LEADER 05388nam 2200661 a 450 001 9910451637403321 005 20200520144314.0 010 $a981-4401-01-3 035 $a(CKB)2550000000101519 035 $a(EBL)919133 035 $a(OCoLC)793374377 035 $a(SSID)ssj0000655480 035 $a(PQKBManifestationID)12237672 035 $a(PQKBTitleCode)TC0000655480 035 $a(PQKBWorkID)10595844 035 $a(PQKB)11320924 035 $a(MiAaPQ)EBC919133 035 $a(WSP)00002701 035 $a(Au-PeEL)EBL919133 035 $a(CaPaEBR)ebr10563477 035 $a(CaONFJC)MIL505495 035 $a(EXLCZ)992550000000101519 100 $a20120611d2012 uy 0 101 0 $aeng 135 $aur|n|---||||| 181 $ctxt 182 $cc 183 $acr 200 10$aDocument analysis and recognition with wavelet and fractal theories$b[electronic resource] /$fYuan Yan Tang 210 $aSingapore $cWorld Scientific Pub. Co.$d2012 215 $a1 online resource (373 p.) 225 1 $aSeries in machine perception and artificial intelligence ;$vv. 79 300 $aDescription based upon print version of record. 311 $a981-4401-00-5 320 $aIncludes bibliographical references and index. 327 $aContents; 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 327 $a1.5.1 Document Understanding Based on Tree Transformation1.5.2 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 327 $a1.7.1.1 Extracting Multiresolution Features in Recognition of Handwritten Numerals with 2-D Haar Wavelet1.7.1.2 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 327 $a1.8.8 Form Definition Language (FDL)1.8.9 Texture Analysis - Gabor Filters; 1.8.10 Wavelet Transform; 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 327 $a3.1 Continuous Wavelet Transforms3.1.1 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 327 $aChapter 4 Document Analysis by Fractal Dimension 330 $aMany phenomena around the research in document analysis and understanding are much better described through the powerful multiscale signal representations than by traditional ways. From this perspective, the recent emergence of powerful multiscale signal representations in general and fractal/wavelet basis representations in particular, has been particularly timely. Indeed, out of these theories arise highly natural and extremely useful representations for a variety of important phenomena in document analysis and understanding. This book presents both the development of these new approaches as 410 0$aSeries in machine perception and artificial intelligence ;$vv. 79. 606 $aWavelets (Mathematics) 606 $aFractals 608 $aElectronic books. 615 0$aWavelets (Mathematics) 615 0$aFractals. 676 $a515 676 $a515.2433 700 $aTang$b Yuan Yan$0911926 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910451637403321 996 $aDocument analysis and recognition with wavelet and fractal theories$92042054 997 $aUNINA