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Paper currency defect detection algorithm using quaternion uniform strength

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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.

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Acknowledgements

This work is partially supported by National Natural Science Foundation of China under Grant 61563037, 61866027; The Jiangxi Science Fund for Distinguished Young Scholars under Grant 20192ACB21032; Outstanding Youth Scheme of Jiangxi Province under Grant 20171BCB23057; Key research project of Jiangxi Province under Grant 20171BBE50013.

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  1. School of Information Engineering, Nanchang Hangkong University, Nanchang, 330063, China

    Shan Gai, Xiaolin Xu & Bangshu Xiong

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  1. Shan Gai
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  2. Xiaolin Xu
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  3. Bangshu Xiong
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Correspondence to Shan Gai.

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Gai, S., Xu, X. & Xiong, B. Paper currency defect detection algorithm using quaternion uniform strength. Neural Comput & Applic 32, 12999–13016 (2020). https://doi.org/10.1007/s00521-020-04745-6

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