Eye detection by complex filtering for periocular recognition

We present a novel system to localize the eye position based on symmetry filters. By using a 2D separable filter tuned to detect circular symmetries, detection is done with a few ID convolutions. The detected eye center is used as input to our periocular algorithm based on retinotopic sampling grids and Gabor analysis of the local power spectrum. This setup is evaluated with two databases of iris data, one acquired with a close-up NIR camera, and another in visible light with a web-cam. The periocular system shows high resilience to inaccuracies in the position of the detected eye center. The density of the sampling grid can also be reduced without sacrificing too much accuracy, allowing additional computational savings. We also evaluate an iris texture matcher based on ID Log-Gabor wavelets. Despite the poorer performance of the iris matcher with the webcam database, its fusion with the periocular system results in improved performance.

[1]  Johan Wiklund,et al.  Multidimensional Orientation Estimation with Applications to Texture Analysis and Optical Flow , 1991, IEEE Trans. Pattern Anal. Mach. Intell..

[2]  Damon L. Woodard,et al.  Performance evaluation of local appearance based periocular recognition , 2010, 2010 Fourth IEEE International Conference on Biometrics: Theory, Applications and Systems (BTAS).

[3]  Fabrizio Smeraldi,et al.  Saccadic search with Gabor features applied to eye detection and real-time head tracking , 2000, Image Vis. Comput..

[4]  Arun Ross,et al.  On the Fusion of Periocular and Iris Biometrics in Non-ideal Imagery , 2010, 2010 20th International Conference on Pattern Recognition.

[5]  Abhijit Mahalanobis,et al.  Biometric verification with correlation filters. , 2004, Applied optics.

[6]  John Daugman,et al.  How iris recognition works , 2002, IEEE Transactions on Circuits and Systems for Video Technology.

[7]  Arun Ross,et al.  Periocular Biometrics in the Visible Spectrum , 2011, IEEE Transactions on Information Forensics and Security.

[8]  Hugo Proença,et al.  Periocular biometrics: An emerging technology for unconstrained scenarios , 2013, 2013 IEEE Symposium on Computational Intelligence in Biometrics and Identity Management (CIBIM).

[9]  Libor Masek,et al.  Recognition of Human Iris Patterns for Biometric Identification , 2003 .

[10]  Fernando Alonso-Fernandez,et al.  Periocular Recognition Using Retinotopic Sampling and Gabor Decomposition , 2012, ECCV Workshops.

[11]  Julian Fiérrez,et al.  Biosec baseline corpus: A multimodal biometric database , 2007, Pattern Recognit..

[12]  Arun Ross,et al.  Score normalization in multimodal biometric systems , 2005, Pattern Recognit..

[13]  Andreas Uhl,et al.  Combining Face with Face-Part Detectors under Gaussian Assumption , 2012, ICIAR.

[14]  Josef Bigün,et al.  Recognition by symmetry derivatives and the generalized structure tensor , 2004, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[15]  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.

[16]  J. Bigun.  Pattern recognition in images by symmetries and coordinate transformations , 1997 .

[17]  J. Bigun,et al.  Assuring liveness in biometric identity authentication by real-time face tracking , 2004, Proceedings of the 2004 IEEE International Conference on Computational Intelligence for Homeland Security and Personal Safety, 2004. CIHSPS 2004..

[18]  Josef Bigün,et al.  Localization of corresponding points in fingerprints by complex filtering , 2003, Pattern Recognit. Lett..

[19]  Fernando Alonso-Fernandez,et al.  Iris boundaries segmentation using the generalized structure tensor. A study on the effects of image degradation , 2012, 2012 IEEE Fifth International Conference on Biometrics: Theory, Applications and Systems (BTAS).

[20]  Damon L. Woodard,et al.  Human and Machine Performance on Periocular Biometrics Under Near-Infrared Light and Visible Light , 2012, IEEE Transactions on Information Forensics and Security.

[21]  Julian Fierrez,et al.  Off-line Signature Verification Using Contour Features , 2008, ICFHR 2008.

[22]  Fabrizio Smeraldi,et al.  Retinal vision applied to facial features detection and face authentication , 2002, Pattern Recognit. Lett..

[23]  Stefan Fischer,et al.  Expert Conciliation for Multi Modal Person Authentication Systems by Bayesian Statistics , 1997, AVBPA.

[24]  Jinyu Zuo,et al.  An Automatic Algorithm for Evaluating the Precision of Iris Segmentation , 2008, 2008 IEEE Second International Conference on Biometrics: Theory, Applications and Systems.

[25]  Ana F. Sequeira,et al.  MobBIO: A multimodal database captured with a portable handheld device , 2014, 2014 International Conference on Computer Vision Theory and Applications (VISAPP).

[26]  Mark J. Burge,et al.  Handbook of Iris Recognition , 2013, Advances in Computer Vision and Pattern Recognition.

[27]  Julian Fiérrez,et al.  Fingerprint Image-Quality Estimation and its Application to Multialgorithm Verification , 2008, IEEE Transactions on Information Forensics and Security.