A reliable method for paper currency recognition based on LBP

Author

Guo, Junfang ; Zhao, Yanyun ; Cai, Anni

Author_Institution

Multimedia Commun. & Pattern Recognition Labs., Beijing Univ. of Posts & Telecommun., Beijing, China

fYear

2010

fDate

24-26 Sept. 2010

Firstpage

359

Lastpage

363

Abstract

Paper currency recognition with good accuracy and high processing speed has great importance for banking system. How to extract high quality monetary features from currency images is a key problem in paper currency recognition. Based on the traditional local binary pattern (LBP) method, an improved LBP algorithm, called block-LBP algorithm, is proposed in this paper for characteristic extraction. The proposed method has advantages of simplicity and high speed. The experimental results show that this improved method has a high recognition rate, as well as robustness for noise and illumination change.

Keywords

banking; feature extraction; image denoising; image recognition; lighting; LBP; banking system; currency image; high quality monetary feature extraction; illumination change; image denoising; local binary pattern; paper currency recognition; Artificial neural networks; Feature extraction; Histograms; Mathematical model; Pattern recognition; Pixel; Training; LBP algorithm; feature extraction; paper currency recognition;

fLanguage

English

Publisher

ieee

Conference_Titel

Network Infrastructure and Digital Content, 2010 2nd IEEE International Conference on

Conference_Location

Beijing

Print_ISBN

978-1-4244-6851-5

Type

conf

DOI

10.1109/ICNIDC.2010.5657978

Filename

5657978