Image Texture Analysis Foundations, Models and Algorithms /

• Main Authors: Hung, Chih-Cheng (Author, http://id.loc.gov/vocabulary/relators/aut), Song, Enmin (http://id.loc.gov/vocabulary/relators/aut), Lan, Yihua (http://id.loc.gov/vocabulary/relators/aut)
• Corporate Author: SpringerLink (Online service)
• Format: Electronic eBook
• Language: English
• Published: Cham : Springer International Publishing : Imprint: Springer, 2019.
• Edition: 1st ed. 2019.
• Subjects: Optical data processing.; Artificial intelligence.; Image Processing and Computer Vision.; Artificial Intelligence.

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 imag...

Table of Contents:

• 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.