Edge detection methods

TL;DR: An attempt is made to study the performance of most commonly used edge detection techniques for image segmentation and the comparison of these techniques are compared with one another so as to choose the best technique for edge detection segment image.

Abstract: Edge detection is a type of image segmentation techniques which determines the presence of an edge or line in an image and outlines them in an appropriate way. The main purpose of edge detection is to simplify the image data in order to minimize the amount of data to be processed. Generally, an edge is defined as the boundary pixels that connect two separate regions with changing image amplitude attributes such as different constant luminance and tristimulus values in an image. In this paper, we present methods for edge segmentation of images; we used five techniques for this category; Sobel operator technique, Prewitt technique, Laplacian technique, Canny technique, Roberts technique, and they are compared with one another so as to choose the best technique for edge detection segment image. These techniques applied on one image to choose base guesses for segmentation or edge detection image. In this paper an attempt is made to study the performance of most commonly used edge detection techniques for image segmentation and also the comparison of these techniques is carried out with an experiment by using MATLAB software. We will use the edges to find congruence between objects.