Polygonal Approximation and Scale-Space Analysis of Closed Digital Curves

Polygonal Approximation: Introduction. 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. Scale-space analysis: Introduction. 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. Application of Polygonal Approximation for Pattern Classification and Object Recognition: Introduction. 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. Conclusion.