Face spoofing detection from single images using active shape models with Stasm and LBP

Besides the recognition task, todays biometric systems need to cope with additional problem: spoofing attacks, like presenting a photo of a person(client) to camera. We study in this paper an anti-spoofing solution for distinguishing between ‘live’ and ‘fake ‘ faces. In our approach we focused in face detection using Viola-Jones algorithm and Active Shape Models with Stasm for locating landmarks. Then, we apply Local Binary Patterns (LBP) operator to extract the features in each region of the image. Finally, we use a nonlinear Support Vector Machine (SVM) classifier with kernel function for determining whether the input image corresponds to a live face or not. Our experimental analysis on a publicly available database NUAA, showed excellent results compared to existing methods.

[1]  Sébastien Marcel,et al.  Can face anti-spoofing countermeasures work in a real world scenario? , 2013, 2013 International Conference on Biometrics (ICB).

[2]  Sébastien Marcel,et al.  On the effectiveness of local binary patterns in face anti-spoofing , 2012, 2012 BIOSIG - Proceedings of the International Conference of Biometrics Special Interest Group (BIOSIG).

[3]  Tieniu Tan,et al.  Live face detection based on the analysis of Fourier spectra , 2004, SPIE Defense + Commercial Sensing.

[4]  Naser Damer,et al.  2D face liveness detection: An overview , 2012, 2012 BIOSIG - Proceedings of the International Conference of Biometrics Special Interest Group (BIOSIG).

[5]  Sébastien Marcel,et al.  LBP - TOP Based Countermeasure against Face Spoofing Attacks , 2012, ACCV Workshops.

[6]  Zhaohui Wu,et al.  Liveness Detection for Face Recognition , 2008 .

[7]  Rui Chen,et al.  Liveness detection for iris recognition using multispectral images , 2012, Pattern Recognit. Lett..

[8]  Paul A. Viola,et al.  Rapid object detection using a boosted cascade of simple features , 2001, Proceedings of the 2001 IEEE Computer Society Conference on Computer Vision and Pattern Recognition. CVPR 2001.

[9]  Fred Nicolls,et al.  Locating Facial Features with an Extended Active Shape Model , 2008, ECCV.

[10]  Lin Sun,et al.  Eyeblink-based Anti-Spoofing in Face Recognition from a Generic Webcamera , 2007, 2007 IEEE 11th International Conference on Computer Vision.

[11]  Andreas Christmann,et al.  Support vector machines , 2008, Data Mining and Knowledge Discovery Handbook.

[12]  Matti Pietikäinen,et al.  Multiresolution Gray-Scale and Rotation Invariant Texture Classification with Local Binary Patterns , 2002, IEEE Trans. Pattern Anal. Mach. Intell..

[13]  Anderson Rocha,et al.  Face spoofing detection through partial least squares and low-level descriptors , 2011, 2011 International Joint Conference on Biometrics (IJCB).

[14]  Matti Pietikäinen,et al.  Computer Vision Using Local Binary Patterns , 2011, Computational Imaging and Vision.

[15]  Fabio Roli,et al.  Fusion of multiple clues for photo-attack detection in face recognition systems , 2011, 2011 International Joint Conference on Biometrics (IJCB).

[16]  Hong Li,et al.  A liveness detection method for face recognition based on optical flow field , 2009, 2009 International Conference on Image Analysis and Signal Processing.

[17]  Matti Pietikäinen,et al.  Face spoofing detection from single images using texture and local shape analysis , 2012, IET Biom..

[18]  Anderson Rocha,et al.  Face liveness detection under bad illumination conditions , 2011, 2011 18th IEEE International Conference on Image Processing.

[19]  Matti Pietikäinen,et al.  Face spoofing detection from single images using micro-texture analysis , 2011, 2011 International Joint Conference on Biometrics (IJCB).

[20]  Yi Li,et al.  Face Liveness Detection from a Single Image with Sparse Low Rank Bilinear Discriminative Model , 2010, ECCV.

[21]  Josef Bigün,et al.  Evaluating liveness by face images and the structure tensor , 2005, Fourth IEEE Workshop on Automatic Identification Advanced Technologies (AutoID'05).

[22]  Sébastien Marcel,et al.  Counter-measures to photo attacks in face recognition: A public database and a baseline , 2011, 2011 International Joint Conference on Biometrics (IJCB).

[23]  Josef Bigün,et al.  Verifying liveness by multiple experts in face biometrics , 2008, 2008 IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops.

[24]  Fernando L. Podio.  Biometrics - Technologies for Highly Secure Personal Authentication , 2001 .