On the Efficacy of Correcting for Refractive Effects in Iris Recognition

In this study, we aim to determine if iris recognition accuracy might be improved by correcting for the refractive effects of the human eye when the optical axes of the eye and camera are misaligned. We undertake this investigation using an anatomically-approximated, three-dimensional model of the human eye and ray-tracing. We generate synthetic iris imagery from different viewing angles using first a simple pattern of concentric rings on the iris for analysis, and then synthetic texture maps on the iris for experimentation. We estimate the distortion from the concentric-ring iris images and use the results to guide the sampling of textured iris images that are distorted by refraction. Using the well-known Gabor filter phase quantization approach, our model-based results indicate that the Hamming distances between iris signatures from different viewing angles can be significantly reduced by accounting for refraction. Over our experimental conditions comprising viewing angles from 0 to 60 degrees, we observe a median reduction in Hamming distance of 27.4% and a maximum reduction of 70.0% when we compensate for refraction. Maximum improvements are observed at viewing angles o/20deg-25deg.

[1]  Scott A Read,et al.  The topography of the central and peripheral cornea. , 2006, Investigative ophthalmology & visual science.

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

[3]  Erik Reinhard,et al.  An Ocularist's Approach to Human Iris Synthesis , 2003, IEEE Computer Graphics and Applications.

[4]  Yves le Grand,et al.  Form and Space Vision , 1967 .

[5]  M. Dubbelman,et al.  The shape of the anterior and posterior surface of the aging human cornea , 2006, Vision Research.

[6]  Fabrice Manns,et al.  Radius of curvature and asphericity of the anterior and posterior surface of human cadaver crystalline lenses. , 2004, Experimental eye research.

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

[8]  Arun Ross,et al.  Generating Synthetic Irises by Feature Agglomeration , 2006, 2006 International Conference on Image Processing.

[9]  T. Hoang‐Xuan,et al.  [A review of mathematical descriptors of corneal asphericity]. , 2002, Journal francais d'ophtalmologie.

[10]  J. Daugman.  5 RECOGNIZING PERSONS BY THEIR IRIS PATTERNS , 2005 .

[11]  J. Marshall,et al.  Shape and radius of posterior corneal surface. , 1993, Refractive & corneal surgery.