Abstract

Undersampling in the detector array degrades the performance of iris-recognition imaging systems. We find that an undersampling of 8×8 reduces the iris-recognition performance by nearly a factor of 4 (on CASIA iris database), as measured by the false rejection ratio (FRR) metric. We employ optical point spread function (PSF) engineering via a Zernike phase mask in conjunction with multiple sub pixel shifted image measurements (frames) to mitigate the effect of undersampling. A task-specific optimization framework is used to engineer the optical PSF and optimize the postprocessing parameters to minimize the FRR. The optimized Zernike phase enhanced lens (ZPEL) imager design with one frame yields an improvement of nearly 33% relative to a thin observation module by bounded optics (TOMBO) imager with one frame. With four frames the optimized ZPEL imager achieves a FRR equal to that of the conventional imager without undersampling. Further, the ZPEL imager design using 16 frames yields a FRR that is actually 15% lower than that obtained with the conventional imager without undersampling.

© 2010 Optical Society of America

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References

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  1. J. G. Daugman, “High confidence visual recognition of persons by a test of statistical independence,” IEEE Trans. Pattern Anal. Mach. Intell. 15, 1148-1161 (1993).
    [CrossRef]
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    [CrossRef]
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    [CrossRef]
  4. R. Barnard, V. P. Pauca, T. C. Torgersen, R. J. Plemmons, S. Prasad, J. van der Gracht, J. Nagy, J. Chung, G. Behrmann, S. Mathews, and M. Mirotznik, “High-resolution iris image reconstruction from low-resolution imagery,” Proc. SPIE 6313, 63130D (2006).
    [CrossRef]
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    [CrossRef]
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2008 (3)

2007 (1)

2006 (1)

R. Barnard, V. P. Pauca, T. C. Torgersen, R. J. Plemmons, S. Prasad, J. van der Gracht, J. Nagy, J. Chung, G. Behrmann, S. Mathews, and M. Mirotznik, “High-resolution iris image reconstruction from low-resolution imagery,” Proc. SPIE 6313, 63130D (2006).
[CrossRef]

2005 (2)

R. Narayanswamy, P. E. X. Silveira, H. Setty, V. P. Pauca, and J. van der Gracht, “Extended depth-of-field iris recognition system for a workstation environment,” Proc. SPIE 5779, 41-50 (2005).
[CrossRef]

R. Narayanswamy, G. E. Johnson, P. E. X. Silveira, and H. B. Wach, “Extending the imaging volume for biometric iris recognition,” Appl. Opt. 44, 701-712 (2005).
[CrossRef] [PubMed]

2004 (2)

2003 (2)

J. G. Daugman, “The importance of being random: statistical principles of iris recognition,” Pattern Recogn. 36, 279-291(2003).
[CrossRef]

E. Y. Lam, “Noise in superresolution reconstruction,” Opt. Lett. 28, 2234-2236 (2003).
[CrossRef] [PubMed]

2001 (1)

1999 (1)

W. Wenzel and K. Hamacher, “A stochastic tunneling approach for global minimization,” Phys. Rev. Lett. 82, 3003-3007(1999).
[CrossRef]

1993 (1)

J. G. Daugman, “High confidence visual recognition of persons by a test of statistical independence,” IEEE Trans. Pattern Anal. Mach. Intell. 15, 1148-1161 (1993).
[CrossRef]

1987 (1)

D. J. Field, “Relations between the statistics of natural images and the response properties of cortical cells,” J. Opt. Soc. Am. 4, 2379-2394 (1987).
[CrossRef]

1984 (1)

1977 (1)

A. Papoulis, “Generalized sampling expansion,” IEEE Trans. Circuits Syst. 24, 652-654 (1977).
[CrossRef]

1974 (1)

Y. Itakura, S. Tsutsumi, and T. Takagi, “Statistical properties of the background noise for the atmospheric windows in the intermediate infrared region,” Infrared Phys. 14, 17-29(1974).
[CrossRef]

Andrews, H. C.

