Goal of this project is the automatisation of online-identifications using a videostream. During the project, different imaging methods and face validation frameworks are tested and evaluated. The different safety features of passports are investigated and methods implemented, to determine if a certain features is present or not. Main aspect of this project is the secure identification and different techniques are used to identify if the user attempts to deceive the system.
Duration
01.04.2016 – 31.08.2016
Partner
Credi2 GmbH
Funding
Austrian Research Promotion Agency FFG – Basisprogramm
Publications 1
2018
Model-Based Image Processing Approaches For Automated Person Identification And Authentification In Online Banking
Pointner A., Krauss O., Freilinger G., Strieder D., Zwettler G. Proceedings of the 30th European Modeling and Simulation Symposium EMSS2018, Budapest, Ungarn, 2018.
In this thesis the applicability of image processing algorithms for robust person identification is evaluated. At first the state of the domain in person identification will be analyzed in detail. Later their automation possibilities will be identified. The first step is to analyze the process and represent it in the BPMN. Therefore the key areas will be modeled to achieve a legal implementation. The three main components in the process, which are implemented by this thesis, are: the recognition of the identity card, the validation of safety features, as well as the reading of the machine-readable areas. The process starts with detecting an identity card inside a picture. The algorithmic foundations are explained for this purpose, as well as an implementation of Hough-Lines, which is used for the detection, is provided. After a successful detection and equalization of the identity card, the next step is to validate the Holograms. Therefore binary and color segmentation is used to analyze the ID card. After that the binary image can be compared to a template. With a simple pixel comparison a confidence value can be calculated. This value will be analyzed over multiple images to make a clear statement of the validity of the hologram. Later on the thesis describes the reading of the machine readable part using optical character recognition (OCR). In this process step mostly preprocessing algorithms are implemented. The actual OCR will then be provided by an OCR Framework called Tesseract. Finally, the different results of each step are evaluated. The result shows that the hologram detection has some deficits in its current implementation. Therefore a final chapter describes improvement and optimization possibilities.
