Classifying Recaptured Identity Documents Using the Biomedical Meijering and Sato Algorithms

Authors

John Magee, Technological University DublinFollow
Stephen Sheridan, Technological University DublinFollow
Christina Thorpe, Technological University DublinFollow

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Publisher

Technological University Dublin

Related Paper

https://arrow.tudublin.ie/diraacon/5/

Description

Recaptured identity documents are a low-cost, high-risk threat to modern eKYC systems. Bad actors can easily manipulate images and print them. Existing solutions typically demand manual review of remotely captured identity documents, this is expensive and does not scale. In 2022, the UK National Crime Agency estimated fraud cost business hundreds of billion pounds per year and document forgery is an area of investigation by Europol.

Publication Date

2023

Keywords

Capturing, identity documents, Meijering, Sato, algorithm

Disciplines

Computer Sciences

Supervisors

Stephen Sheridan, Christina Thorpe

Conference

First Annual Teaching and Research Showcase 2023

DOI

https://doi.org/10.21427/22ZK-H530

Creative Commons License

This work is licensed under a Creative Commons Attribution-NonCommercial-Share Alike 4.0 International License.

Recommended Citation

Magee, J., Sheridan, S., & Thorpe, C. (2023). Classifying recaptured identity documents using the biomedical Meijering and Sato algorithms. Technological University Dublin. DOI: 10.21427/22ZK-H530