision, texture analysis may be used alone or in combination with other sensed features (e.g. color, shape, or motion) to perform the task of recognition. Either way, it is a feature of paramount importance and boasts a tremendous body of work in terms of both research and applications.Currently, the main approaches to texture analysis must be sought out through a variety of research papers. This collection of chapters brings together in one handy volume the major topics of importance, and categorizes the various techniques into comprehensible concepts. The methods covered will not only be relevant to those working in computer vision, but will also be of benefit to the computer graphics, psychophysics, and pattern recognition communities, academic or industrial./a
Feature Extraction And Image Processing For Computer Vision
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Author : Mark Nixon
language : en
Publisher: Academic Press
Release Date : 2019-11-17
Feature Extraction And Image Processing For Computer Vision written by Mark Nixon and has been published by Academic Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-11-17 with Computers categories.
Feature Extraction for Image Processing and Computer Vision is an essential guide to the implementation of image processing and computer vision techniques, with tutorial introductions and sample code in MATLAB and Python. 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 link between theory and exemplar code of the algorithms." Essential background theory is carefully explained. This text gives students and researchers in image processing and computer vision a complete introduction to classic and state-of-the art methods in feature extraction together with practical guidance on their implementation. The only text to concentrate on feature extraction with working implementation and worked through mathematical derivations and algorithmic methods A thorough overview of available feature extraction methods including essential background theory, shape methods, texture and deep learning Up to date coverage of interest point detection, feature extraction and description and image representation (including frequency domain and colour) Good balance between providing a mathematical background and practical implementation Detailed and explanatory of algorithms in MATLAB and Python
A Beginner S Guide To Image Shape Feature Extraction Techniques
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Author : Jyotismita Chaki
language : en
Publisher: CRC Press
Release Date : 2019-07-25
A Beginner S Guide To Image Shape Feature Extraction Techniques written by Jyotismita Chaki and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-07-25 with Computers categories.
This book emphasizes various image shape feature extraction methods which are necessary for image shape recognition and classification. Focussing on a shape feature extraction technique used in content-based image retrieval (CBIR), it explains different applications of image shape features in the field of content-based image retrieval. Showcasing useful applications and illustrating examples in many interdisciplinary fields, the present book is aimed at researchers and graduate students in electrical engineering, data science, computer science, medicine, and machine learning including medical physics and information technology.
Image Feature Detectors And Descriptors
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Author : Ali Ismail Awad
language : en
Publisher: Springer
Release Date : 2016-02-22
Image Feature Detectors And Descriptors written by Ali Ismail Awad and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016-02-22 with Technology & Engineering categories.
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.