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    Copyright
    Preface
    Acknowledgment
    Ch. I. Fusion of Segmentation Strategies for Off-Line Cursive Handwriting Recognition
    ABSTRACT
    INTRODUCTION
    TYPICAL HANDWRITING RECOGNITION SYSTEM
    REVIEW OF EXISTING HANDWRITING RECOGNITION TECHNIQUES/SYSTEMS
    PROPOSED STRATEGIES FOR SEGMENTATION-BASED HANDWRITING RECOGNITION
    CONCLUSION AND FUTURE RESEARCH
    REFERENCES
    Ch. II. Elastic Matching Techniques for Handwritten Character Recognition
    Ch. III. State of the Art in Off-Line Signature Verification
    Ch. IV. An Automatic Off-Line Signature Verification and Forgery Detection System
    Ch. V. Introduction to Speech Recognition
    Ch. VI. Seeking Patterns in the Forensic Analysis of Handwriting and Speech
    Ch. VII. Image Pattern Recognition-Based Morphological Structure and Applications
    Ch. VIII. Robust Face Recognition Technique for a Real-Time Embedded Face Recognition System
    Ch. IX. Occlusion Sequence Mining for Activity Discovery from Surveillance Videos
    Ch. X. Human Detection in Static Images
    Ch. XI. A Brain-Inspired Visual Pattern Recognition Architecture and Its Applications
    Ch. XII. Significance of Logic Synthesis in FPGA-Based Design of Image and Signal Processing Systems
    Ch. XIII. A Novel Support Vector Machine with Class-Dependent Features for Biomedical Data
    Ch. XIV. A Unified Approach to Support Vector Machines
    Ch. XV. Cluster Ensemble and Multi-Objective Clustering Methods
    Ch. XVI. Implementing Negative Correlation Learning in Evolutionary Ensembles with Suitable Speciation Techniques1
    Ch. XVII. A Recurrent Probabilistic Neural Network for EMG Pattern Recognition
    Compilation of References
    About the Contributors
    Index
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    Chapter I. Fusion of Segmentation Strategies for Off-Line Cursive Handwritin...

    Chapter I. Fusion of Segmentation Strategies for Off-Line Cursive Handwriting Recognition

    Brijesh Verma
    Central Queensland University, Australia

    Michael Blumenstein
    Griffith University, Australia


      

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