Impact of severe signal degradation on ear recognition performance

We investigate ear recognition systems for severe signal degradation of ear images in order to assess the impact on biometric performance of diverse well-established feature extraction algorithms. Various intensities of signal degradation, i.e. out-of-focus blur and thermal noise, are simulated in order to construct realistic acquisition scenarios. Experimental evaluations, which are carried out on a comprehensive database comprising more than 2,000 ear images, point out the effects of severe signal degradation on ear recognition performance using appearance features.

[1]  Ping Yan,et al.  Biometric Recognition Using 3D Ear Shape , 2007, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[2]  Alphonse Bertillon,et al.  La photographie judiciaire, avec un appendice sur la classification et l'identification anthropométriques , 1890 .

[3]  Timo Ahonen,et al.  Recognition of blurred faces using Local Phase Quantization , 2008, 2008 19th International Conference on Pattern Recognition.

[4]  A J Hoogstrate,et al.  Ear identification based on surveillance camera images. , 2001, Science & justice : journal of the Forensic Science Society.

[5]  Ville Ojansivu,et al.  Blur Insensitive Texture Classification Using Local Phase Quantization , 2008, ICISP.

[6]  Christoph Busch,et al.  Ear biometrics: a survey of detection, feature extraction and recognition methods , 2012, IET Biom..

[7]  Bill Triggs,et al.  Histograms of oriented gradients for human detection , 2005, 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05).

[8]  Christoph Busch,et al.  Effects of severe signal degradation on ear detection , 2014, 2nd International Workshop on Biometrics and Forensics.

[9]  Davide G. Tommasi,et al.  Age- and sex-related changes in the normal human ear. , 2009, Forensic science international.

[10]  Vitomir Struc,et al.  The Complete Gabor-Fisher Classifier for Robust Face Recognition , 2010, EURASIP J. Adv. Signal Process..

[11]  Patrick J. Flynn,et al.  Rotated Profile Signatures for robust 3D feature detection , 2008, 2008 8th IEEE International Conference on Automatic Face & Gesture Recognition.

[12]  Ping Yan,et al.  An Automatic 3D Ear Recognition System , 2006, Third International Symposium on 3D Data Processing, Visualization, and Transmission (3DPVT'06).

[13]  Zhang Li,et al.  Contrast Limited Adaptive Histogram Equalization , 2010 .

[14]  Karel J. Zuiderveld,et al.  Contrast Limited Adaptive Histogram Equalization , 1994, Graphics Gems.

[15]  Mary Ann F. Harrison,et al.  Ear recognition: a complete system , 2013, Defense, Security, and Sensing.

[16]  Neeti A. Ogale,et al.  A survey of techniques for human detection from video , 2006 .