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A Study on Hierarchical Recognition Algorithm of Multinational Banknotes Using SIFT Features
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 Title & Authors
A Study on Hierarchical Recognition Algorithm of Multinational Banknotes Using SIFT Features
Lee, Wang-Heon;
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In this paper, we not only take advantage of the SIFT features in banknote recognition, which has robustness to illumination changes, geometric rotation as well as scale changes, but also propose the hierarchical banknote recognition algorithm, which comprised of feature vector extraction from the frame grabbed image of the banknotes, and matching to the prepared data base of multinational banknotes by ANN algorithm. The images of banknote under the developed UV, IR and white illumination are used so as to extract the SIFT features peculiar to each banknotes. These SIFT features are used in recognition of the nationality as well as face value. We confirmed successful function of the proposed algorithm by applying the proposed algorithm to the banknotes of Korean and USD as well as EURO.
Banknote Recognition;Approximated Nearest Neighbour;RANSAC;Hierarchical Recognition;
 Cited by
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