Anti-spoofing detection based on eyeblink liveness testing for iris recognition

Isaack Adidas Kamanga * and Johanson Miserigodiasi Lyimo

Department of Electronic and telecommunications engineering, Dar es Salaam Institute of Technology (DIT), Dar es Salaam, Tanzania.
 
Research Article
International Journal of Science and Research Archive, 2022, 07(01), 053–067.
Article DOI: 10.30574/ijsra.2022.7.1.0186
Publication history: 
Received on 30 June 2022; revised on 08 September 2022; accepted on 10 September 2022
 
Abstract: 
Iris pattern is the most stable biometric trait for personal identification. It is the only traits that can’t be used after a person death.  Despite its stability and difficulty to spoof, it has found that presenting a high quality image of an iris one can spoof and gain an access. Furthermore, the use of video frames of an authorized personnel and the use of 3D models can cheat the system. This study aimed at presenting a solution to this problem by testing the liveness of an eye being scanned by an access control device. The algorithm works by additional process of detecting an eyeblink and background subtraction and correlation to assume liveness. For one to gain access, first an iris is scanned and identified, secondly if this iris is in the database before providing an access, an eyeblink is also sensed. If eyeblink is sensed an access is granted otherwise access is denied. An algorithm has been developed in MATLAB adopting an adaptive Canny method for edge detection. The proposed algorithm validates the user being scanned by two stages which are; Eyeblink detection, background subtraction and correlation.  Testing on standard datasets of ZJU Eyeblink, ACASIA v3 and the TalkingFace databases showed show 96.47% accuracy.
 
Keywords: 
Biometric ID; Iris recognition; Hamming distance; Eyeblink; Iris Code
 
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