LEADER 00000nam a22004813i 4500
001 EBC919133
003 MiAaPQ
005 20200713055220.0
006 m o d |
007 cr cnu||||||||
008 200713s2012 xx o ||||0 eng d
020 9789814401012|q(electronic bk.)
020 |z9789814401005
035 (MiAaPQ)EBC919133
035 (Au-PeEL)EBL919133
035 (CaPaEBR)ebr10563477
035 (CaONFJC)MIL505495
035 (OCoLC)793374377
040 MiAaPQ|beng|erda|epn|cMiAaPQ|dMiAaPQ
050 4 QA403.3 -- .T36 2012eb
082 0 515.243
100 1 Tang, Yuan Yan
245 10 Document Analysis and Recognition with Wavelet and Fractal
Theories
264 1 Singapore :|bWorld Scientific Publishing Co Pte Ltd,|c2012
264 4 |c©2012
300 1 online resource (373 pages)
336 text|btxt|2rdacontent
337 computer|bc|2rdamedia
338 online resource|bcr|2rdacarrier
490 1 World Scientific Series On The Economics Of Climate Change
;|vv.79
505 0 Intro -- Contents -- Preface -- Chapter 1 Basic Concepts
of Document Analysis and Understanding -- 1.1
Introduction. -- 1.2 Basic Model of Document Processing --
1.3 Document Structures -- 1.3.1 Strength of Structure --
1.3.2 Geometric Structure -- 1.3.2.1 Geometric Complexity
-- 1.3.3 Logical Structure -- 1.4 Document Analysis --
1.4.1 Hierarchical Methods -- 1.4.1.1 Top-Down Approach --
1.4.1.2 Bottom-Up Approach -- 1.4.2 No-HierarchicalMethods
-- 1.4.2.1 Modified Fractal Signature -- 1.4.2.2 Order
Stochastic Filtering -- 1.4.3 Web Document Analysis -- 1.5
Document Understanding -- 1.5.1 Document Understanding
Based on Tree Transformation -- 1.5.2 Document
Understanding Based on Formatting Knowledge -- 1.5.3
Document Understanding Based on Description Language --
1.6 Form Document Processing -- 1.6.1 Characteristics of
Form Documents -- 1.6.2 Wavelet Transform Approach --
1.6.3 Approach Based on Form Description Language -- 1.6.4
Form Document Processing Based on Form Registration --
1.6.5 Form Document Processing System -- 1.7 Character
Recognition and Document Image Processing -- 1.7.1
Handwritten and Printed Character Recognition -- 1.7.1.1
Extracting Multiresolution Features in Recognition of
Handwritten Numerals with 2-D Haar Wavelet -- 1.7.1.2
Recognition of Printed Kannada Text in Indian Languages --
1.7.1.3 Wavelet Descriptors of Handprinted Characters --
1.7.2 Document Image Analysis Based on Multiresolution
Hadamard Representation (MHR) -- 1.8 Major Techniques --
1.8.1 Hough Transform. -- 1.8.2 Techniques for Skew
Detection -- 1.8.3 Projection Profile Cuts -- 1.8.4 Run-
Length Smoothing Algorithm (RLSA) -- 1.8.5 Neighborhood
Line Density (NLD) -- 1.8.6 Connected Components Analysis
(CCA) -- 1.8.7 Crossing Counts -- 1.8.8 Form Definition
Language (FDL) -- 1.8.9 Texture Analysis - Gabor Filters -
- 1.8.10 Wavelet Transform
505 8 1.8.11 Other Segmentation Techniques -- Chapter 2 Basic
Concepts of Fractal Dimension -- 2.1 Definitions of
Fractals -- 2.2 Hausdorff Dimension -- 2.2.1 Hausdorff
Measure -- 2.2.2 Hausdorff Dimension -- 2.2.3 Examples of
Computing Hausdorff Dimension -- 2.3 Box Computing
Dimension -- 2.3.1 Dimensions -- 2.3.2 Box Computing
Dimension -- 2.3.3 Minkowski Dimension -- 2.3.4 Properties
of Box Counting Dimension -- 2.4 Basic Methods for
Calculating Dimensions -- Chapter 3 Basic Concepts of
Wavelet Theory -- 3.1 Continuous Wavelet Transforms --
3.1.1 General Theory of Continuous Wavelet Transforms --
3.1.2 The Continuous Wavelet Transform as a Filter --
3.1.3 Description of Regularity of Signal by Wavelet --
3.1.4 Some Examples of Basic Wavelets -- 3.2
Multiresolution Analysis (MRA) and Wavelet Bases -- 3.2.1
Multiresolution Analysis -- 3.2.1.1 Basic Concept of MRA -
- 3.2.1.2 The Solution of Two-Scale Equation -- 3.2.2 The
Construction of MRAs -- 3.2.2.1 The Biorthonormal MRA --
3.2.2.2 Examples of Constructing MRA -- 3.2.3 The
Construction of Biorthonormal Wavelet Bases -- 3.2.4
S.Mallat Algorithms -- Chapter 4 Document Analysis by
Fractal Dimension -- 4.1 Introduction. -- 4.2 Document
Analysis Based on Modified Fractal Signature (MFS) --
4.2.1 Basic Idea of Modified Fractal Signature (MFS) --
