Multispectral scleral patterns for ocular biometric recognition

Pattern Recognition Letters

Volumn 33, Issue 14, 2012, Pages 1860-1869

  Crihalmeanu, Simona ^a   Ross, Arun ^a  

^a West Virginia University   (United States)

Author keywords

Biometrics; Conjunctival vasculature; Multispectral; Ocular biometrics; Sclera

Indexed keywords

ACQUISITION DEVICE; BEHAVIORAL TRAITS; BIOMETRIC RECOGNITION; GAZE DIRECTION; IRIS PATTERNS; IRIS RECOGNITION; MATCHING SCHEME; MULTI-SPECTRAL; MULTISPECTRAL IMAGES; NEAR INFRARED SPECTRA; NOVEL ALGORITHM; RECOGNITION SYSTEMS; SCLERA; VASCULATURE; VISIBLE SPECTRA;

ALGORITHMS; FEATURE EXTRACTION; INFRARED DEVICES; NEAR INFRARED SPECTROSCOPY;

BIOMETRICS;

EID: 84865598659     PISSN: 01678655     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.patrec.2011.11.006     Document Type: Article

References (37)

1. Bayer, B.E., 1976. Color imaging array. U.S.Patent 3 971 065.
2. H. Bay, A. Ess, T. Tuyleraars, and L.V. Gool Speeded-up robust features Computer Vision and Image Understanding (CVIU) 110 3 2008 346 359
3. K.W. Bowyer, K. Hollingsworth, and P.J. Flynn Image understanding for iris biometrics: A survey Computer Vision and Image Understanding 110 2 2008 281 307
4. Brown, M., Lowe, D., 2002. Invariant features from interest point groups. In British Machine Vision Conf., pp. 656-665.
5. Crihalmeanu, S., Ross, A., 2011. On the use of multispectral conjunctival vasculature as a soft biometric. In: Proc. IEEE Workshop on Applications of Computer Vision (WACV), Kona, USA, pp. 204-211.
6. Crihalmeanu, S., Ross, A., Derakhshani, R., 2009. Enhancement and registration schemes for matching conjunctival vasculature. In: Proc. Internat. Conf. on Biometrics, Alghero, Italy, pp. 1240-1249.
7. J. Daugman How iris recognition works IEEE Trans. Circuit Systems Video Technol. 14 1 2004 21 30
8. Derakhshani, R., Ross, A., 2007. A texture-based neural network classifier for biometric identification using ocular surface vasculature. In: Proc. Internat. Joint Conf. on Neural Networks (IJCNN) Orlando, USA.
9. Derakhshani, R., Ross, A., Crihalmeanu, S., 2006. A new biometric modality based on conjunctival vasculature. In: Proc. Artificial Neural Networks in Engineering, St.Louis, MO.
10. R.C. Gonzales, and R.E. Woods Digital Image Processing second ed. 2001 Tom Robbins Upper Saddle River, New Jersey
11. G. Heath The episclera, sclera and conjunctiva, Optometry today Different. Diagnosis Ocular Dis. 9 2 2006 36 42
12. R. Hill Retina Identification Biometrics: Personal Identification in Networked Society 1999 Kluwer Academic pp. 123-141
13. A. Jain, A. Ross, and S. Prabhakar An introduction to biometric recognition IEEE Trans. Circuits Systems Video Technol. 14 1 2004 4 20
14. A. Jain, P. Flynn, and A. Ross 1st ed. Handbook of Biometrics vol. 233 2008 Springer Science + Business Media Spring Street, New York 10013, USA
15. J.J. Kanski Clinical Ophthalmology: A Systematic Approach 2003 Elsevier Science Limited
16. F. Maes, A. Collignon, D. Vandermeulen, G. Marchal, and P. Suetens Multimodality image registration by maximization of mutual information IEEE Trans. Med. Imag. 16 2 1997 187 198
17. D. Maltoni, D. Maio, A. Jain, and S. Prabhakar first ed. Handbook of Fingerprint recognition 233 2003 Springer Science+Business Media, Inc., Spring Street, New York, NY, USA