H. C. Andrews and B. R. Hunt, Digital Image Restoration (Prentice-Hall, 1977).

Barnard, R.

R. Barnard, V. P. Pauca, T. C. Torgersen, R. J. Plemmons, S. Prasad, J. van der Gracht, J. Nagy, J. Chung, G. Behrmann, S. Mathews, and M. Mirotznik, “High-resolution iris image reconstruction from low-resolution imagery,” Proc. SPIE 6313, 63130D (2006).
[CrossRef]

Barrett, H. H.

H. H. Barrett and K. J. Myers, Foundations of Image Science (Wiley-Interscience, 2004), Chaps. 7 and 15.

Barwick, D. S.

Behrmann, G.

R. Barnard, V. P. Pauca, T. C. Torgersen, R. J. Plemmons, S. Prasad, J. van der Gracht, J. Nagy, J. Chung, G. Behrmann, S. Mathews, and M. Mirotznik, “High-resolution iris image reconstruction from low-resolution imagery,” Proc. SPIE 6313, 63130D (2006).
[CrossRef]

Born, M.

M. Born and E. Wolf, Principles of Optics (Pergamon, 1989), Chap. 9.

Chen, D.

V. P. Pauca, D. Chen, J. van der Gracht, R. J. Plemmons, S. Prasad, and T. C. Torgersen, “Pupil phase encoding for multi-aperture imaging,” Proc. SPIE 7074, 70740D (2008).
[CrossRef]

Chung, J.

R. Barnard, V. P. Pauca, T. C. Torgersen, R. J. Plemmons, S. Prasad, J. van der Gracht, J. Nagy, J. Chung, G. Behrmann, S. Mathews, and M. Mirotznik, “High-resolution iris image reconstruction from low-resolution imagery,” Proc. SPIE 6313, 63130D (2006).
[CrossRef]

Daugman, J. G.

J. G. Daugman, “How iris recognition works,” IEEE Trans. Circ. Syst. Video Tech. 14, 21-30 (2004).
[CrossRef]

J. G. Daugman, “The importance of being random: statistical principles of iris recognition,” Pattern Recogn. 36, 279-291(2003).
[CrossRef]

J. G. Daugman, “High confidence visual recognition of persons by a test of statistical independence,” IEEE Trans. Pattern Anal. Mach. Intell. 15, 1148-1161 (1993).
[CrossRef]

Erbetta, J.

S. Sanderson and J. Erbetta, “Authentication for secure environments based on iris scanning technology,” in IEE Colloquium on Visual Biometrics (IEEE, 2000), pp. 8/1-8/7.

Fales, C. L.

Field, D. J.

D. J. Field, “Relations between the statistics of natural images and the response properties of cortical cells,” J. Opt. Soc. Am. 4, 2379-2394 (1987).
[CrossRef]

Goodman, J. W.

J. W. Goodman, Introduction to Fourier Optics (McGraw-Hill, 1996), Chap. 7.

Hamacher, K.

W. Wenzel and K. Hamacher, “A stochastic tunneling approach for global minimization,” Phys. Rev. Lett. 82, 3003-3007(1999).
[CrossRef]

Huck, F. O.

Hunt, B. R.

H. C. Andrews and B. R. Hunt, Digital Image Restoration (Prentice-Hall, 1977).

Ichioka, Y.

Ishida, K.

Itakura, Y.

Y. Itakura, S. Tsutsumi, and T. Takagi, “Statistical properties of the background noise for the atmospheric windows in the intermediate infrared region,” Infrared Phys. 14, 17-29(1974).
[CrossRef]

Johnson, G. E.

Kay, S.

S. Kay, Fundamentals of Statistical Signal Processing: Detection Theory (Prentice-Hall, 1993).

Kitamura, Y.

Kondou, N.

Kumagai, T.

Lam, E. Y.

Masaki, Y.

Masek, L.

L. Masek, “Recognition of human iris patterns for biometric identification,” Technical report (University of Western Australia, 2003).

Mathews, S.