4.2.2 δ-Parallel Bodies -- 4.2.3 Blanket Technique to
Extract Fractal Feature -- 4.3 Algorithm of Modified
Fractal Signature (MFS) -- 4.3.1 Identification of
Different Blocks of Document by Fractal Signature -- 4.3.2
Modified Fractal Signature (MFS) -- 4.4 Experiments --
Chapter 5 Text Extraction by Wavelet Decomposition -- 5.1
Introduction -- 5.2 Wavelet Decomposition of Pseudo-Motion
Functions -- 5.2.1 One Variable Case -- 5.2.2 Two
Variables Case -- 5.3 Segmentation of Different Areas of
Document Image -- 5.3.1 Segmentation of Areas of Different
Frequency
505 8 5.3.2 WDPM Algorithm -- 5.4 Experiments -- 5.4.1 Position
of License Plate -- 5.4.1.1 Choose of the Bases -- 5.4.1.2
Experimental Results -- 5.4.2 Localization of Text Areas
of Document Images -- Chapter 6 Rotation Invariant by
Fractal Theory with Central Projection Transform (CPT) --
6.1 Introduction -- 6.1.1 Rotations -- 6.1.2 Rotation
Invariants -- 6.1.3 Rotation Invariant of Discrete Images
-- 6.1.4 Rotation Invariants in Pattern Recognition --
6.1.4.1 Boundary Curvature -- 6.1.4.2 Fourier Descriptors
-- 6.1.4.3 Zernik Moments -- 6.1.4.4 Neural Networks --
6.2 Preprocessing and Central Projection Transform (CPT) -
- 6.2.1 Preprocessing -- 6.2.2 Central Projection
Transform (CPT) -- 6.2.2.1 Basic Definitions of CPT -- 1.
Central Projection -- 2. Regional Central Projection (RCP)
-- 6.2.2.2 Properties of CPT -- 1. Contour Unitization --
2. Shape Invariance -- 6.2.2.3 Parallel Algorithm for CPT
-- 6.2.2.4 Contour Unfolding -- 6.3 Rotation Invariance
Based on Box Computing Dimension -- 6.3.1 Estimation of
the 1-D Fractal Dimension -- 6.3.2 Rotation Invariant
Signature (RIS) -- 6.4 Experiments -- 6.4.1 Rotation
Invariant Signature (RIS) Algorithm -- 6.4.1.1 Estimation
of the BCD -- 6.4.1.2 Extraction of Feature with Rotation
Invariant Property -- 6.4.2 Experimental Procedure and
Results -- Chapter 7 Wavelet-Based and Fractal-Based
Methods for Script Identification -- 7.1 Introduction --
7.2 Wavelet-Based Approach -- 7.2.1 Image Decomposition by
Multi-Scale Wavelet Transform -- 7.2.2 Wavelet-Based
Features -- 7.2.2.1 Average Energy of Document Image --
7.2.2.2 Wavelet Energy Distribution Features (Fd) --
7.2.2.3 Wavelet Energy Distribution Proportion Features
(Fdp) -- 7.2.3 Experiments -- 7.2.3.1 Distance Functions -
- 7.2.3.2 Experimental Results -- 7.3 Fractal-Based
Approach -- 7.3.1 Algorithm -- 7.3.2 Experiments
505 8 Chapter 8 Writer Identification Using Hidden Markov Model
in Wavelet Domain (WD-HMM) -- 8.1 Introduction -- 8.2
Hidden Markov Model and Relative Statistical Knowledge --
8.2.1 Expectation Maximization (EM) Algorithm -- 8.2.2
Gaussian Mixture Model (GMM) and Expectation Maximization
(EM) for Gaussian Mixture Model (GMM) -- 8.2.3 Hidden
Markov Model -- 8.2.3.1 Basic Frame of HMM -- 8.2.3.2
Three Basic Problems for HMM -- 8.2.3.3 Important
Assumptions for HMM -- 8.3 Hidden Markov Models in Wavelet
Domain -- 8.3.1 GMM Model for a Single Wavelet Coefficient
-- 8.3.2 Independence Mixture Model -- 8.3.3 WD-HMM and EM
for WD-HMM -- 8.4 Writer Identification Using WD-HMM --
8.4.1 The Whole Procedure -- 8.4.2 Feature Extraction --
8.4.3 Similarity Measurement -- 8.4.4 Performance
Evaluation -- 8.5 Experiments -- Bibliography -- Index
520 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
588 Description based on publisher supplied metadata and other
sources
590 Electronic reproduction. Ann Arbor, Michigan : ProQuest
Ebook Central, 2020. Available via World Wide Web. Access
may be limited to ProQuest Ebook Central affiliated
libraries
650 0 Wavelets (Mathematics);Fractals
655 4 Electronic books
776 08 |iPrint version:|aTang, Yuan Yan|tDocument Analysis and
Recognition with Wavelet and Fractal Theories|dSingapore :
World Scientific Publishing Co Pte Ltd,c2012
|z9789814401005
830 0 World Scientific Series On The Economics Of Climate Change
856 40 |uhttps://ebookcentral.proquest.com/lib/sinciatw/
detail.action?docID=919133|zClick to View
