Face anti-spoofing system using motion and similarity feature elimination under spoof attacks
Joint Authors
Source
The International Arab Journal of Information Technology
Issue
Vol. 19, Issue 5 (30 Sep. 2022), pp.747-758, 12 p.
Publisher
Zarqa University Deanship of Scientific Research
Publication Date
2022-09-30
Country of Publication
Jordan
No. of Pages
12
Main Subjects
Information Technology and Computer Science
Abstract EN
From border control to mobile device unlocking applications, the practical utility of biometric system can be seriously compromised due face spoofing attacks.
So, face recognition systems require greater attention to combating face spoofing attacks.
As, face spoofing attacks can be easily propelled through 3D masks, video replays, and printed photos so we are presented face recognition system using motion and similarity features elimination under spoof attacks against the Replay Attack and Institute of Automation, Chinese Academy of Sciences (CASIA) databases.
In this paper a calculative analysis has been done by firstly segmenting the foreground and background regions from the input video using Gaussion Mixture Model and secondly by extracting features i.e., face, eye, and nose and applied 26 image quality assessment parameters on spoof face videos under different illumination lighting conditions.
The results attained using Replay Attack and CASIA databases are extremely competitive in discriminating from fake traits with paralleled viz-a-viz other approaches.
Different machine learning classifiers and their comparative analysis with existing approaches has been shown.
American Psychological Association (APA)
Bakshi, Aditya& Gupta, Sunanda. 2022. Face anti-spoofing system using motion and similarity feature elimination under spoof attacks. The International Arab Journal of Information Technology،Vol. 19, no. 5, pp.747-758.
https://search.emarefa.net/detail/BIM-1437077
Modern Language Association (MLA)
Bakshi, Aditya& Gupta, Sunanda. Face anti-spoofing system using motion and similarity feature elimination under spoof attacks. The International Arab Journal of Information Technology Vol. 19, no. 5 (Sep. 2022), pp.747-758.
https://search.emarefa.net/detail/BIM-1437077
American Medical Association (AMA)
Bakshi, Aditya& Gupta, Sunanda. Face anti-spoofing system using motion and similarity feature elimination under spoof attacks. The International Arab Journal of Information Technology. 2022. Vol. 19, no. 5, pp.747-758.
https://search.emarefa.net/detail/BIM-1437077
Data Type
Journal Articles
Language
English
Record ID
BIM-1437077