Method for Distinguishing Mixed Waste-Printed Circuit Board Using Image Processing

Abstract

Waste-printed circuit boards (WPCBs) are recycled in nonferrous metal smelters to recover valuable metals. Workers visually determine the similarity between images of previously handled WPCBs and images of substrates to be measured for their valuable metal content and classify the substrates to so that appropriate processing methods can be selected. In particular, groups of substrates of multiple types (mixed WPCBs) are more difficult for workers to process. Therefore, in this study, we propose a method to evaluate different types of substrates using segmented images of mixed WPCBs. Our results show that the proposed approach was able to classify substrates appearing in segmented images well.