A novel image-based method for conveyor belt rip detection

Conveyor belts of all types are prone to rips from impact by sharp objects in the flow path, which can lead to expensive belt failure. In this paper, we present a novel method for detecting conveyor belt rips. In contrast to previous work on conveyor belt rip detection, the proposed method has a built-in real/false rip classification mechanism, which we believe will serve as a quite useful reference to designers of vision-based conveyor belt monitoring systems who wish to reduce false rip detection rates.