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Improved Biohashing Method Based on Most Intensive Histogram Block Location

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Neural Information Processing (ICONIP 2014)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 8836))

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Abstract

Biohashing is a promising cancellable biometrics method. However, it suffers from a problem known as ‘stolen token scenario’. The performance of the biometric system drops significantly if the Biohashing private token is stolen. To solve this problem, this paper proposes a new method termed as Most Intensive Histogram Block Location (MIBL) to extract additional information of the p-th best gradient magnitude. Experimental analysis shows that the proposed method is able to solve the stolen token problem with error equal rates as low as 1.46% and 7.27% when the stolen token scenario occurred for both FVC2002 DB1 and DB2 respectively.

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Syarif, M.A., Ong, T.S., Teoh, A.B.J., Tee, C. (2014). Improved Biohashing Method Based on Most Intensive Histogram Block Location. In: Loo, C.K., Yap, K.S., Wong, K.W., Beng Jin, A.T., Huang, K. (eds) Neural Information Processing. ICONIP 2014. Lecture Notes in Computer Science, vol 8836. Springer, Cham. https://doi.org/10.1007/978-3-319-12643-2_78

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  • DOI: https://doi.org/10.1007/978-3-319-12643-2_78

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-12642-5

  • Online ISBN: 978-3-319-12643-2

  • eBook Packages: Computer ScienceComputer Science (R0)

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