Abstract
In this paper a biometric system for personal identification, realized through the manipulation of retinal fundus images and the detection of its bifurcation points, is described. In the image pre-processing step, a strong contrast exaltation between blood vessels and the background in retinal image is carried out; then blood vessels are extracted and next the vasculature bifurcation and crossover points are identified within squared shaped regions used to window the image. Finally the features sets are compared with a pattern recognition algorithm and a novel formulation is introduced to evaluate a similarity score and to obtain the personal identification.
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References
Jain, A., Bolle, R., Pankanti, S.: Biometrics: Personal Identification in Networked Society, p. 123. Springer Science/Business Media, New York (1996)
Wilson, C.L., McCabe, R.M.: Simple Test Procedure for Image-based Biometric Verification Systems. NISTIR 6336, National Institute of Standards and Technology (1999), http://www.itl.nist.gov/iaui/894.03/pubs.htm
Tower, P.: The Fundus Oculi in Monozygotic Twins: Report of Six Pairs of Identical Twins. Archives of Ophthalmology 54, 225–239 (1955)
Simon, C., Goldstein, I.: A New Scientific Method of Identification. New York State Journal of Medicine 35(18), 901–906 (1935)
Kresimir, D.I., Mislav, G.: A Survey of Biometric Recognition Methods. In: 46th International SyrnPoSium Electronics in Marine, ELMAR-2004, Zadar, Croatia (2004)
Naka, K.I., Rushton, W.A.: S-potentials from Luminosity Units in the Retina of fish (Cyprinidae). Journal of Physiology 185, 587–599 (1966)
Bevilacqua, V., Cariello, L., Cambò, S., Daleno, D., Mastronardi, G.: Retinal Fundus Features Hybrid Detection based on a Genetic Algorithm. In: Proceedings of the Workshop on Medical Applications of Genetic and Evolutionary Computation (MedGEC), Seattle (USA) (2005)
Steger, C.: An Unbiased Detector of Curvilinear Structures. Proceedings of IEEE Transactions on Pattern Analysis and Machine Intelligence 20(2) (1998)
Ballard, D.H.: Generalizing the Hough Transform to detect arbitrary shapes. Pattern Recognition 13, 111–122 (1981)
Mastronardi, G., Daleno, D., Bevilacqua, V., Chiaia, G.: Tecniche di identificazione personale basate sulla trasformata generalizzata di Hough applicata a nuvole di punti. In: Proceedings of National Conf. AICA 2007 (Associazione italiana per l’informatica ed il calcolo distribuito), Milano (Italy) (2007) ISBN 88-901620-3-1
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Bevilacqua, V. et al. (2008). Retinal Fundus Biometric Analysis for Personal Identifications. In: Huang, DS., Wunsch, D.C., Levine, D.S., Jo, KH. (eds) Advanced Intelligent Computing Theories and Applications. With Aspects of Artificial Intelligence. ICIC 2008. Lecture Notes in Computer Science(), vol 5227. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-85984-0_147
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DOI: https://doi.org/10.1007/978-3-540-85984-0_147
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-85983-3
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