An expert system for industrial machine vision

An expert system for algorithm design for industrial machine vision is presented. Its knowledge base includes human experts´ knowledge about image processing techniques, and it is capable of solving given vision problems. As a problem domain, the authors have chosen vision algorithms for a parts feeder, which determines the attitude of mechanical parts on a conveyor belt and rejects parts with inappropriate attitudes. The expert system for a parts feeder is designed to consist of three components: a feature selection expert, an image processing expert, and a decision tree generator. The knowledge necessary for the design of a vision algorithm for determining the attitudes of parts is discussed. A framework for representing the knowledge needed in order to find solutions to pattern classification problems is established