@inproceedings{e1662c5892fc448aa1b1c6918411fd4d,
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 ; Joint IAPR International Workshop on Structural and Syntactic Pattern Recognition (SSPR 2012) and Statistical Techniques in Pattern Recognition (SPR 2012) ; Conference date: 07-11-2012 Through 09-11-2012",
year = "2012",
month = nov,
day = "7",
doi = "10.1007/978-3-642-34166-3\_65",
language = "Undefined",
isbn = "978-3-642-34165-6",
series = "Lecture Notes in Computer Science",
publisher = "Springer",
pages = "593--601",
booktitle = "Joint IAPR International Workshop on Structural and Syntactic Pattern Recognition (SSPR 2012) and Statistical Techniques in Pattern Recognition (SPR 2012)",
address = "Germany",
}