Machine Vision Based Image Processing Techniques for Surface Finish and Defect Inspection in a Grinding Process

Abstract

Inspection of surface finish and defects in a machined surface is critically important for ensuring the functional requirements in high precision applications. This paper presents simple image processing techniques for surface finish and defect inspection of grinding surface. Canny edge detection and histogram analysis were applied for understanding the effect of surface finish on pixel intensity distribution & edge detection using a machine vision system for a mild steel rectangular specimens. The gray scale intensity distribution on the image is observed using pixel level values. Canny Edge detection algorithm is implemented and the results are compared visually to observe the edge detection under various grinding surface conditions. An experimental analysis is presented as a base for further research work on object surface classification under varying surface grinding conditions.