R. Barnard, V. P. Pauca, T. C. Torgersen, R. J. Plemmons, S. Prasad, J. van der Gracht, J. Nagy, J. Chung, G. Behrmann, S. Mathews, and M. Mirotznik, “High-resolution iris image reconstruction from low-resolution imagery,” Proc. SPIE 6313, 63130D (2006).
[CrossRef]

Mirotznik, M.

R. Barnard, V. P. Pauca, T. C. Torgersen, R. J. Plemmons, S. Prasad, J. van der Gracht, J. Nagy, J. Chung, G. Behrmann, S. Mathews, and M. Mirotznik, “High-resolution iris image reconstruction from low-resolution imagery,” Proc. SPIE 6313, 63130D (2006).
[CrossRef]

Miyamoto, M.

Miyatake, S.

Miyazaki, D.

Morimoto, T.

Myers, K. J.

H. H. Barrett and K. J. Myers, Foundations of Image Science (Wiley-Interscience, 2004), Chaps. 7 and 15.

Nagy, J.

R. Barnard, V. P. Pauca, T. C. Torgersen, R. J. Plemmons, S. Prasad, J. van der Gracht, J. Nagy, J. Chung, G. Behrmann, S. Mathews, and M. Mirotznik, “High-resolution iris image reconstruction from low-resolution imagery,” Proc. SPIE 6313, 63130D (2006).
[CrossRef]

Narayanswamy, R.

R. Narayanswamy, P. E. X. Silveira, H. Setty, V. P. Pauca, and J. van der Gracht, “Extended depth-of-field iris recognition system for a workstation environment,” Proc. SPIE 5779, 41-50 (2005).
[CrossRef]

R. Narayanswamy, G. E. Johnson, P. E. X. Silveira, and H. B. Wach, “Extending the imaging volume for biometric iris recognition,” Appl. Opt. 44, 701-712 (2005).
[CrossRef] [PubMed]

Nguyen, N. X.

N. X. Nguyen, “Numerical algorithms for image superresolution,” Ph. D. dissertation (Stanford University, 2000).

Papoulis, A.

A. Papoulis, “Generalized sampling expansion,” IEEE Trans. Circuits Syst. 24, 652-654 (1977).
[CrossRef]

A. Papoulis and S. U. Pillai, Probability, Random Variables and Stochastic Processes (McGraw-Hill, 2001).

Pauca, V. P.

V. P. Pauca, D. Chen, J. van der Gracht, R. J. Plemmons, S. Prasad, and T. C. Torgersen, “Pupil phase encoding for multi-aperture imaging,” Proc. SPIE 7074, 70740D (2008).
[CrossRef]

R. Barnard, V. P. Pauca, T. C. Torgersen, R. J. Plemmons, S. Prasad, J. van der Gracht, J. Nagy, J. Chung, G. Behrmann, S. Mathews, and M. Mirotznik, “High-resolution iris image reconstruction from low-resolution imagery,” Proc. SPIE 6313, 63130D (2006).
[CrossRef]

R. Narayanswamy, P. E. X. Silveira, H. Setty, V. P. Pauca, and J. van der Gracht, “Extended depth-of-field iris recognition system for a workstation environment,” Proc. SPIE 5779, 41-50 (2005).
[CrossRef]

Pillai, S. U.

A. Papoulis and S. U. Pillai, Probability, Random Variables and Stochastic Processes (McGraw-Hill, 2001).

Plemmons, R. J.

V. P. Pauca, D. Chen, J. van der Gracht, R. J. Plemmons, S. Prasad, and T. C. Torgersen, “Pupil phase encoding for multi-aperture imaging,” Proc. SPIE 7074, 70740D (2008).
[CrossRef]

R. Barnard, V. P. Pauca, T. C. Torgersen, R. J. Plemmons, S. Prasad, J. van der Gracht, J. Nagy, J. Chung, G. Behrmann, S. Mathews, and M. Mirotznik, “High-resolution iris image reconstruction from low-resolution imagery,” Proc. SPIE 6313, 63130D (2006).
[CrossRef]

Prasad, S.

