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CHARACTER RECOGNITION FOR THE MACHINE READER ZONE OF ELECTRONIC IDENTITY CARDS

Cited 6 time in Web of Science Cited 7 time in Scopus
Authors

Lee, Hyeogjin; Kwak, Nojun

Issue Date
2015
Publisher
IEEE
Citation
2015 IEEE INTERNATIONAL CONFERENCE ON IMAGE PROCESSING (ICIP), pp.387-391
Abstract
This paper proposes an overall procedure of recognizing the machine reader zone of a real world picture of a passport. To begin with, the proposed method finds the area of passport from the input image and its rotation angle is determined. With the rectified passport image by counter-rotating the area of passport, the machine reader zone is found and an inverse projective transform is performed to remove projective distortion. Then, each code is extracted and enhanced by using adaptive posterization. Template matching with improved similarity measure is applied to classify the codes. To classify the number 0 and the character O, a support vector machine is used. The experimental results show the correct character recognition rate of 99.77% and the correct recognition rate of 83.84%.
ISSN
1522-4880
URI
https://hdl.handle.net/10371/207321
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Related Researcher

  • Graduate School of Convergence Science & Technology
  • Department of Intelligence and Information
Research Area Feature Selection and Extraction, Object Detection, Object Recognition

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