Reduction of False Rejection in an Authentication System by Fingerprint with Deep Neural Networks

• 作者: Claude Tangha Olaf Kouamo Stéphane Kouamo
• 来源期刊: 软件工程与应用(英文)
• 学科: 工学
• 关键词: AUTHENTICATION FINGERPRINT False REJECTION NEURAL Networks Pattern RECOGNITION DEEP Learning
• 年，卷（期）: 2020,（1）
• 页码范围: 1-13
• 页数: 13页
• 分类号: TN9

摘要

Faultless authentication of individuals by fingerprints results in high false rejections rate for rigorously built systems. Indeed, the authors prefer that the system erroneously reject a pattern when it does not meet a number of predetermined correspondence criteria. In this work, after discussing existing techniques, we propose a new algorithm to reduce the false rejection rate during the authentication-using fingerprint. This algorithm extracts the minutiae of the fingerprint with their relative orientations and classifies them according to the different classes already established;then, make the correspondence between two templates by simple probabilities calculations from a deep neural network. The merging of these operations provides very promising results both on the NIST4 international data reference and on the SOCFing database.