2D and 3D Image Analysis by Moments Front Cover

2D and 3D Image Analysis by Moments

  • Length: 560 pages
  • Edition: 1
  • Publisher:
  • Publication Date: 2016-12-19
  • ISBN-10: 1119039355
  • ISBN-13: 9781119039358
  • Sales Rank: #3712938 (See Top 100 Books)
Description

Presents recent significant and rapid development in the field of 2D and 3D image analysis

2D and 3D Image Analysis by Moments, is a unique compendium of moment-based image analysis which includes traditional methods and also reflects the latest development of the field.

The book presents a survey of 2D and 3D moment invariants with respect to similarity and affine spatial transformations and to image blurring and smoothing by various filters. The book comprehensively describes the mathematical background and theorems about the invariants but a large part is also devoted to practical usage of moments. Applications from various fields of computer vision, remote sensing, medical imaging, image retrieval, watermarking, and forensic analysis are demonstrated. Attention is also paid to efficient algorithms of moment computation.

Key features:

  • Presents a systematic overview of moment-based features used in 2D and 3D image analysis.
  • Demonstrates invariant properties of moments with respect to various spatial and intensity transformations.
  • Reviews and compares several orthogonal polynomials and respective moments.
  • Describes efficient numerical algorithms for moment computation.
  • It is a “classroom ready” textbook with a self-contained introduction to classifier design.
  • The accompanying website contains around 300 lecture slides, Matlab codes, complete lists of the invariants, test images, and other supplementary material.

2D and 3D Image Analysis by Moments, is ideal for mathematicians, computer scientists,   engineers, software developers, and Ph.D students involved in image analysis and recognition. Due to the addition of two introductory chapters on classifier design, the book may also serve as a self-contained textbook for graduate university courses on object recognition.

Table of Contents

Chapter 1 Motivation
Chapter 2 Introduction to Object Recognition
Chapter 3 2D Moment Invariants to Translation, Rotation, and Scaling
Chapter 4 3D Moment Invariants to Translation, Rotation, and Scaling
Chapter 5 Affine Moment Invariants in 2D and 3D
Chapter 6 Invariants to Image Blurring
Chapter 7 2D and 3D Orthogonal Moments
Chapter 8 Algorithms for Moment Computation
Chapter 9 Applications
Chapter 10 Conclusion

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