Advertisement

Image Texture Analysis

Foundations, Models and Algorithms

  • Chih-Cheng Hung
  • Enmin Song
  • Yihua Lan
Textbook

Table of contents

  1. Front Matter
    Pages i-xii
  2. Existing Models and Algorithms for Image Texture

    1. Front Matter
      Pages 1-1
    2. Chih-Cheng Hung, Enmin Song, Yihua Lan
      Pages 15-50
    3. Chih-Cheng Hung, Enmin Song, Yihua Lan
      Pages 51-102
    4. Chih-Cheng Hung, Enmin Song, Yihua Lan
      Pages 103-127
  3. The K-Views Models and Algorithms

    1. Front Matter
      Pages 129-129
    2. Chih-Cheng Hung, Enmin Song, Yihua Lan
      Pages 131-148
    3. Chih-Cheng Hung, Enmin Song, Yihua Lan
      Pages 149-161
    4. Chih-Cheng Hung, Enmin Song, Yihua Lan
      Pages 163-182
    5. Chih-Cheng Hung, Enmin Song, Yihua Lan
      Pages 183-198
  4. Deep Machine Learning Models for Image Texture Analysis

    1. Front Matter
      Pages 199-199
    2. Chih-Cheng Hung, Enmin Song, Yihua Lan
      Pages 201-232
    3. Chih-Cheng Hung, Enmin Song, Yihua Lan
      Pages 233-251
  5. Back Matter
    Pages 253-258

About this book

Introduction

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.

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.​

Keywords

Image Texture Analysis Digital Image Processing K-View Model Texture Classification Deep Learning Convolutional Neural Networks (CNN)

Authors and affiliations

  • Chih-Cheng Hung
    • 1
  • Enmin Song
    • 2
  • Yihua Lan
    • 3
  1. 1.Kennesaw State UniversityMariettaUSA
  2. 2.Huazhong University of Science and TechnologyWuhanChina
  3. 3.Nanyang Normal UniversityNanyangChina

Bibliographic information

Industry Sectors
Automotive
Chemical Manufacturing
Health & Hospitals
Biotechnology
Electronics
IT & Software
Telecommunications
Law
Consumer Packaged Goods
Pharma
Materials & Steel
Energy, Utilities & Environment
Aerospace
Oil, Gas & Geosciences
Engineering