Vision system for classification of metallic tokens using the selective stereo gradient method
Markus Adameck, Michael Hossfeld, Manfred Eich · Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE · 2002
This paper presents a vision system whose purpose is to detect topographies of high reflective, metallic surfaces of minted tokens. We call this technique 'Selective Stereo Gradient Method' (SSGM). The objective is to decide whether the token belongs to a reference class or not. The most important property of the SSGM is that the classification can not be deceived by a photographic image and hence yields high fraud protection. To achieve this a 3 sector 120# LED illumination is used for generating three images under different illumination directions. The comparison between these three sequentially taken images leads to a discrimination between a real object with 3 D topography and a photographic image. The experimental setup and special illumination conditions are described. Rotation and translation invariance of the recognition and classification process are implemented. This is achieved by image transformation into a suitable coordinate system. A specimen will be identified to belong to the class of interest if, in a subsequent template matching step, selected patterns taken from the class reference object, can be successfully identified. If a first pattern is found additional patterns will be searched for. The classification statistics results will be reported for metallic tokens.