Find it! Fraud Detection Contest Report

Chloé Artaud (1) , Nicolas Sidère (1) , Antoine Doucet (1) , Jean-Marc Ogier (1) , Vincent Poulain d'Andecy (2)

1 L3I - Laboratoire Informatique, Image et Interaction - EA 2118
2 Yooz ITESOFT-Yooz Group

This paper describes the ICPR2018 fraud detection contest, its data set, evaluation methodology, as well as the different methods submitted by the participants to tackle the predefined tasks. Forensics research is quite a sensitive topic. Data are either private or unlabeled and most of related works are evaluated on private datasets with a restricted access. This restriction has two major consequences: results cannot be reproduced and no benchmarking can be done between every approach. This contest was conceived in order to address these drawbacks. Two tasks were proposed: detecting documents containing at least one forgery in a flow of documents and spotting and localizing these forgeries within documents. An original dataset composed of images and texts of French receipts was provided to participants. The results they obtained are presented and discussed.

Domaines: Traitement du texte et du document; Traitement des images [eess.IV]; Vision par ordinateur et reconnaissance de formes [cs.CV]; Intelligence artificielle [cs.AI]

Chloé Artaud, Nicolas Sidère, Antoine Doucet, Jean-Marc Ogier, Vincent Poulain d'Andecy. Find it! Fraud Detection Contest Report. 24th International Conference on Pattern Recognition (ICPR 2018), Aug 2018, Beijing, China. pp. 13-18. ⟨hal-02316399⟩