Abstract
This paper presents a reliable coin recognition system that is based on a registration approach. To optimally align two coins we search for a rotation in order to reach a maximal number of colinear gradient vectors. The gradient magnitude is completely neglected. After a quantization of the gradient directions the computation of the induced similarity measure can be done efficiently in the Fourier domain. The classification is realized with a simple nearest neighbor classification scheme followed by several rejection criteria to meet the demand of a low false positive rate. © Springer-Verlag Berlin Heidelberg 2007.
Cite
CITATION STYLE
Reisert, M., Ronneberger, O., & Burkhardt, H. (2007). A fast and reliable coin recognition system. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 4713 LNCS, pp. 415–424). Springer Verlag. https://doi.org/10.1007/978-3-540-74936-3_42
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