1st Edition

Polygonal Approximation and Scale-Space Analysis of Closed Digital Curves

By Kumar S. Ray, Bimal Kumar Ray Copyright 2013
    388 Pages 153 B/W Illustrations
    by Apple Academic Press

    388 Pages 153 B/W Illustrations
    by Apple Academic Press

    This book covers the most important topics in the area of pattern recognition, object recognition, computer vision, robot vision, medical computing, computational geometry, and bioinformatics systems. Students and researchers will find a comprehensive treatment of polygonal approximation and its real life applications. The book not only explains the theoretical aspects but also presents applications with detailed design parameters. The systematic development of the concept of polygonal approximation of digital curves and its scale-space analysis are useful and attractive to scholars in many fields.

    Part I: Polygonal Approximation
    A Split-and-Merge Technique
    A Sequential One-Pass Method
    Another Sequential One-Pass Method
    A Data-Driven Method
    Another Data-Driven Method
    A Two-Pass Sequential Method
    Polygonal Approximation Using Reverse Engineering on Bresenham's Line Drawing Technique
    Polygonal Approximation as Angle Detection
    Polygonal Approximation as Angle Detection Using Asymmetric Region of Support
    Part II: Scale-space analysis
    Scale-Space Analysis and Corner Detection on Chain Coded Curves
    Scale-Space Analysis and Corner Detection Using Iterative Gaussian Smoothing With Constant Window Size
    Corner detection using Bessel function as smoothing kernel
    Adaptive smoothing using convolution with Gaussian Kernel
    Part III: Application of Polygonal Approximation for Pattern Classification and Object Recognition
    Polygonal Dissimilarity and Scale Preserving Smoothing
    Matching Polygon Fragments
    Polygonal Approximation to Recognize and Locate Partially Occluded Objects: Hypothesis Generation and Verification Paradigm
    Object Recognition With Belief Revision: Hypothesis Generation and Belief Revision Paradigm
    Neuro-Fuzzy Reasoning for Occluded Object Recognition: A Learning Paradigm Through Neuro-Fuzzy Concept


    Kumar S. Ray, PhD, is a professor in the Electronics and Communication Science Unit at the Indian Statistical Institute, Kolkata, India. He has written a number of articles published in international journals and has presented at several professional meetings. His current research interests include artificial intelligence, computer vision, commonsense reasoning, soft computing, non-monotonic deductive database systems, and DNA computing. 

    Bimal Kumar Ray is a professor at the School of Information Technology and Engineering, Vellore Institute of Technology, Vellore, India. He received his PhD degree in computer science from the Indian Statistical Institute, Kolkata, India. He received hs master’s degree in applied mathematics from Calcutta University and his bachelor’s degree in mathematics from St. Xavier’s College, Kolkata. His research interests include computer graphics, computer vision, and image processing. He has published a number of research papers in peer-reviewed journals.