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Communication Dans Un Congrès Année : 2019

Quick Response Encoding of Human Facial Images for Identity Fraud Detection

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Advancements in printing and scanning technology enable fraudsters to tamper with identity documents such as identity cards, drivers’ licenses, admit cards, examination hall tickets and academic transcripts. Several security features are incorporated in important identity documents to counter forgeries and verify genuineness, but these features are often lost in printed versions of the documents. At this time, a satisfactory method is not available for authenticating a person’s facial image (photograph) in a printed version of a document. Typically, an official is required to check the person’s image against an image stored in an online verification database, which renders the problem even more challenging.This chapter presents an automated, low-cost and efficient method for addressing the problem. The method employs printed quick response codes corresponding to low-resolution facial images to authenticate the original and printed versions of identity documents.
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hal-02534605 , version 1 (07-04-2020)

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Shweta Singh, Saheb Chhabra, Garima Gupta, Monika Gupta, Gaurav Gupta. Quick Response Encoding of Human Facial Images for Identity Fraud Detection. 15th IFIP International Conference on Digital Forensics (DigitalForensics), Jan 2019, Orlando, FL, United States. pp.185-199, ⟨10.1007/978-3-030-28752-8_10⟩. ⟨hal-02534605⟩
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