Face anti-spoofing with Image Quality Assessment

被引：0

作者：

Fourati, Emna ^{[1
]}

Elloumi, Wael ^{[1
]}

Chetouani, Aladine ^{[2
]}

机构：

[1] Worldline Co, 19 Rue Vallee Maillard, Blois, France

[2] Univ Orleans, Lab Prisme, 12 Rue Blois, Orleans, France

来源：

2017 2ND INTERNATIONAL CONFERENCE ON BIO-ENGINEERING FOR SMART TECHNOLOGIES (BIOSMART) | 2017年

关键词：

Image quality assessment; anti-spoofing; biometric facial authentication;

D O I：

暂无

中图分类号：

R318 [生物医学工程];

学科分类号：

0831 ;

摘要：

Face recognition-based authentication techniques can be easily spoofed using various types of attack. Consistent counter-measures need to meet certain requirements, mainly regarding reliable robustness and low complexity. In this paper, we aim to find the best compromise between these two criteria, as we propose an anti-spoofing solution based on Image Quality Assessment (IQA) to distinguish between genuine and fake face-appearances. Our solution was tested on a publicly available database, and proved to outperform state-of-the-art approaches.

引用

页数：4

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