RF Sign: : Signature Anticounterfeiting Real-Time Monitoring System Based on Single Tag
Authors: 
Biaokai Zhu, Qing Wei, Lu Li, Zejiao Yang, Wei Liu, Zirong You, Jiangfan Zhou, Ping Li, Jie Song, Sanman Liu, Deng-ao Li Academic Editor: Jian Feng LiAuthors Info & Claims
Biaokai Zhu, Qing Wei, Lu Li, Zejiao Yang, Wei Liu, Zirong You, Jiangfan Zhou, Ping Li, Jie Song, Sanman Liu, Deng-ao Li Academic Editor: Jian Feng LiAuthors Info & ClaimsAbstract
Signatures are one of the most important means to ensure the authenticity of documents and are commonly used in life and work. In identifying imitation handwriting, it is easy to make mistakes that cannot correctly identify and evaluate different writing characteristics. In this paper, from the perspective of dynamic handwriting detection, we propose RF sign, a signature anticounterfeiting real-time monitoring model, which achieves passive recognition of signature behavior using only a single antenna with a single tag. The RF sign identifies different users by extracting fine-grained reflection features from the original RF signal. We introduced a dynamic time regularization and neural network technique for similarity calculation and signature recognition matching to achieve template matching and classification. We compiled a real-time signature handwriting detection system. The system effectively identifies the person’s signature by checking real-time spatial and temporal information. Comprehensive experiments show that the recognition accuracy of my signature can reach over 93% and is robust to input location, environmental changes, and user diversity.
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Copyright © 2023 Biaokai Zhu et al.
This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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Published: 01 January 2023
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