2006/10/18 by Yu Zhang, Y. Zhang, Peter Rockett +1
Computer Science · Engineering · #Image and Object Detection Techniques #Industrial Vision Systems and Defect Detection #Medical Image Segmentation Techniques
paper · doi:10.1109/tip.2006.881964
openalex publication_date 2006/10/18 · openalex created_date 2025/10/10 · openalex updated_date 2026/06/26
We have investigated the operating point of the Canny edge detector which minimizes the Bayes risk of misclassification. By considering each of the sequential stages which constitute the Canny algorithm, we conclude that the linear filtering stage of Canny, without postprocessing, performs very poorly by any standard in pattern recognition and achieves error rates which are almost indistinguishable from a priori classification. We demonstrate that the edge detection performance of the Canny detector is due almost entirely to the postprocessing stages of nonmaximal suppression and hysteresis thresholding.