Title :
Bill classification by using the LVQ method
Author :
Kosaka, Toshihisa ; Omatu, Sigeru ; Fujinaka, Toru
Author_Institution :
Glory Ltd., Himeji, Japan
Abstract :
For pattern classification problems the neuro-pattern recognition, which is the pattern recognition based on the neural network approach, has been increasingly popular since it can classify various patterns similar to human beings. In this paper we adopt the learning vector quantization (LVQ) method to classify the various bank notes. The reasons to use LVQ are that it can process the unsupervised classification and treat many input data with small computational burdens. We construct the LVQ network to classify the Italian Liras. Compared with a conventional pattern matching technique, which has been adopted as a classification method, the proposed method has shown excellent classification results
Keywords :
bank data processing; learning (artificial intelligence); neural nets; pattern classification; vector quantisation; Italian Liras; LVQ algorithm; bank notes; competitive neural network; learning vector quantization; pattern classification; Biological neural networks; Clustering algorithms; Focusing; Humans; Neurons; Pattern classification; Pattern matching; Pattern recognition; Pixel; Size measurement;
Conference_Titel :
Systems, Man, and Cybernetics, 2001 IEEE International Conference on
Conference_Location :
Tucson, AZ
Print_ISBN :
0-7803-7087-2
DOI :
10.1109/ICSMC.2001.973483