Binary gabor statistical features for palmprint template protection

Meiru Mu, Qiuqi Ruan, X. Shao, Lieuwe Jan Spreeuwers, Raymond N.J. Veldhuis

Research output: Chapter in Book/Report/Conference proceedingConference contributionAcademicpeer-review

Abstract

The biometric template protection system requires a highquality biometric channel and a well-designed error correction code (ECC). Due to the intra-class variations of biometric data, an efficient fixed-length binary feature extractor is required to provide a high-quality biometric channel so that the system is robust and accurate, and to allow a secret key to be combined for security. In this paper we present a binary palmprint feature extraction method to achieve a robust biometric channel for template protection system. The real-valued texture statistical features are firstly extracted based on Gabor magnitude and phase responses. Then a bits quantization and selection algorithm is introduced. Experimental results on the HongKong PloyU Palmprint database verify the efficiency of our method which achieves low verification error rate by a robust palmprint binary representation of low bit error rate.
Original languageUndefined
Title of host publicationJoint IAPR International Workshop on Structural and Syntactic Pattern Recognition (SSPR 2012) and Statistical Techniques in Pattern Recognition (SPR 2012)
Place of PublicationBerlin
PublisherSpringer
Pages593-601
Number of pages9
ISBN (Print)978-3-642-34165-6
DOIs
Publication statusPublished - 7 Nov 2012

Publication series

NameLecture Notes in Computer Science
PublisherSpringer Verlag
Volume7626

Keywords

  • SCS-Safety
  • EWI-22989
  • Palmprint verification
  • IR-83638
  • Gabor filtering
  • Feature template protection
  • METIS-296445
  • Binary feature extraction

Cite this

Mu, M., Ruan, Q., Shao, X., Spreeuwers, L. J., & Veldhuis, R. N. J. (2012). Binary gabor statistical features for palmprint template protection. In Joint IAPR International Workshop on Structural and Syntactic Pattern Recognition (SSPR 2012) and Statistical Techniques in Pattern Recognition (SPR 2012) (pp. 593-601). (Lecture Notes in Computer Science; Vol. 7626). Berlin: Springer. https://doi.org/10.1007/978-3-642-34166-3_65
Mu, Meiru ; Ruan, Qiuqi ; Shao, X. ; Spreeuwers, Lieuwe Jan ; Veldhuis, Raymond N.J. / Binary gabor statistical features for palmprint template protection. Joint IAPR International Workshop on Structural and Syntactic Pattern Recognition (SSPR 2012) and Statistical Techniques in Pattern Recognition (SPR 2012). Berlin : Springer, 2012. pp. 593-601 (Lecture Notes in Computer Science).
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title = "Binary gabor statistical features for palmprint template protection",
abstract = "The biometric template protection system requires a highquality biometric channel and a well-designed error correction code (ECC). Due to the intra-class variations of biometric data, an efficient fixed-length binary feature extractor is required to provide a high-quality biometric channel so that the system is robust and accurate, and to allow a secret key to be combined for security. In this paper we present a binary palmprint feature extraction method to achieve a robust biometric channel for template protection system. The real-valued texture statistical features are firstly extracted based on Gabor magnitude and phase responses. Then a bits quantization and selection algorithm is introduced. Experimental results on the HongKong PloyU Palmprint database verify the efficiency of our method which achieves low verification error rate by a robust palmprint binary representation of low bit error rate.",
keywords = "SCS-Safety, EWI-22989, Palmprint verification, IR-83638, Gabor filtering, Feature template protection, METIS-296445, Binary feature extraction",
author = "Meiru Mu and Qiuqi Ruan and X. Shao and Spreeuwers, {Lieuwe Jan} and Veldhuis, {Raymond N.J.}",
note = "10.1007/978-3-642-34166-3_65",
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Mu, M, Ruan, Q, Shao, X, Spreeuwers, LJ & Veldhuis, RNJ 2012, Binary gabor statistical features for palmprint template protection. in Joint IAPR International Workshop on Structural and Syntactic Pattern Recognition (SSPR 2012) and Statistical Techniques in Pattern Recognition (SPR 2012). Lecture Notes in Computer Science, vol. 7626, Springer, Berlin, pp. 593-601. https://doi.org/10.1007/978-3-642-34166-3_65

Binary gabor statistical features for palmprint template protection. / Mu, Meiru; Ruan, Qiuqi; Shao, X.; Spreeuwers, Lieuwe Jan; Veldhuis, Raymond N.J.

Joint IAPR International Workshop on Structural and Syntactic Pattern Recognition (SSPR 2012) and Statistical Techniques in Pattern Recognition (SPR 2012). Berlin : Springer, 2012. p. 593-601 (Lecture Notes in Computer Science; Vol. 7626).

Research output: Chapter in Book/Report/Conference proceedingConference contributionAcademicpeer-review

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AU - Ruan, Qiuqi

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AU - Spreeuwers, Lieuwe Jan

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N2 - The biometric template protection system requires a highquality biometric channel and a well-designed error correction code (ECC). Due to the intra-class variations of biometric data, an efficient fixed-length binary feature extractor is required to provide a high-quality biometric channel so that the system is robust and accurate, and to allow a secret key to be combined for security. In this paper we present a binary palmprint feature extraction method to achieve a robust biometric channel for template protection system. The real-valued texture statistical features are firstly extracted based on Gabor magnitude and phase responses. Then a bits quantization and selection algorithm is introduced. Experimental results on the HongKong PloyU Palmprint database verify the efficiency of our method which achieves low verification error rate by a robust palmprint binary representation of low bit error rate.

AB - The biometric template protection system requires a highquality biometric channel and a well-designed error correction code (ECC). Due to the intra-class variations of biometric data, an efficient fixed-length binary feature extractor is required to provide a high-quality biometric channel so that the system is robust and accurate, and to allow a secret key to be combined for security. In this paper we present a binary palmprint feature extraction method to achieve a robust biometric channel for template protection system. The real-valued texture statistical features are firstly extracted based on Gabor magnitude and phase responses. Then a bits quantization and selection algorithm is introduced. Experimental results on the HongKong PloyU Palmprint database verify the efficiency of our method which achieves low verification error rate by a robust palmprint binary representation of low bit error rate.

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Mu M, Ruan Q, Shao X, Spreeuwers LJ, Veldhuis RNJ. Binary gabor statistical features for palmprint template protection. In Joint IAPR International Workshop on Structural and Syntactic Pattern Recognition (SSPR 2012) and Statistical Techniques in Pattern Recognition (SPR 2012). Berlin: Springer. 2012. p. 593-601. (Lecture Notes in Computer Science). https://doi.org/10.1007/978-3-642-34166-3_65