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http://dx.doi.org/10.5762/KAIS.2020.21.8.530

An Algorithm of Fingerprint Image Restoration Based on an Artificial Neural Network  

Jang, Seok-Woo (Department of Software, Anyang University)
Lee, Samuel (School of Software, Soongsil University)
Kim, Gye-Young (School of Software, Soongsil University)
Publication Information
Journal of the Korea Academia-Industrial cooperation Society / v.21, no.8, 2020 , pp. 530-536 More about this Journal
Abstract
The use of minutiae by fingerprint readers is robust against presentation attacks, but one weakness is that the mismatch rate is high. Therefore, minutiae tend to be used with skeleton images. There have been many studies on security vulnerabilities in the characteristics of minutiae, but vulnerability studies on the skeleton are weak, so this study attempts to analyze the vulnerability of presentation attacks against the skeleton. To this end, we propose a method based on the skeleton to recover the original fingerprint using a learning algorithm. The proposed method includes a new learning model, Pix2Pix, which adds a latent vector to the existing Pix2Pix model, thereby generating a natural fingerprint. In the experimental results, the original fingerprint is restored using the proposed machine learning, and then, the restored fingerprint is the input for the fingerprint reader in order to achieve a good recognition rate. Thus, this study verifies that fingerprint readers using the skeleton are vulnerable to presentation attacks. The approach presented in this paper is expected to be useful in a variety of applications concerning fingerprint restoration, video security, and biometrics.
Keywords
Deep Learning; Fingerprint Image; Feature Extraction; Recognition Rate; Binarization;
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