Tang Y.Y. Wavelet Theory Approach to Pattern Recognition

2nd Edition. — World Scientific, 2009. — 482 p.This book is an update of the book “Wavelet Theory and its Application to Pattern Recognition” which was published in 2000. Three new chapters are added to this new book. The objective is to attack a challenging research topic that is related to both areas of wavelet theory and pattern recognition.
Wavelet analysis and its applications have become one of the fastest growing research areas in recent years. This is in part attributed to the pioneering work by the researchers as well as practitioners in the fields of mathematics and signal processing. Wavelet theory has been employed in many fields and applications, such as signal and image processing, communication systems, biomedical imaging, radar, air acoustics, theoretical mathematics, control system, and endless other areas. However, the research on applying the wavelets to pattern recognition is still too weak; only a few publications deal with this topic at the present. This book focuses on this challenging research topic.
The most fascinating area of signal/image processing with practical applications is pattern recognition. Making computers see and recognize objects like humans has captured the attention of many scientists in different disciplines. Indeed, machine recognition of different patterns such as printed and handwritten characters, fingerprints, biomedical images, etc. has been intensively and extensively researched by scientists in different countries around the world. The area of pattern recognition, after over five decades of continued development, is now definitely playing a very major role in advanced automation in the 21st century. Although a lot of achievements have been made in the area of pattern recognition, many problems still have to be solved. The goal of this book is to, through mathematically sound derivations and experiments, develop some new application-oriented techniques in wavelet theory, and thereafter, apply these new techniques to solve some particular problems in the area of pattern recognition.Continuous Wavelet Transforms
Multiresolution Analysis and Wavelet Bases
Some Typical Wavelet Bases
Step-Edge Detection by Wavelet Transform
Characterization of Dirac-Edges with Quadratic Spline Wavelet Transform
Construction of New Wavelet Function and Application to Curve Analysis
Skeletonization of Ribbon-like Shapes with New Wavelet Function
Feature Extraction by Wavelet Sub-Patterns and Divider Dimensions
Document Analysis by Reference Line Detection with 2-D Wavelet Transform
Chinese Character Processing with B-Spline Wavelet Transform
Classifier Design Based on Orthogonal Wavelet Series