Shape Analysis and Classification: Theory and Practice (Image Processing Series)

Advances in shape analysis impact a wide range of disciplines, from mathematics and engineering to medicine, archeology, and art. Anyone just entering the field, however, may find the few existing books on shape analysis too specific or advanced, and for students interested in the specific problem of shape recognition and characterization, traditional books on computer vision are too general.

Shape Analysis and Classification: Theory and Practice offers an integrated and conceptual introduction to this dynamic field and its myriad applications. Beginning with the basic mathematical concepts, it deals with shape analysis, from image capture to pattern classification, and presents many of the most advanced and powerful techniques used in practice. The authors explore the relevant aspects of both shape characterization and recognition, and give special attention to practical issues, such as guidelines for implementation, validation, and assessment.

Shape Analysis and Classification provides a rich resource for the computational characterization and classification of general shapes, from characters to biological entities. Both students and researchers can directly use its state-of-the-art concepts and techniques to solve their own problems involving the characterization and classification of visual shapes.

There has been considerable research in computer science directed on the problems associated with detecting, analyzing, and categorizing visual shape information. The authors of this book have done an admirable job of discussing the diverse approaches utilized in this area. They also provide a 170-page chapter (chapter 2) that covers a vast range of useful mathematical concepts in shape analysis (e.g., propositional logic, linear algebra, differential geometry, convolution and correlation, probability theory, and Fourier analysis). Chapter 3 deals with digital image processing. Chapter 4 covers the main concepts in 2D shape analysis, and in Chapter 5 the authors consider computer representations of shape information. Chapters 6 and 7 are focused on techniques of shape characterization. In Chapter 8 the authors cover the major methods for classifying and recognizing shapes. This comprehensive book is clearly written and is a valuable resource for scientists interested in visual shape analysis.

Roberto Marcondes Caesar Junior