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Optoelectronics Letters

, Volume 15, Issue 6, pp 463–467 | Cite as

Image restoration of finger-vein networks based on encoder-decoder model

  • Xiao-jing Guo (郭晓静)
  • Dan Li (李丹)Email author
  • Hai-gang Zhang (张海刚)
  • Jin-feng Yang (杨金锋)
Article
  • 6 Downloads

Abstract

Finger-vein recognition is widely applied on access control system due to the high user acceptance and convince. Improving the integrity of finger-vein is helpful for increasing the finger-vein recognition accuracy. During the process of finger-vein imaging, foreign objects may be attached on fingers, which directly affects the integrity of finger-vein images. In order to effectively extract finger-vein networks, the integrity of venous networks is still not ideal after preprocessing of finger vein images. In this paper, we propose a novel deep learning based image restoration method to improve the integrity of finger-vein networks. First, a region detecting method based on adaptive threshold is presented to locate the incomplete region. Next, an encoder-decoder model is used to restore the venous networks of the finger-vein images. Then we analyze the restoration results using several different methods. Experimental results show that the proposed method is effective to restore the venous networks of the finger-vein images.

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Copyright information

© Tianjin University of Technology and Springer-Verlag GmbH Germany, part of Springer Nature 2019

Authors and Affiliations

  • Xiao-jing Guo (郭晓静)
    • 1
  • Dan Li (李丹)
    • 1
    • 2
    Email author
  • Hai-gang Zhang (张海刚)
    • 1
    • 2
  • Jin-feng Yang (杨金锋)
    • 1
    • 2
  1. 1.College of Electronic Information and AutomationCivil Aviation University of ChinaTianjinChina
  2. 2.Tianjin Key Lab for Advanced Signal ProcessingCivil Aviation University of ChinaTianjinChina

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