V. P. Pauca, D. Chen, J. van der Gracht, R. J. Plemmons, S. Prasad, and T. C. Torgersen, “Pupil phase encoding for multi-aperture imaging,” Proc. SPIE 7074, 70740D (2008).
[CrossRef]

S. Prasad, “Digital superresolution and the generalized sampling theorem,” J. Opt. Soc. Am. A 24, 311-325(2007).
[CrossRef]

R. Barnard, V. P. Pauca, T. C. Torgersen, R. J. Plemmons, S. Prasad, J. van der Gracht, J. Nagy, J. Chung, G. Behrmann, S. Mathews, and M. Mirotznik, “High-resolution iris image reconstruction from low-resolution imagery,” Proc. SPIE 6313, 63130D (2006).
[CrossRef]

Robinson, M. D.

Samms, R. W.

Sanderson, S.

S. Sanderson and J. Erbetta, “Authentication for secure environments based on iris scanning technology,” in IEE Colloquium on Visual Biometrics (IEEE, 2000), pp. 8/1-8/7.

Setty, H.

R. Narayanswamy, P. E. X. Silveira, H. Setty, V. P. Pauca, and J. van der Gracht, “Extended depth-of-field iris recognition system for a workstation environment,” Proc. SPIE 5779, 41-50 (2005).
[CrossRef]

Shogenji, R.

Silveira, P. E. X.

R. Narayanswamy, P. E. X. Silveira, H. Setty, V. P. Pauca, and J. van der Gracht, “Extended depth-of-field iris recognition system for a workstation environment,” Proc. SPIE 5779, 41-50 (2005).
[CrossRef]

R. Narayanswamy, G. E. Johnson, P. E. X. Silveira, and H. B. Wach, “Extending the imaging volume for biometric iris recognition,” Appl. Opt. 44, 701-712 (2005).
[CrossRef] [PubMed]

Stork, D. G.

Takagi, T.

Y. Itakura, S. Tsutsumi, and T. Takagi, “Statistical properties of the background noise for the atmospheric windows in the intermediate infrared region,” Infrared Phys. 14, 17-29(1974).
[CrossRef]

Tanida, J.

Torgersen, T. C.

V. P. Pauca, D. Chen, J. van der Gracht, R. J. Plemmons, S. Prasad, and T. C. Torgersen, “Pupil phase encoding for multi-aperture imaging,” Proc. SPIE 7074, 70740D (2008).
[CrossRef]

R. Barnard, V. P. Pauca, T. C. Torgersen, R. J. Plemmons, S. Prasad, J. van der Gracht, J. Nagy, J. Chung, G. Behrmann, S. Mathews, and M. Mirotznik, “High-resolution iris image reconstruction from low-resolution imagery,” Proc. SPIE 6313, 63130D (2006).
[CrossRef]

Tsutsumi, S.

Y. Itakura, S. Tsutsumi, and T. Takagi, “Statistical properties of the background noise for the atmospheric windows in the intermediate infrared region,” Infrared Phys. 14, 17-29(1974).
[CrossRef]

van der Gracht, J.

V. P. Pauca, D. Chen, J. van der Gracht, R. J. Plemmons, S. Prasad, and T. C. Torgersen, “Pupil phase encoding for multi-aperture imaging,” Proc. SPIE 7074, 70740D (2008).
[CrossRef]

R. Barnard, V. P. Pauca, T. C. Torgersen, R. J. Plemmons, S. Prasad, J. van der Gracht, J. Nagy, J. Chung, G. Behrmann, S. Mathews, and M. Mirotznik, “High-resolution iris image reconstruction from low-resolution imagery,” Proc. SPIE 6313, 63130D (2006).
[CrossRef]

R. Narayanswamy, P. E. X. Silveira, H. Setty, V. P. Pauca, and J. van der Gracht, “Extended depth-of-field iris recognition system for a workstation environment,” Proc. SPIE 5779, 41-50 (2005).
[CrossRef]

Wach, H. B.

