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What is Multi-Currency Banknote Classification Algorithm about?

This paper presents an efficient algorithm for classifying multi-national banknote images based on size information and multi-template correlation matching. The algorithm achieved 100% accuracy for unsoiled banknotes and 99.8% for soiled ones, with an average processing time of 4.83 ms per banknote. It utilizes a size map for initial grouping and incorporates post-processing to handle image degradations.

Author

eshaman13

Language

EN