Measurement of Roughness Using Image Processing

A surface roughness measurement technique, based on an optical method using a computer vision system, was investigated for applicability to inprocess monitoring of surface quality. The developed vision system uses a CCD camera for scanning gray-scale images from an area of the machined workpiece. This images were analysed with digital image processing system. Some new optical roughness parameters were derived from the images based on their histograms and optical objects of machined surface. New parameters were plotted against the corresponding average roughness values (Ra ) determined using a stylus method. The resulting curves were researched to determine which optical parameters are optimal for use in the surface monitoring system. As most useful were a number of dark objects of the image and coefficient of variation of the histogram of inspected surface.