Template Matching Algorithm for Polygon Approximation Based on Contour Extraction

This article presents a MATLAB-implemented template matching algorithm specifically designed for polygon approximation matching based on contour extraction. The algorithm utilizes image processing techniques to analyze and extract contours, then compares them against predefined templates using geometric matching approaches. Key implementation aspects include contour detection using edge detection operators (such as Canny or Sobel), polygonal approximation through Douglas-Peucker algorithm or Freeman chain code analysis, and similarity measurement using methods like Hausdorff distance or shape context descriptors. The system enables efficient and accurate identification of polygon shapes and features by comparing extracted contours with template geometries. Further optimizations can be implemented through multi-scale analysis, rotation-invariant matching, or machine learning enhancements to improve algorithm efficiency and matching accuracy. The MATLAB implementation typically involves functions from Image Processing Toolbox for contour extraction, custom geometric comparison functions, and optimization routines for performance enhancement.