Quantification of worn surface using digital image processing

Abstract

Digital Image processing can be used in many areas in some way or the other from medical to satellite applications. The efficiency of the machine is reduced and substantial energy loss was observed by mechanical wear of the contacting surfaces in materials rubbing against each other. The most common test method reported in the literature is pin-on-disc wear testing. The brass material is used for this study. The images of the worn material surface were obtained from the metallurgical inverted microscope. Adaptive Otsu’s global thresholding method is used as the first step of segmentation. The granulometry by opening and closing on binary image detects the wear shapes such as scars, grooves, and pits. Shape descriptors quantify the shape of the crater which is an irregular circular-shaped patch. Craters are detected by morphological filtering using standard deviation. The boundary extraction tool extracts the overall worn area and its distribution across the material surface. The results reveal that it is possible to quantify and identify the mechanism of wear by obtaining the images using a CCD camera instead of highly sophisticated instruments like scanning electron microscope or atomic field microscope (AFM) etc., by using digital image processing.