Iris biometrie: Is the near-infrared spectrum always the best?

Previous work on iris recognition focused on either Visible Light (VL), Near-Infrared (NIR) imaging or the fusion between them. However, limited numbers of works have compared the iris biometric performance under both VL and NIR spectrum using images taken from the same subject. In this paper, we explore the differences in iris recognition performance across the VL and NIR spectrum. In addition, we investigate the possibility of cross-channel matching between the VL and NIR imaging. We carried out our experiments on the UTIRIS database which contains iris images taken under both the VL and NIR spectrum for the same subject. This paper is amongst the first studies which compares the performance of iris biometric under the NIR and VL spectrum and produces comparative experiments between these types of data. Experimental results indicate that the VL and NIR images provide complementary features for the iris pattern and their fusion improves the recognition performance. In addition, the experiments indicate that cross-channel matching between VL and NIR images is feasible.

[1]  Michele Nappi,et al.  Mobile Iris Challenge Evaluation (MICHE)-I, biometric iris dataset and protocols , 2015, Pattern Recognit. Lett..

[2]  Waleed Al-Nuaimy,et al.  Efficient Small Template Iris Recognition System Using Wavelet Transform , 2011 .

[3]  Pingzhi Fan,et al.  Performance evaluation of score level fusion in multimodal biometric systems , 2010, Pattern Recognit..

[4]  Luís A. Alexandre,et al.  The UBIRIS.v2: A Database of Visible Wavelength Iris Images Captured On-the-Move and At-a-Distance , 2010, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[5]  Babak Nadjar Araabi,et al.  Pigment Melanin: Pattern for Iris Recognition , 2009, IEEE Transactions on Instrumentation and Measurement.

[6]  Fernando Alonso-Fernandez,et al.  Comparison and fusion of multiple iris and periocular matchers using near-infrared and visible images , 2015, 3rd International Workshop on Biometrics and Forensics (IWBF 2015).

[7]  Hau T. Ngo,et al.  Preliminary evaluation of multispectral iris imagery , 2012 .

[8]  Paul Meredith,et al.  The physical and chemical properties of eumelanin. , 2006, Pigment cell research.

[9]  Libor Masek,et al.  MATLAB Source Code for a Biometric Identification System Based on Iris Patterns , 2003 .

[10]  Arun Ross,et al.  Exploring multispectral iris recognition beyond 900nm , 2009, 2009 IEEE 3rd International Conference on Biometrics: Theory, Applications, and Systems.

[11]  Kevin W. Bowyer The results of the NICE.II Iris biometrics competition , 2012, Pattern Recognit. Lett..

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