Comparative Study on Edge Detection Methods using Image Processing

Abstract

An edge detection is the process of identifying and locating the discontinuities in an image. Hence, the process of an edge detection is one of the step-in image analyses and it is the key for solving many complex problems. Edge detection is a basic tool which can be used for the image processing applications to obtain the information from frames to extraction the feature and performing the segmentation process of an object. The edge detection used for object recognition, segmentation of an image, data compression and so on. Edge detection is one of the familiar methods for transforming an original image into edge image which can gain the benefits from changing the grey tones in an image. In this research paper, three edge detection algorithms namely Prewitt edge detection, Robert edge detection algorithm and Sobel edge detection algorithm are used to extract edges from the two type of images which is used to detect the edge of an image. Performance factors are analysed namely accuracy and speed are used to find out which algorithm works better. From the experimental results, it is observed that the Sobel edge detection algorithm works better than other two edge detection algorithms.