Approach for Document Detection by Contours and Contrasts
Abstract
This paper considers arbitrary document detection performed on a mobile device. The classical contour-based approach often fails in cases featuring occlusion, complex background, or blur. The region-based approach, which relies on the contrast between object and background, does not have application limitations, however, its known implementations are highly resource-consuming. We propose a modification of the contour-based method, in which the competing contour location hypotheses are ranked according to the contrast between the areas inside and outside the border. In the experiments, such modification allows for the decrease of alternatives ordering errors by 40% and the decrease of the overall detection errors by 10%. The proposed method provides unmatched state-of-the-art performance on the open MIDV-500 dataset, and it demonstrates results comparable with state-of-the-art performance on the SmartDoc dataset.
Cite
@article{arxiv.2008.02615,
title = {Approach for Document Detection by Contours and Contrasts},
author = {Daniil V. Tropin and Sergey A. Ilyuhin and Dmitry P. Nikolaev and Vladimir V. Arlazarov},
journal= {arXiv preprint arXiv:2008.02615},
year = {2021}
}
Comments
This paper has been accepted to the ICPR 2020 conference in Milan which will be held on the 10-15 January 2021. Therefore this work has not yet been presented