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3 April 2024 Multilanguage ID document images synthesis for testing recognition pipelines
Yulia S. Chernyshova, Konstantin K. Suloev, Vladimir V. Arlazarov
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Proceedings Volume 13072, Sixteenth International Conference on Machine Vision (ICMV 2023); 130720E (2024) https://doi.org/10.1117/12.3023179
Event: Sixteenth International Conference on Machine Vision (ICMV 2023), 2023, Yerevan, Armenia
Abstract
Datasets are de facto the only way to test the recognition pipelines and to compare them with each other. To avoid the manual gathering of documents and, moreover, to avoid problems with the law in the case of ID documents researchers create synthetic datasets or datasets of fake documents, but this process is also time-consuming. In this paper, we present a simple method to use when you need to test a recognition pipeline or some part of it. The method employs only the information that the developers of such pipelines use in their work and allows them to create natural-looking images. The quantitative experiments show that the recognition accuracy of the synthesized images corresponds with the recognition accuracy of the MIDV-2020 dataset. The qualitative comparison also demonstrates that such images can be helpful in recognition systems’ development.
(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.
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Yulia S. Chernyshova, Konstantin K. Suloev, and Vladimir V. Arlazarov "Multilanguage ID document images synthesis for testing recognition pipelines", Proc. SPIE 13072, Sixteenth International Conference on Machine Vision (ICMV 2023), 130720E (3 April 2024); https://doi.org/10.1117/12.3023179
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KEYWORDS
Neural networks
Optical character recognition
Video
Scientific research
Statistical modeling
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