Feature Extraction and Image Processing, 2nd edition
by Mark Nixon and Alberto Aguado
Academic Press, December 2007
This is a 400 page book with, as its title states, information about image processing and techniques to extract image features, particularly edges, shapes and textures. The book contains a broad overview of the field presented at a level of depth aimed at those who are new to the field.
One of the assets of this book is its large number of references. Image processing can be quite a broad field, and the book’s authors cite an overwhelming and impressive number of books, conference, and journal articles on a broad range of topics. The citations are often accompanied by a description of how each reference can be beneficial and how it is related to the topic under discussion. This citation list would be beneficial for practitioners who are taking a sidestep to a new part of their field, for professors to provide articles for their students, or for students to follow subjects more deeply and independently.
Each chapter starts with a table listing the main topics of the chapter. These are listed both from an applications standpoint and from a technical component/algorithm standpoint. The book starts with an introduction of the requisite material on human vision systems and a few mind-eye tricks. Then it provides a very good overview of image processing software and web site resources.
Chapters 2 and 3 give the basic definitions of images and gray scale representations and introduce techniques such as the Fourier transform, image histograms and point operations, convolution and other window based operations. Chapter 4 starts into feature extraction in the context of edge detection, edge curvature and corner detection, and then provides a short discussion of optical flow. Chapter 5 discusses shape matching both from a template standpoint and a Hough transform standpoint. The Hough transform discussion is expanded beyond the straight line discussion found in most image processing texts to circles, ellipses and the generalized Hough transform. Chapter 6 discusses snake and active contour techniques and includes a discussion of skeletonization (that doesn’t seem to fit with the rest of the chapter contents). Chapter 7 covers object description. This includes boundary descriptors like chain codes and Fourier descriptors and region descriptors like moments.
Chapter 8 endeavors to bring the whole concept of feature extraction together with the feature of texture. There is a short discussion of how the various features that have been identified throughout the book could be used to do texture classification. As I associate “feature extraction” with “pattern recognition”, given the title of the book, I felt this should have been done earlier and used throughout the book to indicate how the image processing is related to feature extraction.
There are four appendices in the book covering, Matlab and MathCAD worksheets, camera geometry models, least square analysis, and principal component analysis. There is a smattering of MathCAD and MATLAB code throughout the book. The Matlab code is written to be functional pseudo code rather than efficiently written Matlab code, as it used excessive for-loops instead of making use of Matlab’s array based processing features. These would have to be rewritten to run at any reasonable speed, but if you are starting at the beginning it is useful to have some functional code to test things out.
To accomplish its goal as an overview text, this book describes many different techniques for each task. For many topics, mathematical descriptions are provided – while still keeping the discussion at an overview level. This book could be used for an introductory course if the instructor supplements with material from his or her favorite sub-topics. The book can also be used as a good framework to facilitate a broad range of discussion topics through its content and extensive references.
Click above to go to the author’s home page for this book where you will find contents and extra material for the book and links for image processing and computer vision.
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