Abstract
Recently, the biometric information such as faces, fingerprints, and irises has been used widely in a security system for biometric authentication. Among these biometric features which are unique to each individual, the blood vessel pattern in fingers is superior for identifying individuals and verifying their identities: We may obtain easily the information on blood vessels which is almost impossible to counterfeit because the pattern exists inside the body unlike the others. In this work, we propose a finger vein recognition method using an illumination normalization and a SIFT (Scale-Invariant Feature Transform) matching identification. To verify individual identification, the proposed methodology is composed of two steps: (i) we first normalize the illumination of finger vein images, and (ii) extract SIFT descriptors from the image and match them to the given data. Experimental results indicate that the proposed method is shown to be successful for authentication system.
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© 2012 Springer-Verlag Berlin Heidelberg
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Kim, HG., Lee, E.J., Yoon, GJ., Yang, SD., Lee, E.C., Yoon, S.M. (2012). Illumination Normalization for SIFT Based Finger Vein Authentication. In: Bebis, G., et al. Advances in Visual Computing. ISVC 2012. Lecture Notes in Computer Science, vol 7432. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-33191-6_3
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DOI: https://doi.org/10.1007/978-3-642-33191-6_3
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-33190-9
Online ISBN: 978-3-642-33191-6
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