Edge Detection and Boundary Tracking MATLAB Program

This article presents my custom MATLAB implementation for edge detection and boundary tracking using image processing techniques. The program utilizes core MATLAB functions like edge() with various operators (Sobel, Canny, Prewitt) for initial edge detection, followed by boundary tracking algorithms to connect discontinuous edges. Key implementation aspects include gradient calculation using convolution kernels, non-maximum suppression for edge thinning, and hysteresis thresholding for optimal edge connectivity. The boundary tracking module employs techniques like Moore-Neighborhood tracing or morphological operations (bwmorph, bwboundaries) to extract continuous object contours from binary edge maps. This implementation provides a complete pipeline from raw image input to structured boundary output, incorporating error handling for invalid inputs and parameter validation for different image types. Through extensive testing with various image datasets, the program demonstrates robust performance in extracting accurate edge features and coherent boundaries, making it suitable for computer vision applications requiring precise shape analysis. The modular code structure allows easy customization of detection parameters and tracking methods, providing researchers and developers with a flexible tool for image analysis and computer vision projects.