Measuring the Quality of Hand and Surface Grinding Images by Applying Image Processing Tools of Scilab Software

Abstract

Powerful and resourceful Image Processing techniques can be applied in the field of manufacturing engineering to understand a good number of quality attributes. In this research, the focus has been to apply the edge detection algorithms of Canny, Prewitt and Sobel to identify the quality of hand grinding and surface grinding done on standard size steel metals flats. The edge detected images are compared with the reference good grinded surface images to understand the similarity between them. Multiple samples taken from a laboratory environment are considered for the comparison. Based on the results obtained it is found that Canny edge detection function is able to find a good number of defects in the given set of samples. It is also found that the grinding done in each case is only around 25% perfect even if the Sobel algorithm is used for the surface edge detections.