AN EFFICIENT APPROACH FOR IMPROVING CANNY EDGE DETECTION ALGORITHM

Abstract

Edge detection is one of the most important stages in digital image processing and medical image processing. The Canny edge detector is widely used in computer vision and medical imaging to locate sharp intensity changes and to find object boundaries in an image. The Canny edge detection algorithm is most widely used edge detection algorithm because of its advantages. The Canny edge detector classifies a pixel as an edge if the gradient magnitude of the pixel is larger than those of pixels at both its sides in the direction of maximum intensity change. In this paper an efficient approach for improving canny edge detection Algorithm has been proposed which uses variable sigma and thresholding for different parts of the medical image. The results of experiments show that it performs better to find edges for low resolution angiography images