DocumentCode :
1648300
Title :
New Banknote Number Recognition Algorithm Based on Support Vector Machine
Author :
Shan Gai ; Guowei Yang ; Sheng Zhang ; Minghua Wan
Author_Institution :
Sch. of Inf. Eng., Nanchang Hangkong Univ., Nanchang, China
fYear :
2013
Firstpage :
176
Lastpage :
180
Abstract :
Detecting the banknote serial number is an important task in business transaction. In this paper, we propose a new banknote number recognition method. The preprocessing of each banknote image is used to locate position of the banknote number image. Each number image is divided into non-overlapping partitions and the average gray value of each partition is used as feature vector for recognition. The optimal kernel function is obtained by the semi-definite programming (SDP). The experimental results show that the proposed method outperforms MASK, BP, HMM, Single SVM classifiers.
Keywords :
feature extraction; financial data processing; mathematical programming; object recognition; support vector machines; BP; HMM; MASK; SDP; banknote image preprocessing; banknote number recognition algorithm; banknote serial number detection; business transaction; feature vector; nonoverlapping partitions; optimal kernel function; semidefinite programming; single SVM classifiers; support vector machine; Educational institutions; Equations; Hidden Markov models; Kernel; Mathematical model; Support vector machines; Training; Multiple Kernel Learning; Semi-definite programming; Support Vector Machine; banknote Number recognition;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Pattern Recognition (ACPR), 2013 2nd IAPR Asian Conference on
Conference_Location :
Naha
Type :
conf
DOI :
10.1109/ACPR.2013.115
Filename :
6778305
Link To Document :
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