Issue |
E3S Web of Conf.
Volume 389, 2023
Ural Environmental Science Forum “Sustainable Development of Industrial Region” (UESF-2023)
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|
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Article Number | 02023 | |
Number of page(s) | 9 | |
Section | Environmental Protection and Pollution Control | |
DOI | https://doi.org/10.1051/e3sconf/202338902023 | |
Published online | 31 May 2023 |
Evaluating methods of anti-spoofing of living entities and propose solutions
1 Vietnam Maritime University, 484 Lach Tray, Le Chan, Hai Phong, Viet Nam
2 National Research Tomsk State University, Tomsk, 634050, Russian Federation
3 Saigon - Hanoi Commercial Joint Stock Bank, Hanoi, Vietnam
* Corresponding author: cuongntit@vimaru.edu.vn
In recent 10 years, object recognition technology has been widely developed with many solutions given with high practical applications. However, with the development of digital devices, the resulting images can be provided from a variety of sources: photos taken (or video captured) directly from living entities, photos printed on paper or photos (video) is displayed on the computer screen or mobile phone. Therefore, the image detection obtained from the camera system directly from the living entity or from images are printed/displayed to determine the correct object is the problem posed. The article focuses on the issue of anti-spoofing of human faces with the content outlining the measures applied in the banking system, the access monitoring system in accordance with the previous registration of these faces there. The purpose is to validate customer or user information such as: wink test results, response to random challenges, etc. The article evaluates the advantages and disadvantages of these methods, after that proposes an anti-spoofing solution by using 3D camera and combining with convolutional neural network to create a more accurate anti-spoofing system.
© The Authors, published by EDP Sciences, 2023
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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