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A Mobile Computing Method Using CNN and SR for Signature Authentication with Contour Damage and Light Distortion
Joint Authors
Zhai, Ke
Liu, Chi Harold
Li, Yujie
Wang, Mei
Source
Wireless Communications and Mobile Computing
Issue
Vol. 2018, Issue 2018 (31 Dec. 2018), pp.1-10, 10 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2018-06-25
Country of Publication
Egypt
No. of Pages
10
Main Subjects
Information Technology and Computer Science
Abstract EN
A signature is a useful human feature in our society, and determining the genuineness of a signature is very important.
A signature image is typically analyzed for its genuineness classification; however, increasing classification accuracy while decreasing computation time is difficult.
Many factors affect image quality and the genuineness classification, such as contour damage and light distortion or the classification algorithm.
To this end, we propose a mobile computing method of signature image authentication (SIA) with improved recognition accuracy and reduced computation time.
We demonstrate theoretically and experimentally that the proposed golden global-local (G-L) algorithm has the best filtering result compared with the methods of mean filtering, medium filtering, and Gaussian filtering.
The developed minimum probability threshold (MPT) algorithm produces the best segmentation result with minimum error compared with methods of maximum entropy and iterative segmentation.
In addition, the designed convolutional neural network (CNN) solves the light distortion problem for detailed frame feature extraction of a signature image.
Finally, the proposed SIA algorithm achieves the best signature authentication accuracy compared with CNN and sparse representation, and computation times are competitive.
Thus, the proposed SIA algorithm can be easily implemented in a mobile phone.
American Psychological Association (APA)
Wang, Mei& Zhai, Ke& Liu, Chi Harold& Li, Yujie. 2018. A Mobile Computing Method Using CNN and SR for Signature Authentication with Contour Damage and Light Distortion. Wireless Communications and Mobile Computing،Vol. 2018, no. 2018, pp.1-10.
https://search.emarefa.net/detail/BIM-1216078
Modern Language Association (MLA)
Wang, Mei…[et al.]. A Mobile Computing Method Using CNN and SR for Signature Authentication with Contour Damage and Light Distortion. Wireless Communications and Mobile Computing No. 2018 (2018), pp.1-10.
https://search.emarefa.net/detail/BIM-1216078
American Medical Association (AMA)
Wang, Mei& Zhai, Ke& Liu, Chi Harold& Li, Yujie. A Mobile Computing Method Using CNN and SR for Signature Authentication with Contour Damage and Light Distortion. Wireless Communications and Mobile Computing. 2018. Vol. 2018, no. 2018, pp.1-10.
https://search.emarefa.net/detail/BIM-1216078
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1216078