Document Analysis and Recognition with Wavelet and Fractal Theories

Many phenomena around the research in document analysis and understanding are much better described through the powerful multiscale signal representations than by traditional ways. From this perspective, the recent emergence of powerful multiscale signal representations in general and fractal/wavelet basis representations in particular, has been particularly timely. Indeed, out of these theories arise highly natural and extremely useful representations for a variety of important phenomena in document analysis and understanding. This book presents both the development of these new approaches as well as their application to a number of fundamental problems of interest to scientists and engineers in document analysis and understanding. Contents:Basic Concepts of Document Analysis and UnderstandingBasic Concepts of Fractal DimensionBasic Concepts of Wavelet TheoryDocument Analysis by Fractal DimensionText Extraction by Wavelet DecompositionRotation Invariant by Fractal Theory with Central Projection Transform (CPT)Wavelet-Based and Fractal-Based Methods for Script IdentificationWriter Identification Using Hidden Markov Model in Wavelet Domain (WD-HMM) Readership: Professionals, researchers, academics and graduate students in pattern/recognition/image analysis, machine perception/computer vision, and electrical & electronic engineering. Keywords:Document Analysis;Recognition;Wavelet Theory;Multiresolution Analysis;Hidden Markov Model;Fractal Dimension;Box Computing Dimension