e-Counterfeit: a mobile-server platform for document counterfeit detection

TL;DR

This paper introduces e-Counterfeit, a mobile-server platform utilizing texture analysis for detecting forged identity documents, offering an accessible service with crowdsourcing capabilities for continuous improvement.

Contribution

It presents an end-to-end mobile-server system for counterfeit detection that is user-friendly and supports crowdsourcing for database expansion and algorithm training.

Findings

Effective texture analysis features for counterfeit detection

End-to-end mobile-server architecture demonstrated

Crowdsourcing mode enables database growth

Abstract

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.