Research on Restoration Algorithm of Halftone Anti-counterfeiting Images
Authors: 
Yumeng Zhen, Peng CaoAuthors Info & Claims
Pages 133 - 137
Abstract
The anti-counterfeiting information is implanted into the QR Code with tiny pixels as single halftone dot. This method to realize information hiding and anti-counterfeiting is one of the research hotspots in this field. When the mobile phone identifies the micro-scale anti-counterfeiting information of this type of QR Code, it is easy to be affected by factors such as mobile phone shake and out of focus, which will make the scanned QR Code image blurred and affect the effective identifying of the carried information. In order to obtain higher-quality images, this paper uses the BP neural network method to calculate the optimal mapping model between the blurred image and the original image according to the characteristics of hidden halftoning pseudo-random noise images, and then realizes the blurred image restoration. Compared with traditional methods, this method can effectively solve the problem of high-quality restoration of microstructure information in such halftone anti-counterfeiting blurred images.
References
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Chen Fangfang. Research on Halftone Composite Anti-counterfeiting Method and Algorithm[D]. Beijing institute of graphic communication,2020.
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Shen Yan, Li Shun Mo, Mao Jianguo, Xin Jianghui. Digital Image Restoration Techniques:A Review [J]. Journal of Image and Graphics,2009,14(09):1764-1775.
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Zhen Yumeng, Cao Peng, Feng Liuping, Chen Fangfang. Research on Pseudo-Random Noise Information Identification Technology of Printed Anti-Counterfeiting Image Based on Deep Learning [C]. // International Conference on Computer and Communication Systems. 2020:206-209.
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Published In
December 2020
266 pages
ISBN:9781450388559
DOI:10.1145/3446999
Copyright © 2020 ACM.
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Association for Computing Machinery
New York, NY, United States
Publication History
Published: 09 April 2021
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- Research-article
- Research
- Refereed limited
Funding Sources
- General Program of National Natural Science Foundation of China
- School-level research project of Beijing Institute of Graphic Communication
- Beijing Fund-Municipal Education Commission Joint Project
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ICIT 2020
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