Citation

Ng, Wen Dong and Yeoh, Eng Thiam (2022) Multi-Factor Verification of International Passports. Journal of Logistics, Informatics and Service Science, 9 (4). pp. 72-90. ISSN 2409-2665

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Abstract

This paper describes the design and development of a passport verification Web service. This service allows users to check and confirm their passports by submitting a snapshot of the passport's principal data page. The techniques used for developing the verification Web service included Python, Flask, OpenCV, and Tesseract OCR methods. The difficulty of generating a high accuracy verification result owing to numerous environmental elements, such as the quality of the uploaded images, the angle of the uploaded images, content tampering is the research focus of this project. We propose a multi-factor verification to increase the accuracy of verification thus reducing the probability of a fraudulent passport. The multi-factor verification is to combine the landmark detection, security feature detection, and fraud detection. In landmark detection, the algorithm will detect various landmarks on the passport document. Some of the landmarks containing text could be further processed to obtain additional information for verification. For security feature detection, the algorithm will detect security elements on the passport document which varies for different countries. For fraud detection, the algorithm will perform blurriness detection and validity detection to verify the information detected for the authenticity of the passport document. A set of passport images for Malaysia, Singapore, and Indonesia is used to test the algorithms. The results showed that the combined multi-factor verification slightly improved the verification compared to the separate algorithms.

Item Type:	Article
Uncontrolled Keywords:	Passport verification, multi-factor verification, landmark detection, security feature detection, fraud detection, Web service
Subjects:	Q Science > QA Mathematics > QA71-90 Instruments and machines > QA75-76.95 Calculating machines
Divisions:	Faculty of Computing and Informatics (FCI)
Depositing User:	Ms Nurul Iqtiani Ahmad
Date Deposited:	22 Mar 2023 02:24
Last Modified:	22 Mar 2023 02:33
URII:	http://shdl.mmu.edu.my/id/eprint/11257

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