The MOBIDEM (MOBile IDEntity for the Masses) project was selected as part of the 21st FUI (Fonds Unique Interministériel) call and ran over a 36-month period, from 2016 to 2019. The consortium included several industrial partners, such as AriadNEXT (now IDnow), Oberthur Technologies (now IDEMIA), Oodrive, and the L3i Laboratory from the University of La Rochelle.
The goal of the MOBIDEM project was to make advanced electronic signature capabilities widely accessible—simple to use, low-cost, and legally robust. As part of the growing digitization of information exchange, mobile electronic signatures offer faster processes, reduced costs, improved customer experience, and help address challenges like long-term archiving and the environmental footprint of paper-based contracts.
To achieve its objectives, MOBIDEM developed a platform for issuing and using high-trust mobile electronic identities and signatures—without requiring prior in-person appointments. The Image Processing and Pattern Recognition group contributed to the project by designing methods for automatic user self-enrollment. This involved verifying the authenticity of identity documents captured via camera and checking whether the personal information and facial image provided by the user matched the content of the document. The approach focused on image-based analysis alone, with no additional sensors, and addressed both document forgery detection and biometric consistency.
Partners
Related Publications
[1]
Lê Duy Huỳnh • Yongchao Xu • Thierry Géraud. "Morphology-Based Hierarchical Representation with Application to Text Segmentation in Natural Images". Proceedings of the 23st International Conference on Pattern Recognition (ICPR). 2016. https://doi.org/10.1109/ICPR.2016.7900264.
[2]
Lê Duy Huỳnh • Yongchao Xu • Thierry Géraud. "Morphological Hierarchical Image Decomposition Based on Laplacian 0-Crossings". Mathematical Morphology and Its Application to Signal and Image Processing -- Proceedings of the 13th International Symposium on Mathematical Morphology (ISMM). 2017. https://doi.org/10.1007/978-3-319-57240-6_13.
[3]
Élodie Puybareau • Thierry Géraud. "Real-Time Document Detection in Smartphone Videos". Proceedings of the 24th IEEE International Conference on Image Processing (ICIP). 2018. https://doi.org/10.1109/ICIP.2018.8451533.