e-Counterfeit: a mobile-server platform for document counterfeit detection
This addresses document fraud for non-expert users in scenarios like ID or banknote verification, but it is incremental as it builds on existing texture analysis methods.
The paper tackles the problem of detecting counterfeit identity documents forged by scan-printing operations, proposing texture analysis to extract validation features from security backgrounds, and results in an end-to-end mobile-server platform that includes a crowdsourcing mode for incremental training.
This paper presents a novel application to detect counterfeit identity documents forged by a scan-printing operation. Texture analysis approaches are proposed to extract validation features from security background that is usually printed in documents as IDs or banknotes. The main contribution of this work is the end-to-end mobile-server architecture, which provides a service for non-expert users and therefore can be used in several scenarios. The system also provides a crowdsourcing mode so labeled images can be gathered, generating databases for incremental training of the algorithms.