Data Mining for Automated Visual Inspection

This paper addresses an automatic knowledge discovery process from a database of images in a context of Automated Visual Inspection (AVI). AVI is the field of computer vision addressing quality inspection of industrial products, even under informal quality models. When modelling informal knowledge, one of the most critical point turns out to be the correct and efficient translation of human experience into a set of rules. The paper focuses on the use of machine learning in inspection of industrial workpieces. It shows how machine learning can be exploited for data mining purposes and more specifically for selecting a minimal set of visual primitives, in order to perform reliable and robust classification of the inspected components. Eventually, the industrial application and the inspection system are presented in details.