Image Texture Analysis: Foundations, Models and Algorithms
by Chih-Cheng Hung, Enmin Song and Yihua Lan
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BookPal × TalezoImage Texture Analysis
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.
Details
- Publisher
- Springer International Publishing
- Authors
- Chih-Cheng Hung, Enmin Song, Yihua Lan
- Format
- Hardcover
- Published
- Jun 17, 2019
- ISBN-13
- 9783030137724
- Pages
- 258
- Printing
- Printed on demand
Image Texture Analysis for groups: pricing
Volume pricing applies automatically in your cart. No codes, no account needed.
| Copies | Price per copy | You save |
|---|---|---|
| 25 – 49 | $61.59 | 12% off list |
| 50 – 99 | $60.89 | 13% off list |
| 100+ | $60.19 | 14% off list |
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