Abstract
This paper deals with a proposal of the algorithm for features extraction from the blood vessels on the back of eyeball. Automated extraction is based on the bifurcations (points where a single vessel splits into two vessels) in retina. Each particular bifurcation is subsequently specified by its own position given by the coordinate system derived from the mutual position of the optic disc and fovea. The complete algorithm has been developed in C++ language and uses OpenCV library for image processing. This proposed method was evaluated on available images of the STARE and DRIVE databases.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Das, R.: Retina recognition: Biometric technology in practice. Journal of Documents: A Bimonthly Magazine about Developments in the Security Industry (22), 11–14 (2011)
Chowdhary, B., Latif, S.: Pattern Matching Algorithm using Polar Spectrum in Retina Recognition for Human Identification System. Australian Journal of Basic and Applied Sciences/International Network for Scientific Information; INSInet (5), 1385–1392 (2011)
Saradhi, G.V., Balasubramanian, S., Chandrasekaran, V.: Performance Enhancement of Optic Disc Boundary Detection using Active Contours via Improved Homogenization of Optic Disc Region. In: International Conference on Information and Automation, ICIA, pp. 264–269 (2006)
Aquino, A., Gegúndez, M.E., Marín, D.: Automated Optic Disc Detection in Retinal Images of Patients with Diabetic Retinopathy and Risk of Macular Edema. World Academy of Science, Engineering and Technology (60), 87–92 (2009)
Siddalingaswamy, P.C., Prabhu, G.K.: Automated Detection of Anatomical Structures in Retinal Images. In: International Conference on Computational Intelligence and Multimedia Applications, vol. 3(10), pp. 164–168 (2007)
Chen, Z., Abidi, B.R., Page, D.L., Abidi, M.A.: Gray-Level Grouping (GLG): An Automatic Method for Optimized Image Contrast Enhancement—Part I: The Basic Method. IEEE Transactions on Image Processing: A Publication of the IEEE Signal Processing Society (8), 2290–2302 (2006)
Chen, Z., Abidi, B.R., Page, D.L., Abidi, M.A.: Gray-Level Grouping (GLG): An Automatic Method for Optimized Image Contrast Enhancement—Part II: The Variations. IEEE Transactions on Image Processing: A Publication of the IEEE Signal Processing Society (8), 2303–2314 (2006)
Chaudhuri, S., Chatterjee, S., Katz, N., Nelson, M., Goldbaum, M.: Detection of blood vessels in retinal images using two-dimensional matched filters. IEEE Transactions on Medical Imaging (3), 263–269 (1989)
Parker, J.: Algorithms for image processing and computer vision. John Wiley & Sons (1996) ISBN 0471140562
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2012 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Drozd, R., Hájek, J., Drahanský, M. (2012). An Algorithm for Retina Features Extraction Based on Position of the Blood Vessel Bifurcation. In: Zheng, WS., Sun, Z., Wang, Y., Chen, X., Yuen, P.C., Lai, J. (eds) Biometric Recognition. CCBR 2012. Lecture Notes in Computer Science, vol 7701. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-35136-5_37
Download citation
DOI: https://doi.org/10.1007/978-3-642-35136-5_37
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-35135-8
Online ISBN: 978-3-642-35136-5
eBook Packages: Computer ScienceComputer Science (R0)