A Vision System for Detecting Paint Faults on Painted Slates

This paper is concerned with the problem of how to detect paint type defects on painted slates using machine vision. We begin by outlining the motivations for this research and present a review of research in related areas before proceeding with a process description and a categorization of typical paint defects. We describe the test bed built to replicate factory conditions and the testing of image capture techniques. We discuss problems we confronted such as getting a sufficiently strong signal level from the slate, the effects of the slate surface profile on image capture and how we dealt with these problems. The third principal challenge was to generate a strong signal to noise ratio for each defect type so that a computationally inexpensive image processing method becomes viable. We demonstrate ...