DocumentCode :
548923
Title :
Learning banknote fitness for sorting
Author :
Geusebroek, Jan-Mark ; Markus, Peter ; Balke, Peter
Author_Institution :
Inf. Inst., Univ. of Amsterdam, Amsterdam, Netherlands
Volume :
1
fYear :
2011
fDate :
28-29 June 2011
Firstpage :
41
Lastpage :
46
Abstract :
In this work, a machine learning method is proposed for banknote soiling determination. We apply proven techniques from computer vision to come up with a robust and effective method for automatic sorting of banknotes. The proposed method is evaluated with respect to various invariance classes. The method shows excellent performance on a large validation set of over 8,000 banknotes from the Eurosystem, while being learned on only 300 banknotes per denomination.
Keywords :
bank data processing; computer vision; learning (artificial intelligence); automatic sorting; banknote fitness; banknote soiling determination; banknote sorting; computer vision; machine learning; Color; Feature extraction; Image color analysis; Machine learning; Pixel; Printing; Training;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Pattern Analysis and Intelligent Robotics (ICPAIR), 2011 International Conference on
Conference_Location :
Putrajaya
Print_ISBN :
978-1-61284-407-7
Type :
conf
DOI :
10.1109/ICPAIR.2011.5976909
Filename :
5976909
Link To Document :
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