Cork stopper classification using FPGAs and digital image processing techniques

In this paper we study the use of FPGAs as part of an industrial inspection system. More exactly, to evaluate the cork stopper quality applying real-time image processing. Our system uses the HOT2-XL PCI board, a hardware module library implementing some of the most common operations for image processing, and a Visual C++ application in order to validate the hardware designs and manage the platform. Also, we propose an algorithm for obtaining different features of cork stopper defects, so allowing their classification. Finally, the practical results obtained with this algorithm are presented along with the conclusions and future work.