An application of geometric aspects of variational autoencoder model to forgery detection of scanned documents

Igor Janiszewski; Dmitry Slugin; Elena Andreeva

doi:10.1117/12.2587483

4 January 2021 An application of geometric aspects of variational autoencoder model to forgery detection of scanned documents

Igor Janiszewski, Dmitry Slugin, Elena Andreeva

Author Affiliations +

Proceedings Volume 11605, Thirteenth International Conference on Machine Vision; 116051H (2021) https://doi.org/10.1117/12.2587483
Event: Thirteenth International Conference on Machine Vision, 2020, Rome, Italy

Abstract

The paper proposes an approach for matching of digitized copies of business documents. This task arises when comparing two versions of the same document, genuine and forgery, to find possible modifications, for example in the banking sector during the conclusion of contracts in paper form to avoid possible fraud. The matching method of two documents based on comparison images of text lines using Variational Autoencoder (VAE) trained on genuine images and calculation Fisher information metric to find modifications. Experiments were conducted on the public Payslips dataset (in French). The results show the high quality and reliability of finding document forgeries and are compared to the results of the method which applies OCR and image matching.

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Igor Janiszewski, Dmitry Slugin, and Elena Andreeva "An application of geometric aspects of variational autoencoder model to forgery detection of scanned documents", Proc. SPIE 11605, Thirteenth International Conference on Machine Vision, 116051H (4 January 2021); https://doi.org/10.1117/12.2587483

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