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Abstract
Finger vein pattern recognition is a biometric modality that uses features found in the blood vessel structure of the fingers. Vein pattern images are captured using a specialized infrared sensitive sensor which due to physical properties of the hemoglobin present in the blood stream give rise to a slight intensity difference between veins and tissue. We investigate five different contrast enhancement algorithms, which range from high to low computational complexity, and evaluate the performance by using five different quantitative contrast measuring methods.
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Authors and Affiliations
Department of Informatics and Mathematical Modelling, Technical University of Denmark, 2800, Kgs. Lyngby, Denmark
Martin Aastrup Olsen & Rasmus Larsen
Norwegian Information Security laboratory, Gjøvik University College, Gjøvik, Norway
Daniel Hartung & Christoph Busch
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Editors and Affiliations
Institute of Intelligent Machines, Chinese Academy of Sciences, Hefei, Anhui,, China
De-Shuang Huang
School of Computing and Intelligent Systems, University of Ulster at Magee Campus, BT48 7JL, Derry, Northern Ireland, UK
Martin McGinnity
Laboratoire LITIS, Université de Rouen, 76800, Saint Etienne du Rouvray, France
Laurent Heutte
Department of Electrical and Computer Engineering, Ryerson University, Toronto, Ontario, Canada
Xiao-Ping Zhang
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Olsen, M.A., Hartung, D., Busch, C., Larsen, R. (2010). Contrast Enhancement and Metrics for Biometric Vein Pattern Recognition. In: Huang, DS., McGinnity, M., Heutte, L., Zhang, XP. (eds) Advanced Intelligent Computing Theories and Applications. ICIC 2010. Communications in Computer and Information Science, vol 93. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-14831-6_56
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