Edge Detection and Contour Tracking Algorithms

The program for edge detection and contour tracking is implemented in the MATLAB environment, leveraging its comprehensive image processing toolbox. This implementation focuses on detecting edges and tracing contours in digital images through advanced image processing techniques. MATLAB provides essential functions like edge() with various operators (Sobel, Canny, Prewitt), bwboundaries() for contour extraction, and morphological operations for noise reduction. The program employs algorithms such as gradient-based methods for edge detection and boundary following techniques for contour tracking. Key implementation steps include image preprocessing (noise filtering, contrast enhancement), edge detection using differential operators, and contour tracing through connected component analysis. The edge detection phase typically involves calculating image gradients and applying thresholding, while contour tracking uses chain codes or boundary following algorithms to connect edge points into continuous contours. This MATLAB implementation serves various applications including image analysis, computer vision systems, and pattern recognition tasks. Through developing this program, users gain deeper understanding of fundamental principles in edge detection algorithms (like Canny's multi-stage approach) and contour tracing methods (such as Moore-neighbor tracing), enabling practical application in real-world image processing projects. The code structure typically includes modules for image input, parameter configuration, algorithm execution, and visualization of results using MATLAB's plotting capabilities.