Contents -- Preface -- Chapter 1 Introduction -- 1.1 Wavelet: A Novel Mathematical Tool for Pattern Recognition -- 1.2 Brief Review of Pattern Recognition with Wavelet Theory -- 1.2.1 Iris Pattern Recognition -- 1.2.2 Face Recognition Using Wavelet Transform -- 1. Wavelet-based PCA Approach -- 2. Nonlinear Wavelet Approximation Method -- 3. Wavelet Packets Transform for Classification of Facial Images -- 1.2.3 Hand Gestures Classification -- 1. Visual Hand Gestures Classification UsingWavelet Transforms -- 2. Hand Gestures Classification by Wavelet Transforms and Moment Based Features -- 3. Wavelet Directional Histograms of The Spatio-Temporal Templates of Human Gestures -- 1.2.4 Classification and Clustering -- 1. Classifier Design Based on Orthogonal Wavelet Series -- 2. Neuro-Wavelet Classifier for Multispectral Remote Sensing Images -- 3. Pattern Clustering Based on Noise Modeling in Wavelet Space -- 1.2.5 Document Analysis with Wavelets -- 1. Form-Document Analysis by Reference Line Detection with 2-D Wavelet Transform -- 2. Multiresolution Hadamard Representation and Its Application to Document Image Analysis -- 1.2.6 Analysis and Detection of Singularities withWavelets -- 1. Edge Detection with Local Maximal Modulus of Wavelet Transform -- 2. Detection of Step-Structure Edges by Scale-Independent Algorithm and MASW Wavelet Transform -- 1.2.7 Wavelet Descriptors for Shapes of the Objects -- 1. Wavelet Descriptor of Planar Curves: Theory and Applications -- 2. Wavelet Descriptors for Multiresolution Recognition Of Handprinted Characters -- 3. Wavelet-Based Shape form Shading -- 4. Representation of 2-D Pattern by 1-D Wavelet Sub-patterns -- 5. Wavelet Descriptors for Multiresolution Recognition Of Handprinted Characters -- 1.2.8 Invariant Representation of Patterns.

1. Extraction of Rotation-Invariant Feature by Ring-projectionwavelet- fractal Method -- 2. Wavelet Rotation-Invariant Shape Descriptors for Recognition of 2-D Pattern -- 3. Scale-Invariant Object Recognition Based on the Multiresolution Approximation -- 1.2.9 Handwritten and Printed Character Recognition -- 1. Wavelet Descriptors for Recognition of Handprinted Characters -- 2. Extracting Multiresolution Features in Recognition of Handwritten Numerals with 2-D Haar Wavelet -- 3. Wavelet Descriptors for Recognition of Printed Kannada Text in Indian languages -- 1.2.10 Texture Analysis and Classification -- 1. Wavelet correlation signatures for color texture characterization -- 2. Rotation-Invariant Texture Classification Using a Complete Space-Frequency Model -- 3. Statistical Texture Characterization from Discrete Wavelet Representation -- 4. Adaptive Scale Fixing for Multiscale Texture Segmentation -- 5. Combination of Gabor Wavelet Transforms and Moments for Texture Segmentation -- 1.2.11 Image Indexing and Retrieval -- 1. Wavelet Correlogram -- 2. Region Separation and Multiresolution Analysis -- 1.2.12 Wavelet-Based Image Fusion -- 1.2.13 Others -- Chapter 2 Continuous Wavelet Transforms -- 2.1 General Theory of Continuous Wavelet Transforms -- 2.2 The Continuous Wavelet Transform as a Filter -- 2.3 Characterization of Lipschitz Regularity of Signal by Wavelet -- 2.4 Some Examples of Basic Wavelets -- Chapter 3 Multiresolution Analysis and Wavelet Bases -- 3.1 Multiresolution Analysis -- 3.1.1 Basic Concept of Multiresolution Analysis (MRA) -- 3.1.2 The Solution of Two-Scale Equation -- 3.2 The Construction of MRAs -- 3.2.1 The Biorthonormal MRA -- 3.2.2 Examples of Constructing MRA -- 3.3 The Construction of Biorthonormal Wavelet Bases -- 3.4 S.Mallat Algorithms -- Chapter 4 Some Typical Wavelet Bases -- 4.1 Orthonormal Wavelet Bases.

