Comparison of edge detection algorithm for part identification in a vision guided robotic assembly system

Abstract

Machine vision system has a major role in making robotic assembly system autonomous. Part detection and identification of the correct part are important tasks which need to be carefully done by a vision system to initiate the process. This process consists of many sub-processes wherein, the image capturing, digitizing and enhancing, etc. do account for reconstructive the part for subsequent operations. Edge detection of the grabbed image, therefore, plays an important role in the entire image processing activity. Thus one needs to choose the correct tool for the process with respect to the given environment. Five different algorithms for edge detection of objects are considered here for comparison of their performance. The work is performed on the Matlab R2010a Simulink. The algorithm considered here are Canny’s, Robert, Perwitt, Sobel, and LOG edge detection algorithms. An attempt has been made to find the best algorithm for the problem. It is found that Canny’s edge detection algorithm gives better result with negligible error for the intended task.