Title: Face liveness detection through face structure analysis

Authors: Avinash Kumar Singh; Piyush Joshi; G.C. Nandi

Addresses: Robotics and Artificial Intelligence Lab, Indian Institute of Information Technology, Allahabad, Uttar Pradesh – 211012, India ' Robotics and Artificial Intelligence Lab, Indian Institute of Information Technology, Allahabad, Uttar Pradesh – 211012, India ' Robotics and Artificial Intelligence Lab, Indian Institute of Information Technology, Allahabad, Uttar Pradesh – 211012, India

Abstract: Liveness detection is a way to detect whether the person is live or not during submission of his/her biometric trait. It is mandatory in order to prevent face spoofing attacks. Therefore, in this paper, we proposed a robust face structure analysis mechanism to detect the liveness by exploiting face shape information. 3D structure/shape of the face is measured on the basis of disparity map between left and right image taken by stereoscopic vision. A gradient-based eight neighbour feature extraction technique has been proposed to extract unique features from these disparity images. It produces minimal computational cost by taking subset of the overall image. We have applied linear discriminant analysis (LDA), C-means algorithms on these features while principal component analysis (PCA) is applied on raw disparity images. We have achieved a recognition rate of 91.6%, 97.5% and 98.3% using PCA, LDA and C-means respectively, which strengthened the confidence of our proposed feature extraction technique.

Keywords: face spoofing attacks; face liveness detection; face disparity map; feature extraction; principal component analysis; PCA; linear discriminant analysis; LDA; C-means; false rejection rate; FRR; facial structure analysis; biometrics; face shape; disparity images.

DOI: 10.1504/IJAPR.2014.068327

International Journal of Applied Pattern Recognition, 2014 Vol.1 No.4, pp.338 - 360

Received: 10 Apr 2013
Accepted: 16 Sep 2013
Published online: 10 Apr 2015 *

Full-text access for editors Full-text access for subscribers Purchase this article Comment on this article