Automated visual inspection of pharmaceutical tablets in heavily cluttered dynamic environments

We present a framework for automated visual inspection of pharmaceutical tablets in heavily cluttered dynamic environments. A two light camera system is proposed, which acquires two images with different lighting directions. With two images, pose of each tablet in the scene is first estimated. Second, regions that are shadowed or overlapped by neighboring tablets are detected. The final analysis is then performed on the remaining areas of the tablets. The proposed framework was evaluated on a set of real pharmaceutical tablets, imaged with the proposed system inside a rotating drum. The rotating drum simulated the movement of the tablets inside the tablet coating machine. Acquired images were analyzed with the proposed framework and the analysis results were compared with a gold standard, which was prepared manually. With the proposed framework we detected 81% of defective tablets while 5% of good tablets were erroneously classified. The results indicate that the proposed framework is a viable approach for the on-line and in-line analysis of partly diffuse objects.