Wenzel, W.

W. Wenzel and K. Hamacher, “A stochastic tunneling approach for global minimization,” Phys. Rev. Lett. 82, 3003-3007(1999).
[CrossRef]

Wolf, E.

M. Born and E. Wolf, Principles of Optics (Pergamon, 1989), Chap. 9.

Yamada, K.

Appl. Opt. (6)

IEEE Trans. Circ. Syst. Video Tech. (1)

J. G. Daugman, “How iris recognition works,” IEEE Trans. Circ. Syst. Video Tech. 14, 21-30 (2004).
[CrossRef]

IEEE Trans. Circuits Syst. (1)

A. Papoulis, “Generalized sampling expansion,” IEEE Trans. Circuits Syst. 24, 652-654 (1977).
[CrossRef]

IEEE Trans. Pattern Anal. Mach. Intell. (1)

J. G. Daugman, “High confidence visual recognition of persons by a test of statistical independence,” IEEE Trans. Pattern Anal. Mach. Intell. 15, 1148-1161 (1993).
[CrossRef]

Infrared Phys. (1)

Y. Itakura, S. Tsutsumi, and T. Takagi, “Statistical properties of the background noise for the atmospheric windows in the intermediate infrared region,” Infrared Phys. 14, 17-29(1974).
[CrossRef]

J. Opt. Soc. Am. (1)

D. J. Field, “Relations between the statistics of natural images and the response properties of cortical cells,” J. Opt. Soc. Am. 4, 2379-2394 (1987).
[CrossRef]

J. Opt. Soc. Am. A (1)

Opt. Lett. (1)

Pattern Recogn. (1)

J. G. Daugman, “The importance of being random: statistical principles of iris recognition,” Pattern Recogn. 36, 279-291(2003).
[CrossRef]

Phys. Rev. Lett. (1)

W. Wenzel and K. Hamacher, “A stochastic tunneling approach for global minimization,” Phys. Rev. Lett. 82, 3003-3007(1999).
[CrossRef]

Proc. SPIE (3)

V. P. Pauca, D. Chen, J. van der Gracht, R. J. Plemmons, S. Prasad, and T. C. Torgersen, “Pupil phase encoding for multi-aperture imaging,” Proc. SPIE 7074, 70740D (2008).
[CrossRef]

R. Barnard, V. P. Pauca, T. C. Torgersen, R. J. Plemmons, S. Prasad, J. van der Gracht, J. Nagy, J. Chung, G. Behrmann, S. Mathews, and M. Mirotznik, “High-resolution iris image reconstruction from low-resolution imagery,” Proc. SPIE 6313, 63130D (2006).
[CrossRef]

R. Narayanswamy, P. E. X. Silveira, H. Setty, V. P. Pauca, and J. van der Gracht, “Extended depth-of-field iris recognition system for a workstation environment,” Proc. SPIE 5779, 41-50 (2005).
[CrossRef]

Other (11)

N. X. Nguyen, “Numerical algorithms for image superresolution,” Ph. D. dissertation (Stanford University, 2000).

L. Masek, “Recognition of human iris patterns for biometric identification,” Technical report (University of Western Australia, 2003).

S. Sanderson and J. Erbetta, “Authentication for secure environments based on iris scanning technology,” in IEE Colloquium on Visual Biometrics (IEEE, 2000), pp. 8/1-8/7.

S. Kay, Fundamentals of Statistical Signal Processing: Detection Theory (Prentice-Hall, 1993).

CASIA-IrisV1 database, http://www.cbsr.ia.ac.cn/IrisDatabase.htm.

J. W. Goodman, Introduction to Fourier Optics (McGraw-Hill, 1996), Chap. 7.

M. Born and E. Wolf, Principles of Optics (Pergamon, 1989), Chap. 9.

H. H. Barrett and K. J. Myers, Foundations of Image Science (Wiley-Interscience, 2004), Chaps. 7 and 15.

H. C. Andrews and B. R. Hunt, Digital Image Restoration (Prentice-Hall, 1977).

A. Papoulis and S. U. Pillai, Probability, Random Variables and Stochastic Processes (McGraw-Hill, 2001).

MPI 1.1 standard, http://www.mpi-forum.org/docs/mpi-11-html/mpi-report.html.

