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

Xiao-jing Guo; Dan Li; Hai-gang Zhang; Jin-feng Yang

doi:10.1007/s11801-019-9033-1

Optoelectronics Letters ›› 2019, Vol. 15 ›› Issue (6) : 463 -467. DOI: 10.1007/s11801-019-9033-1

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

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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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Xiao-jing Guo, Dan Li, Hai-gang Zhang, Jin-feng Yang. Image restoration of finger-vein networks based on encoder-decoder model. Optoelectronics Letters, 2019, 15(6): 463-467 DOI:10.1007/s11801-019-9033-1

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