Biometric cryptosystem based on discretized fingerprint texture descriptors

Yadigar Imamverdiyev; Andrew Beng Jin Teoh; Jaihie Kim

doi:10.1016/j.eswa.2012.10.009

Biometric cryptosystem based on discretized fingerprint texture descriptors

Yadigar Imamverdiyev, Andrew Beng Jin Teoh, Jaihie Kim

Department of Electrical and Electronic Engineering

Research output: Contribution to journal › Article › peer-review

35 Citations (Scopus)

Abstract

This paper focuses on a biometric cryptosystem implementation and evaluation based on a number of fingerprint texture descriptors. The texture descriptors, namely, the Gabor filter-based FingerCode, a local binary pattern (LBP), and a local direction pattern (LDP), and their various combinations are considered. These fingerprint texture descriptors are binarized using a biometric discretization method and used in a fuzzy commitment scheme (FCS). We constructed the biometric cryptosystems, which achieve a good performance, by fusing discretized fingerprint texture descriptors and using effective error-correcting codes. We tested the proposed system on a FVC2000 DB2a fingerprint database, and the results demonstrate that the new system significantly improves the performance of the FCS for texture-based fingerprints.

Original language	English
Pages (from-to)	1888-1901
Number of pages	14
Journal	Expert Systems with Applications
Volume	40
Issue number	5
DOIs	https://doi.org/10.1016/j.eswa.2012.10.009
Publication status	Published - 2013 Apr

Bibliographical note

Funding Information:
This work was supported by the National Research Foundation of Korea (NRF) grant funded by the Korea government (MEST) .

All Science Journal Classification (ASJC) codes

Engineering(all)
Computer Science Applications
Artificial Intelligence

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10.1016/j.eswa.2012.10.009

Cite this

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title = "Biometric cryptosystem based on discretized fingerprint texture descriptors",

abstract = "This paper focuses on a biometric cryptosystem implementation and evaluation based on a number of fingerprint texture descriptors. The texture descriptors, namely, the Gabor filter-based FingerCode, a local binary pattern (LBP), and a local direction pattern (LDP), and their various combinations are considered. These fingerprint texture descriptors are binarized using a biometric discretization method and used in a fuzzy commitment scheme (FCS). We constructed the biometric cryptosystems, which achieve a good performance, by fusing discretized fingerprint texture descriptors and using effective error-correcting codes. We tested the proposed system on a FVC2000 DB2a fingerprint database, and the results demonstrate that the new system significantly improves the performance of the FCS for texture-based fingerprints.",

author = "Yadigar Imamverdiyev and Teoh, {Andrew Beng Jin} and Jaihie Kim",

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AU - Imamverdiyev, Yadigar

AU - Teoh, Andrew Beng Jin

AU - Kim, Jaihie

N1 - Funding Information: This work was supported by the National Research Foundation of Korea (NRF) grant funded by the Korea government (MEST) .

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N2 - This paper focuses on a biometric cryptosystem implementation and evaluation based on a number of fingerprint texture descriptors. The texture descriptors, namely, the Gabor filter-based FingerCode, a local binary pattern (LBP), and a local direction pattern (LDP), and their various combinations are considered. These fingerprint texture descriptors are binarized using a biometric discretization method and used in a fuzzy commitment scheme (FCS). We constructed the biometric cryptosystems, which achieve a good performance, by fusing discretized fingerprint texture descriptors and using effective error-correcting codes. We tested the proposed system on a FVC2000 DB2a fingerprint database, and the results demonstrate that the new system significantly improves the performance of the FCS for texture-based fingerprints.

AB - This paper focuses on a biometric cryptosystem implementation and evaluation based on a number of fingerprint texture descriptors. The texture descriptors, namely, the Gabor filter-based FingerCode, a local binary pattern (LBP), and a local direction pattern (LDP), and their various combinations are considered. These fingerprint texture descriptors are binarized using a biometric discretization method and used in a fuzzy commitment scheme (FCS). We constructed the biometric cryptosystems, which achieve a good performance, by fusing discretized fingerprint texture descriptors and using effective error-correcting codes. We tested the proposed system on a FVC2000 DB2a fingerprint database, and the results demonstrate that the new system significantly improves the performance of the FCS for texture-based fingerprints.

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Biometric cryptosystem based on discretized fingerprint texture descriptors

Abstract

Bibliographical note

All Science Journal Classification (ASJC) codes

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