Paper currency defect detection algorithm using quaternion uniform strength
Autor: | Bangshu Xiong, Xiaolin Xu, Shan Gai |
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Rok vydání: | 2020 |
Předmět: |
0209 industrial biotechnology
Color difference Computer science ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION 02 engineering and technology Image (mathematics) Convolution 020901 industrial engineering & automation Artificial Intelligence Currency 0202 electrical engineering electronic engineering information engineering Key (cryptography) Range (statistics) 020201 artificial intelligence & image processing Quaternion Algorithm Software |
Zdroj: | Neural Computing and Applications. 32:12999-13016 |
ISSN: | 1433-3058 0941-0643 |
Popis: | 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. |
Databáze: | OpenAIRE |
Externí odkaz: | |
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