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Figures (14)

Fig. 1
Fig. 1

PSF-engineered multiaperture imaging system layout.

Fig. 2
Fig. 2

Iris examples from the training dataset.

Fig. 3
Fig. 3

Model fit and training estimate of the object power spectral density: a radial profile.

Fig. 4
Fig. 4

Examples of (a) iris segmentation, (b) masked iris texture region, (c) unwrapped iris, and (d) iris code.

Fig. 5
Fig. 5

Illustration of FRR and FAR definitions in the context of intraclass and interclass probability densities.

Fig. 6
Fig. 6

Optimized ZPEL imager with K = 1 (a) pupil phase, (b) optical PSF, and (c) optical PSF of the TOMBO imager.

Fig. 7
Fig. 7

Cross-section MTF profiles of optimized ZPEL imager with K = 1 .

Fig. 8
Fig. 8

Optimized ZPEL imager with K = 4 : (a) pupil phase and (b) optical PSF.

Fig. 9
Fig. 9

Cross-section MTF profiles of optimized ZPEL imager with K = 4 .

Fig. 10
Fig. 10

Optimized ZPEL imager with K = 9 : (a) pupil phase and (b) optical PSF.

Fig. 11
Fig. 11

Cross-section MTF profiles of optimized ZPEL imager with K = 9 .

Fig. 12
Fig. 12

Optimized ZPEL imager with K = 16 : (a) pupil phase and (b) optical PSF.

Fig. 13
Fig. 13

Cross-section MTF profiles of optimized ZPEL imager with K = 16 .

Fig. 14
Fig. 14

Iris examples from the validation dataset.

Tables (3)

Tables Icon

Table 1 Imaging System Performance (FRR) for K = 1 , K = 4 , K = 9 , and K = 16 on Training Dataset

Tables Icon

Table 2 TOMBO Imaging System Performance (FRR) with Defocus and K = 1 on Training Dataset

Tables Icon

Table 3 Imaging System Performance (FRR) for K = 1 , K = 4 , K = 9 , and K = 16 on Validation Dataset

Equations (19)

Equations on this page are rendered with MathJax. Learn more.

g k = H k f + n k ,
H k = D C S k ,
g = H c f + n ,
t pupil ( ρ , θ ) = t amp ( ρ ) exp ( j 2 π ( n r 1 ) t phase ( ρ , θ ) λ ) ,
t phase ( ρ , θ ) = i = 1 P a i · Z i ( ρ , θ ) ,
h ( ρ , θ ) = A c ( λ f l ) 4 | T pupil ( ρ λ f l , θ ) | 2 ,
T pupil ( ω ) = F 2 { t pupil ( ρ , θ ) } ,
h d ( l , m ) = d 2 d 2 d 2 d 2 h ( x l d , y m d ) d x d y { ( l , m ) l = L L , m = L L } ,
W = R ff H c T ( H c R ff H c T + R nn ) 1 ,
R ^ ff = 1 160 k = 1 160 r ff k .
S ^ ff ( ρ ) = F 2 ( R ^ ff ) .
S ff ( ρ ) = σ f 2 ( 1 + 2 π μ d ρ 2 ) 3 2 .
Q ( f ^ ) = 1 2 f ^ t A f ^ b t f ^ .
f ^ k + 1 = f ^ k + α k p k ,
α k = p k t Q k d k ,
G log ( ρ ) = exp ( log ( ρ ρ o ) 2 log ( σ g ρ o ) ) ,
s ( t code ) = k , i min d h d ( t code c mask k , R i ( r code k ) c mask k ) ,
d h d ( t code c mask , r code c mask ) = ( t code c mask r code c mask ) W ,
s ( t code ) H 1 H 0 T H D ,

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