MATLAB Source Code for Shape Context with Digital Character Matching Demo

This MATLAB source code implements the shape context algorithm designed for shape matching and recognition applications. The package includes a comprehensive demo that performs alphanumeric character matching by comparing input images against pre-stored template images. The algorithm computes similarity metrics between shapes by analyzing their spatial distribution patterns through log-polar histograms. Key implementation details include: - Shape context descriptor extraction using boundary point sampling - Cost matrix calculation for point correspondences with Hungarian algorithm optimization - Thin plate spline (TPS) transformation for shape alignment - Similarity scoring based on χ² distance between histogram distributions The code structure features modular functions for pre-processing (edge detection, contour extraction), feature computation (shape context generation), and matching optimization. Parameters such as sampling density, histogram bins, and matching thresholds can be adjusted to optimize performance for various applications including OCR systems, object recognition, and biometric authentication like face recognition. The implementation demonstrates robustness to minor shape deformations and lighting variations through normalized feature representations.