A new approach to edge detection

Abstract

This paper introduces the discrete singular convolution (DSC) algorithm for edge detection. Two classes of new edge detectors, DSC edge detector (DSCED) and DSC anti-noise edge detector (DSCANED), are proposed for the detection of multiscale edges. The DSCED is capable of extracting the fine details of images, whereas DSCANED is robust against noise. The combination of two classes of DSC edge detectors provides an efficient and reliable approach to multiscale edge detection. Computer experiments are carried out for extracting edge information from real images, with and without the contamination of Gaussian white noise. Sharp image edges are obtained from a variety of sample images, including those that are degraded to a peak-signal-noise-ratio (PSNR) of 16 dB. Some of the best results are attained from a number of standard test problems. The performance of the proposed algorithm is compared with many other existing methods, such as the Sobel, Prewitt and Canny detectors. © 2002 Pattern Recognition Society. Published by Elsevier Science Ltd. All rights reserved.