Exploiting Symbolic Learning in Visual Inspection

. The paper describes the use of data analysis techniques in the computer-vision inspection of industrial workpieces. Computer-vision inspection aims at accomplishing quality verification of fabricated parts by means of automated visual procedures. Gathering the visual information into models proves a critical task, especially when subjective judgement is involved in quality verification. In this work, intelligent data analysis techniques based on symbolic learning by examples have been explored in order to automatically devise and parametrize effective quantitative models. The paper reports and discusses the experimental results achieved in an industrial application. 1 Introduction Inspection of fabricated components is a fundamental part of a production process, aiming at the respect of predefined quality levels in final products. Since human inspection carries high costs and scarce reliability, automated techniques are required to substitute for or integrate the human work. An impo..