Performance Evaluation of a Neural Network based Edge Detector for high-contrast images

| The performance of a neural network based edge detector for high-contrast images has been investigated both quantitatively and qualitatively. We have compared it's performance for both synthetic and natural images with those of four existing edge detection methods namely, Sobel's operator, Johnson proposed Contrast based Sobel operator, MarrHildreth's Laplacian-of-Gaussian (LoG) operator, and Canny's operator. We have also investigated it's noise immunity and compared with those of the above mentioned methods. We have found the performance of the neural network based edge detector to be consistently better, especially for images where the illumination varies widely.