A Comparative Study of Edge Detection Techniques in Digital Images


ImanKadhim Ajlan*, AlaaAbdulhusseinDaleh Al-magsoosi, Hayder G. Murad


College of medicine – Wasit University, Iraq

College for pure science University of Wasit, Iraq

Corresponding Author Email: [email protected]; [email protected]

This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Digital image processing consists of the manipulation of images using digital computers. Its use has been increasing exponentially in the last decades. Everyone is concerned and demands a system as faster, more accurate, cheaper and more extensive computation. An image is defined as an array, or a matrix, of square pixels arranged in rows and columns. Image processing is a procedure of converting an image into digital form and carry out some operation on it, in order to get an improved image and to retrieve some important information from the image. It involves various steps like image analysis, image segmentation, edge extraction, image compression etc. In this paper, three essential edge detection methods , programmed to determine the best way in terms of accuracy and time, based on the alleged masks, i.e., arrays applied to the image sequentially is according to each mask , come up with a new image containing only the edges of the original image. These three methods are Sowell Method, Laplace Method and Robert Method. The outcome of applying these methods were , the best results obtained from the Laplace method because it highlights the shapes contours more clearly. Robert’s approach is comparatively better than Sobel’s edge detection methods.