An improved segmentation method for defects inspection on steel roller surface

Abstract

In the field of metal rolling, the quality of the steel roller’s surface is significant for the final rolling products, e.g. metal sheets or foils. Besides the dimensional accuracy and surface roughness, the optical uniformity of the roller surface is also required for high quality rolling application. The typical optical defects of rollers after finish grinding include speckles, chatter marks, feed traces, and combination of all above. Unlike surface roughness, the optical defects can hardly be characterized by the topography or scanning electrical microscope measurement. Only the inspection by bared eyes of experienced engineers appears to be the effective manner for surface optical defects examination for large steel rollers. In this paper, an on-site machine vision system is designed to add on to the roller grinding machine to capture the surface image, and then an improved optical defects segmentation algorithm is developed based on the active contour model. Finally, experiments are carried out to verify the efficacy of the improved model.