Document Type
Conference Paper
Disciplines
Computer Sciences
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.
Publication Details
Presented at the APWG.EU conference on 21st June 2023 in Dublin.
https://ceur-ws.org/