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Illumination Normalization for SIFT Based Finger Vein Authentication

  • Hwi-Gang Kim
  • Eun Jung Lee
  • Gang-Joon Yoon
  • Sung-Dae Yang
  • Eui Chul Lee
  • Sang Min Yoon
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7432)

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.

Keywords

Verification System Sift Descriptor Vein Pattern Illumination Normalization Biometric Information 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  • Hwi-Gang Kim
    • 1
  • Eun Jung Lee
    • 1
  • Gang-Joon Yoon
    • 1
  • Sung-Dae Yang
    • 1
  • Eui Chul Lee
    • 2
  • Sang Min Yoon
    • 3
  1. 1.National Institute for Mathematical SciencesKorea
  2. 2.Sangmyung UniversityKorea
  3. 3.Yonsei UniversityKorea

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