Back to Search Start Over

Paper currency defect detection algorithm using quaternion uniform strength.

Authors :
Gai, Shan
Xu, Xiaolin
Xiong, Bangshu
Source :
Neural Computing & Applications. Aug2020, Vol. 32 Issue 16, p12999-13016. 18p.
Publication Year :
2020

Abstract

In this paper, we propose a novel paper currency defect detection algorithm using quaternion uniform strength. We first build paper currency image preprocessing integration framework which includes intensity balancing, paper currency location, and geometric correction. We then propose a global–local paper currency image registration algorithm by moving key areas within certain range which can eliminate the false difference effectively. Finally, the quaternion uniform strength is calculated by using quaternion convolution edge detector. The defect degree of paper currency is determined by using the quaternion uniform color difference. The proposed algorithm is tested using different datasets from five countries: CNY, USD, EUR, VND, and RUB. The experimental results demonstrate that the proposed algorithm yields better results than the existing state-of-the-art paper currency defect detection techniques. The demo of the proposed paper currency defect detection algorithm will be publicly available. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
09410643
Volume :
32
Issue :
16
Database :
Academic Search Index
Journal :
Neural Computing & Applications
Publication Type :
Academic Journal
Accession number :
144745083
Full Text :
https://doi.org/10.1007/s00521-020-04745-6