Canny Edge Detection

The canny.m file implements the complete Canny edge detection algorithm through three main computational steps: calculating image gradients, applying non-maximum suppression, and performing double threshold processing. The code utilizes the compare.m function to evaluate similarity between images during processing stages, while connect.m function handles edge pixel connectivity using hysteresis thresholding. The algorithm processes the original image (clique.jpg) through sequential stages: gradient computation (step1.jpg), non-maximum suppression (step2.jpg), and dual-threshold application with values 80 and 100 (step3.jpg and threshold images). These thresholds control edge sensitivity - lower threshold (80) captures weaker edges while higher threshold (100) preserves stronger edges only. The final result (all.jpg) demonstrates the complete edge detection output, showcasing how the algorithm effectively combines gradient information, noise suppression, and intelligent edge linking to produce clean, continuous boundaries. The implementation follows standard Canny edge detection methodology while providing configurable parameters for threshold adjustment.