On Improving Temporal Consistency for Online Face Liveness Detection System

Author(s):  
Xiang Xu ◽  
Yuanjun Xiong ◽  
Wei Xia
2021 ◽  
Vol 1871 (1) ◽  
pp. 012046
Author(s):  
Ling Yue ◽  
Chenhong Cao ◽  
Yufeng Li ◽  
Jiangtao Li ◽  
Qi Liu

2016 ◽  
Vol 10 (1) ◽  
pp. 361-374
Author(s):  
Xu Guang Zhu ◽  
Yin Pan Long ◽  
Lei Bang Jun ◽  
Zou Yao Bin ◽  
Yang Ji Quan

2020 ◽  
Vol 34 (05) ◽  
pp. 2030001 ◽  
Author(s):  
Rohit Agarwal ◽  
A. S. Jalal ◽  
K. V. Arya

Fingerprint recognition systems are susceptible to artificial spoof fingerprint attacks, like molds manufactured from polymer, gelatin or Play-Doh. Presentation attack is an open issue for fingerprint recognition systems. In a presentation attack, synthetic fingerprint which is reproduced from a real user is submitted for authentication. Different sensors are used to capture the live and fake fingerprint images. A liveness detection system has been designed to defeat different classes of spoof attacks by differentiating the features of live and fake fingerprint images. In the past few years, many hardware- and software-based approaches are suggested by researchers. However, the issues still remain challenging in terms of robustness, effectiveness and efficiency. In this paper, we explore all kinds of software-based solution to differentiate between real and fake fingerprints and present a comprehensive survey of efforts in the past to address this problem.


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