MATLAB Source Code for Circle Detection Using Hough Transform

This MATLAB source code implements circle detection using the Hough transform algorithm, designed to rapidly and precisely identify circular objects within digital images. The code employs a parameter space transformation approach where circle candidates are represented by their center coordinates (a, b) and radius r. Key implementation features include gradient-based edge detection preprocessing, accumulator array optimization for voting, and peak detection to identify valid circles. For image processing enthusiasts and professionals, this code serves as both a practical tool and educational resource. The implementation demonstrates efficient memory management through dimensional reduction techniques and includes threshold parameterization for sensitivity adjustment. You can extend this foundation by experimenting with different edge detection methods, implementing multi-scale analysis for various circle sizes, or adding noise robustness features. The code structure allows straightforward modification for real-time applications or integration with larger computer vision systems. This implementation provides insight into the mathematical principles of Hough transforms while maintaining computational efficiency through MATLAB's vectorized operations. We encourage further experimentation with parameter tuning, performance optimization, and application to various imaging domains to enhance your technical skills in digital image processing.