Defect detection and classification on web textile fabric using multiresolution decomposition and neural networks

In this paper a pilot system for defect detection and classification of web textile fabric in real-time is presented. The general hardware and software platform, developed for solving this problem, is presented while a powerful novel method for defect detection after multiresolution decomposition of the fabric images is proposed. This method gives good results in the detection of low contrast defects under real industrial conditions, where many types of noise are present. An artificial neural network, trained by a back-propagation algorithm, performs the defect classification in categories.