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Image Texture Analysis
Foundations, Models and Algorithms
Buch von Chih-Cheng Hung (u. a.)
Sprache: Englisch

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Beschreibung
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.
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.
Über den Autor

Dr. Chih-Cheng Hung is a Tenured Professor of Computer Science in the College of Computing and Software Engineering at Kennesaw State University, where he serves as the Director of the Center for Machine Vision and Security Research. He also holds the position of YinDu Scholar at Anyang Normal University, China.

Dr. Enmin Song is a Professor and Director of the Department of Computer Science and Application at Huazhong University of Science and Technology, Wuhan, China.

Dr. Yihua Lan is an Associate Professor of Computer Science in the School of Computer and Information Technology at Nanyang Normal University, China.

Zusammenfassung

Reviews the state of the art in models and algorithms for texture analysis, including deep learning and image texture analysis

Introduces the K-View model and its advanced models, highlighting the benefits offered by these models

Discusses the theory, explains the necessary mathematics, and describes the implementation of the algorithms

Inhaltsverzeichnis

Part I: Existing Models and Algorithms for Image Texture.- Image Texture, Texture Features, and Image Texture Classification and Segmentation.- Texture Features and Image Texture Models.- Algorithms for Image Texture Classification.- Dimensionality Reduction and Sparse Representation.- Part II: The K-Views Models and Algorithms.- Basic Concept and Models of the K-Views.- Using Datagram in the K-Views Model.- Features-Based K-Views Model.- Advanced K-Views Algorithms.- Part III: Deep Machine Learning Models for Image Texture Analysis.- Foundations of Deep Machine Learning in Neural Networks.- Convolutional Neural Networks and Texture Classification.

Details
Erscheinungsjahr: 2019
Fachbereich: Anwendungs-Software
Genre: Informatik
Rubrik: Naturwissenschaften & Technik
Medium: Buch
Seiten: 272
Inhalt: xii
258 S.
69 s/w Illustr.
73 farbige Illustr.
258 p. 142 illus.
73 illus. in color.
ISBN-13: 9783030137724
ISBN-10: 3030137724
Sprache: Englisch
Herstellernummer: 978-3-030-13772-4
Ausstattung / Beilage: HC runder Rücken kaschiert
Einband: Gebunden
Autor: Hung, Chih-Cheng
Lan, Yihua
Song, Enmin
Auflage: 1st ed. 2019
Hersteller: Springer International Publishing
Springer International Publishing AG
Maße: 241 x 160 x 21 mm
Von/Mit: Chih-Cheng Hung (u. a.)
Erscheinungsdatum: 17.06.2019
Gewicht: 0,576 kg
preigu-id: 115309571
Über den Autor

Dr. Chih-Cheng Hung is a Tenured Professor of Computer Science in the College of Computing and Software Engineering at Kennesaw State University, where he serves as the Director of the Center for Machine Vision and Security Research. He also holds the position of YinDu Scholar at Anyang Normal University, China.

Dr. Enmin Song is a Professor and Director of the Department of Computer Science and Application at Huazhong University of Science and Technology, Wuhan, China.

Dr. Yihua Lan is an Associate Professor of Computer Science in the School of Computer and Information Technology at Nanyang Normal University, China.

Zusammenfassung

Reviews the state of the art in models and algorithms for texture analysis, including deep learning and image texture analysis

Introduces the K-View model and its advanced models, highlighting the benefits offered by these models

Discusses the theory, explains the necessary mathematics, and describes the implementation of the algorithms

Inhaltsverzeichnis

Part I: Existing Models and Algorithms for Image Texture.- Image Texture, Texture Features, and Image Texture Classification and Segmentation.- Texture Features and Image Texture Models.- Algorithms for Image Texture Classification.- Dimensionality Reduction and Sparse Representation.- Part II: The K-Views Models and Algorithms.- Basic Concept and Models of the K-Views.- Using Datagram in the K-Views Model.- Features-Based K-Views Model.- Advanced K-Views Algorithms.- Part III: Deep Machine Learning Models for Image Texture Analysis.- Foundations of Deep Machine Learning in Neural Networks.- Convolutional Neural Networks and Texture Classification.

Details
Erscheinungsjahr: 2019
Fachbereich: Anwendungs-Software
Genre: Informatik
Rubrik: Naturwissenschaften & Technik
Medium: Buch
Seiten: 272
Inhalt: xii
258 S.
69 s/w Illustr.
73 farbige Illustr.
258 p. 142 illus.
73 illus. in color.
ISBN-13: 9783030137724
ISBN-10: 3030137724
Sprache: Englisch
Herstellernummer: 978-3-030-13772-4
Ausstattung / Beilage: HC runder Rücken kaschiert
Einband: Gebunden
Autor: Hung, Chih-Cheng
Lan, Yihua
Song, Enmin
Auflage: 1st ed. 2019
Hersteller: Springer International Publishing
Springer International Publishing AG
Maße: 241 x 160 x 21 mm
Von/Mit: Chih-Cheng Hung (u. a.)
Erscheinungsdatum: 17.06.2019
Gewicht: 0,576 kg
preigu-id: 115309571
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