Blood vessel structure segmentation from retinal scan image using Kekre's fast codebook generation algorithm

ABSTRACT

Human retina is a well-known biometric trait and its use is emerging as retinal blood vessels have high degree of uniqueness. To implement a retinal biometric system we need to separate the blood vessel structure. A retina segmentation system based on vector quantization using Kekre's Fast Codebook Generation Algorithm (KFCG) is proposed in this paper. The retina image is used to generate the initial codevector in a multidimensional vector space. KFCG is then applied to form clusters of the codevectors. Each cluster corresponds to an image plane. These planes are separated for blood vessel segmentation. The results are promising and this technique can be used for retina image preprocessing.

References

1. A. K. Jain, "Handbook of Biometrics", TMH, USA, 2nd Edition, 2003
2. A. Hoover, V. Kouznetsova, and M. Goldbaum, "Locating blood vessels in retinal images by piecewise threshold probing of a matched filter response," IEEE Trans. Med. Imag., vol. 19, pp. 203--210, Mar. 2000.
3. A. Sinthanayothin, J. F. Boyce, H. L. Cook, and T. H. Williamson, "Automated localization of the optic disc, fovea, and retinal blood vessels from digital color fundus images," Br. J. Ophthalmol., vol. 83, no. 8, pp. 902--910, 1999.
4. Sinthanayothin, J. F. Boyce, T. H. Williamson, H. L. Cook, E. Mensah, S. Lal, and D. Usher, "Automated detection of diabetic retinopathy on digital fundus images," Diabetic Med., vol. 19, no. 2, pp. 105--112, 2002.
5. D. J. Cornforth, H. J. Jelinek, et. al., "Development of retinal blood vessel segmentation methodology using wavelet transforms for assessment of diabetic retinopathy." Complexity International Volume 11, 2005
6. Drive Digital Retinal Images for Vessel Extraction, Image Science Institute.
7. H. B. Kekre, Tanuja K. Sarode, "New Fast Improved Codebook Generation Algorithm for Color Images using Vector Quantization," International Journal of Engineering and Technology, vol. 1, No. 1, pp.: 67--77, September 2008.
8. H. B. Kekre, Tanuja K. Sarode, "Fast Codebook Generation Algorithm for Color Images using Vector Quantization," International Journal of Computer Science and Information Technology, Vol. 1, No. 1, pp.: 7--12, Jan 2009.
9. E. T. Miller, J. O'Meara "Blood Vessel Segmentation in Retinal Images", Published: February 8, 2004
10. F. Zana and J. C. Klein, "Segmentation of vessel-like patterns using mathematical morphology and curvature evaluation," IEEE Trans. Image Processing, vol. 10, no. 7, pp. 1010--1019, 2001.
11. H. J. Jelinek, D. J. Cornforth, J. V. B. Soares, R. M. Cesar, Jr., M. J. Cree, P. Mitchell, and T. Bossomaier, "Development of retinal blood vessel segmentation methodology using wavelet transforms for assessment of diabetic retinopathy", Complexity International, volume 11, 2005
12. J. Staal, M. Abràmoff, M. Niemeijer, M. Viergever, B. Ginneken "Ridge-Based Vessel Segmentation in Color Images of the Retina", IEEE Transactions on Medical Imaging, Vol. 23, NO. 4, April 2004
13. Kie Yih Edward Wong, G. Sainarayanan, Ali Chekim Kie Yih Edward Wong, "Palmprint Identification Using Wavelet Energy." IEEE 2007, No.: 1-4244-1355-9/07
14. M. E. Martínez-Pérez, A. D. Hughes et. al., "Scale-space analysis for the characterization of retinal blood vessels," in Medical Image Computing and Computer-Assisted Intervention---MICCAI'99
15. S. Chaudhuri, S. Chatterjee, N. Katz, M. Nelson, and M. Goldbaum, "Detection of blood vessels in retinal images using two-dimensional matched filters," IEEE Trans. Med. Imag., vol. 8, pp. 263--269, Sept. 1989.

Index Terms

• Computing methodologies

  • Artificial intelligence

    • Computer vision

      • Computer vision problems

  • Computer graphics

    • Image manipulation

• Security and privacy

  • Security services

    • Access control

    • Authentication

  • Systems security

    • Operating systems security