18. Neubeck, A., Gool, L.V., 2006. Efficient non-maximum suppression. In: Proc. 18th Internat. Conf. on Pattern Recognition (ICPR), vol. 3, pp. 850-855.
19. C.G. Owen, R.S.B. Newsom, A.R. Rudnicka, T.J. Ellis, and E.G. Woodward Vascular response of the bulbar conjunctiva to diabetes and elevated blood pressure Ophthalmology 112 10 2005 1801 1808
20. C.G. Owen, R.S.B. Newsom, A.R. Rudnicka, S. Barman, T.J. Ellis, and E.G. Woodward Diabetes and the tortuosity of vessels of the bulbar conjunctiva Ophthalmology 115 6 2008 e27 e32
21. U. Park, R. Jillela, A. Ross, and A.K. Jain Periocular biometrics in the visible spectrum IEEE Trans. Inform. Forensics Security (TIFS) 6 1 2011 96 106
22. Perez, E.M., Hughes, A.D., Stanton, A.V., Tom, S.A., Bharath, A.A., Parker, K.H., 1999. Segmentation of retinal blood vessels based on the second directional derivative and region growing. In: Internat. Conf. on Image Processing (ICIP), vol. 2, pp. 173-176.
23. S. Periaswamy, and H. Farid Elastic registration in the presence of intensity variations IEEE Trans. Med. Imag. 22 7 2003 865 874
24. H. Proenca Iris recognition: On the segmentation of degraded images acquired in the visible wavelength IEEE Trans. Pattern Anal. Machine Intell. 32 8 2010 1502 1516
25. L. Qiang, S. Shusuke, and D. Kunio Selective enhancement filters for nodules, vessels, and airway walls in two or three dimentional CT scans Med. Phys. 30 8 2003
26. A. Ross Iris recognition: The path forward IEEE Comput. 2010 30 35
27. A. Ross, K. Nandakumar, and A.K. Jain Handbook of Multibiometrics 2006 Springer Publishers
28. S.A.C. Schuckers, N.A. Schmid, A. Abhyankar, V. Dorairaj, C.K. Boyce, and L.A. Hornak On techniques for angle compensation in nonideal iris recognition IEEE Trans. Systems Man Cybernet. B: Cybernet. 37 5 2007 1176 1190
29. Selenick, I.W., 2002. A new complex-directional wavelet transform and its application to image denoising. In: IEEE Internat. Conf. on Image Processing, vol. 3, pp. 573-576.
30. M. Sonka, and J.M. Fitzpatrick Image Registration Handbook of Medical Imaging Medical Image Processing and Analysis vol. 2 2004 The International Society for Optical Engineering (SPIE) pp. 487-497
31. K. Trier Advances in organ biology The Sclera The Biology of the Eye vol. 10 2006 Elsevier Inc. pp. 353-373
32. C.J. Tucker Red and photographic infrared linear combinations for monitoring vegetation Remote Sens. Environ. 8 1979 127 150
33. P.A. Viola, and M.J. Jones Rapid object detection using a boosted cascade of simple features Comput. Vision Pattern Recognition 2001 511 518
34. Z. Wang, and A.C. Bovik Mean squared error: Love it or leave it? IEEE Signal Process. Mag. 2009 98 117
35. Z. Wang, A.C. Bovik, H.R. Sheikh, and E.P. Simoncelli Image quality assessment: From error measurement to structural similarity IEEE Trans. Image Process. 13 1 2004 600 612
36. Woodard, D., Pundlik, S., Miller, P., Jillela, R., Ross, A., 2010. On the use of periocular and iris biometrics in non-ideal imagery. In: Proc. Internat. Conf. on Pattern Recognition (ICPR), Istanbul, Turkey, pp. 201-204.
37. Zhou, Z., Du, E.Y., Thomas, N.L., 2011. A comprehensive sclera image quality measure. In: 11th International Conference on Control Automation Robotics and Vision (ICARCV), pp. 638-643.