Title

Classifying recaptured identity documents using the biomedical Meijering and Sato algorithms

Authors

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

Document Type

Conference Paper

Disciplines

Computer Sciences

Publication Details

Presented at the APWG.EU conference on 21st June 2023 in Dublin.

https://ceur-ws.org/

Abstract

Recent research into the domain of identity document recapture detection demonstrated the capability of the Meijering filter, a biomedical image processing algorithm, to detect features present in recaptured documents. Manipulation of identity documents using image processing software is a low-cost, high-risk threat to modern financial systems, opening these institutions to fraud through crimes related to identity theft. In this paper we extend the research into the application of biomedical image processing algorithms, including the Meijering filter and the Sato filter. We build support vector machine and decision tree classifiers based on histograms of images generated from these filters and apply some rudimentary feature reduction techniques. The results show that both filters can be applied to this domain, with the Meijering filter slightly outperforming the Sato filter in most tests

DOI

https://doi.org/10.21427/4962-FE30

Recommended Citation

Magee, J., Sheridan, S., & Thorpe, C. (2023). Classifying recaptured identity documents using the biomedical Meijering and Sato algorithms. CEUR-WS.org. DOI: 10.21427/4962-FE30

Funder

None

Creative Commons License

This work is licensed under a Creative Commons Attribution 4.0 International License.