Development of a Machine Vision System for the Average Roughness Measurement of Shot- and Sand-Blasted Surfaces

Abstract

This article presents a machine vision system for measuring the arithmetic average roughness of shot- and sand-blasted surfaces. In the developed system, a digital microscope was used for capturing surface images after shot- and sand-blasting processes. The captured grayscale images were analyzed with the proposed algorithm using Otsu’s global thresholding and a size bandpass filter. The algorithm detected white regions associated with the specular reflection of light on a binary image, and then calculated the size of selected regions. One-way ANOVA was used to identify the relation between the size of the regions and the arithmetic average roughness of blasted surfaces. It was noted that the average size of white regions showed a linear relation to the arithmetic average roughness of both shot- and sand-blasted surfaces. Different abrasives (shot or sand) were found to bring about differences in the rate of change of the average size within a chosen roughness range. When a surface image with unknown roughness is given, it is possible to predict the arithmetic average roughness on the basis of the relation. This machine vision system enables the fast and low-cost roughness measurement of shot- and sand-blasted surfaces. Thus, it could be useful in a quality inspection for shot- and sand-blasting.

Keywords

• arithmetic average surface roughness
• machine vision
• specular reflection
• blasting