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DOI: 10.14569/IJACSA.2019.0101057
PDF

A Method for Segmentation of Vietnamese Identification Card Text Fields

Author 1: Tan Nguyen Thi Thanh
Author 2: Khanh Nguyen Trong

International Journal of Advanced Computer Science and Applications(IJACSA), Volume 10 Issue 10, 2019.

  • Abstract and Keywords
  • How to Cite this Article
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Abstract: The development of deep learning in computer vision has motivated researches in related fields, including Optical Character Recognition (OCR). Many proposed models and pre-trained models in the literature demonstrate their efficient in optical text recognition. In this context, image processing techniques has an essential role in improving the accuracy of recognition task. Because, depending on the practical application, image text often suffering several degradation from blur, uneven illumination, complex background, perspective distortion and so on. In this paper, we propose a method for pre-processing, text area extraction and segmentation of Vietnamese Identification Card, in order to improve the accuracy of Region of Interest detection. The proposed method was evaluated with a large data set with different practical qualities. Experiment results demonstrate the efficiency of our method.

Keywords: Optical Character Recognition (OCR); text identifi-cation; identification card detection and recognition

Tan Nguyen Thi Thanh and Khanh Nguyen Trong, “A Method for Segmentation of Vietnamese Identification Card Text Fields” International Journal of Advanced Computer Science and Applications(IJACSA), 10(10), 2019. http://dx.doi.org/10.14569/IJACSA.2019.0101057

@article{Thanh2019,
title = {A Method for Segmentation of Vietnamese Identification Card Text Fields},
journal = {International Journal of Advanced Computer Science and Applications},
doi = {10.14569/IJACSA.2019.0101057},
url = {http://dx.doi.org/10.14569/IJACSA.2019.0101057},
year = {2019},
publisher = {The Science and Information Organization},
volume = {10},
number = {10},
author = {Tan Nguyen Thi Thanh and Khanh Nguyen Trong}
}



Copyright Statement: This is an open access article licensed under a Creative Commons Attribution 4.0 International License, which permits unrestricted use, distribution, and reproduction in any medium, even commercially as long as the original work is properly cited.

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