Edge Detection in Binary Images Using Sobel Operator Followed by Circle Detection via Hough Transform
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Resource Overview
This MATLAB implementation demonstrates a two-stage image processing approach: first applying the Sobel operator for edge detection on binary images, then utilizing Hough transform to identify circular objects by determining their center coordinates and radii. The package includes sample images, detailed code explanations, and visual results illustrating the complete workflow.
Detailed Documentation
This implementation provides a comprehensive MATLAB solution for circle detection in binary images through a systematic pipeline. The process begins with edge detection using the Sobel operator, which calculates gradient approximations in both horizontal and vertical directions to highlight boundary regions. The algorithm then proceeds to Hough transform implementation, employing a voting mechanism in parameter space to accumulate evidence for circular shapes. Key MATLAB functions utilized include edge() with 'sobel' option for gradient-based boundary extraction and customized Hough circle detection routines that analyze accumulator arrays to pinpoint optimal center points and radius values. The package includes supporting visual materials and step-by-step annotations to clarify the algorithm's execution flow and intermediate results, making it suitable for educational and practical computer vision applications.
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