4.1.1 Haar Wavelet -- 4.1.2 Littlewood-Paley (LP) Wavelet -- 4.1.3 Meyer Wavelet -- 4.1.4 Battle-Lemaré-spline Wavelet -- 4.1.5 Daubechies' Compactly Supported Orthonormal Wavelets -- 4.1.6 Coiflet -- 4.2 Nonorthonormal Wavelet Bases -- 4.2.1 Cardinal SplineWavelet -- 4.2.2 Compactly Supported Spline Wavelet -- Chapter 5 Step-Edge Detection by Wavelet Transform -- 5.1 Edge Detection with Local Maximal Modulus of Wavelet Transform -- 5.2 Calculation of Wsf(x) and Wsf(x, y) -- 5.2.1 Calculation of Wsf(x) -- 5.2.2 Calculation of Wsf(x, y) -- 5.3 Wavelet Transform for Contour Extraction and Background Removal -- 5.3.1 Basic Edge Structures -- 5.3.2 Analysis of the Basic Edge Structures with Wavelet Transform. -- 5.3.3 Scale-Independent Algorithm -- 5.3.4 Experiments -- Chapter 6 Characterization of Dirac-Edges with Quadratic Spline Wavelet Transform -- 6.1 Selection of Wavelet Functions by Derivation -- 6.1.1 ScaleWavelet Transform -- 6.1.2 Construction of Wavelet Function by Derivation of the Low-Pass Function -- 6.2 Characterization of Dirac-Structure Edges by Wavelet Transform -- 6.2.1 Slope Invariant -- 6.2.2 Grey-Level Invariant -- 6.2.3 Width Light-Dependent -- 6.3 Experiments -- Chapter 7 Construction of New Wavelet Function and Application to Curve Analysis -- 7.1 Construction of New Wavelet Function - Tang-Yang Wavelet -- 7.2 Characterization of Curves through New Wavelet Transform -- 7.3 Comparison with OtherWavelets -- 7.3.1 Comparison with Gaussian Wavelets -- 7.3.2 Comparison with Quadratic Spline Wavelets -- 7.4 Algorithmand Experiments -- 7.4.1 Algorithm -- 7.4.2 Experiments -- Chapter 8 Skeletonization of Ribbon-like Shapes with New Wavelet Function -- 8.1 Tang-Yang Wavelet Function -- 8.2 Characterization of the Boundary of a Shape by Wavelet Transform -- 8.3 Wavelet Skeletons and Its Implementation.

8.3.1 Wavelet Transform in the Discrete Domain -- 8.3.2 Generation of Wavelet Skeleton in the Discrete Domain -- 8.3.3 Modification of Primary Wavelet Skeleton -- 8.4 Algorithm and Experiment -- 8.4.1 Algorithm -- 8.4.2 Experiments -- Chapter 9 Feature Extraction by Wavelet Sub-Patterns and Divider Dimensions -- 9.1 Dimensionality Reduction of Two-Dimensional Patterns with Ring-Projection -- 9.2 Wavelet Orthonormal Decomposition to Produce Sub-Patterns -- 9.3 Wavelet-Fractal Scheme -- 9.3.1 Basic Concepts of Fractal Dimension -- 9.3.2 The Divider Dimension of One-Dimensional Patterns -- 9.4 Experiments -- 9.4.1 Experimental Procedure -- 9.4.2 Experimental Results -- Chapter 10 Document Analysis by Reference Line Detection with 2-D Wavelet Transform -- 10.1 Two-Dimensional MRA and Mallat Algorithm -- 10.2 Detection of Reference Line from Sub-Images by the MRA -- 10.3 Experiments -- Chapter 11 Chinese Character Processing with B-Spline Wavelet Transform -- 11.1 Compression of Chinese Character -- 11.1.1 Algorithm 1 (Global Approach) -- 11.1.2 Algorithm 2 (Local Approach) -- 11.1.3 Experiments -- 11.2 Enlargement of Type Size with Arbitrary Scale Based on Wavelet Transform -- 11.2.1 Algorithms -- 11.2.2 Experiments -- 11.3 Generation of Chinese Type Style Based on Wavelet Transform -- 11.3.1 Modification -- 11.3.2 Composition -- Chapter 12 Classifier Design Based on Orthogonal Wavelet Series -- 12.1 Fundamentals -- 12.2 Minimum Average Lose Classifier Design -- 12.3 Minimum Error-Probability Classifier Design -- 12.4 Probability Density Estimation Based on Orthogonal Wavelet Series -- 12.4.1 Kernel Estimation of a Density Function -- 12.4.2 Orthogonal Series Probability Density Estimators -- 12.4.3 Orthogonal Wavelet Series Density Estimators -- List of Symbols -- Bibliography -- Index.