文章基本信息

标题：An End-to-End Method to Extract Information from Vietnamese ID Card Images
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作者：Khanh Nguyen-Trong
期刊名称：International Journal of Advanced Computer Science and Applications(IJACSA)
印刷版ISSN：2158-107X
电子版ISSN：2156-5570
出版年度：2022
卷号：13
期号：3
DOI：10.14569/IJACSA.2022.0130371
语种：English
出版社：Science and Information Society (SAI)
摘要：Information extraction from ID cards plays an important role in many daily activities, such as legal, banking, insurance, or health services. However, in many developing countries, such as Vietnam, it is mostly carried out manually, which is time-consuming, tedious, and may be prone to errors. Therefore, in this paper, we propose an end-to-end method to extract information from Vietnamese ID card images. The proposed method contains three steps with four neural networks and two image processing techniques, including U-Net, VGG16, Contour detection, and Hough transformation to pre-process input card images, CRAFT, and Rebia neural network for Optical Character Recognition, and Levenshtein distance and regular expression to post-process extracted information. In addition, a dataset, including 3.256 Vietnamese ID cards, 400k manual annotated text, and more than 500k synthetic text, was built for verifying our methods. The results of an empirical experiment conducted on our self-collected dataset indicate that the proposed method achieves a high accuracy of 94%, 99.5%, and 98.3% for card segmentation, classification, and text recognition.
关键词：Optical character recognition; U-Net network; VGG16 network; CRAFT network; rebia network