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This article is cited in 5 scientific papers (total in 5 papers)
INTERNATIONAL CONFERENCE ON MACHINE VISION
Towards a unified framework for identity documents analysis and recognition
K. B. Bulatovab, P. V. Bezmaternykhab, D. P. Nikolaevcb, V. V. Arlazarovab a Federal Research Center "Computer Science and Control" of Russian Academy of Sciences, Moscow
b Smart Engines Service LLC, Moscow
c Institute for Information Transmission Problems of the Russian Academy of Sciences (Kharkevich Institute), Moscow
Abstract:
Identity documents recognition is far beyond classical optical character recognition problems. Automated ID document recognition systems are tasked not only with the extraction of editable and transferable data but with performing identity validation and preventing fraud, with an increasingly high cost of error. A significant amount of research is directed to the creation of ID analysis systems with a specific focus for a subset of document types, or a particular mode of image acquisition, however, one of the challenges of the modern world is an increasing demand for identity document recognition from a wide variety of image sources, such as scans, photos, or video frames, as well as in a variety of virtually uncontrolled capturing conditions. In this paper, we describe the scope and context of identity document analysis and recognition problem and its challenges; analyze the existing works on implementing ID document recognition systems; and set a task to construct a unified framework for identity document recognition, which would be applicable for different types of image sources and capturing conditions, as well as scalable enough to support large number of identity document types. The aim of the presented framework is to serve as a basis for developing new methods and algorithms for ID document recognition, as well as for far more heavy challenges of identity document forensics, fully automated personal authentication and fraud prevention.
Keywords:
optical character recognition, document recognition, document analysis, identity documents, recognition system, mobile recognition, video stream recognition
Received: 25.08.2021 Accepted: 05.10.2021
Citation:
K. B. Bulatov, P. V. Bezmaternykh, D. P. Nikolaev, V. V. Arlazarov, “Towards a unified framework for identity documents analysis and recognition”, Computer Optics, 46:3 (2022), 436–454
Linking options:
https://www.mathnet.ru/eng/co1033 https://www.mathnet.ru/eng/co/v46/i3/p436
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