Image Texture Analysis, 1st ed. 2019 Foundations, Models and Algorithms

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.

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.

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

Convolutional Neural Networks and Texture Classification

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.

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