Foreign object detection via texture analysis

Abstract

This paper describes a monitoring system which detects contaminants such as pieces of stone or fragments of glass in food stuffs. The X-ray images of the food stuffs are irregular and highly textured and are thus analysed using an artificial neural network technique for texture recognition. The advantage over the existing methods of inspection is that they achieve a greater capability of reliably locating the contaminants. This paper will show that neural nets comprised of a few nodes can be successfully used in the real-world for industrial applications.