Báo cáo hóa học: " Research Article Biometric Quantization through Detection Rate Optimized Bit Allocation"

Tuyển tập báo cáo các nghiên cứu khoa học quốc tế ngành hóa học dành cho các bạn yêu hóa học tham khảo đề tài: Research Article Biometric Quantization through Detection Rate Optimized Bit Allocation | Hindawi Publishing Corporation EURASIP Journal on Advances in Signal Processing Volume 2009 Article ID 784834 16 pages doi 2009 784834 Research Article Biometric Quantization through Detection Rate Optimized Bit Allocation C. Chen 1 R. N. J. Veldhuis 1 T. A. M. Kevenaar 2 and A. H. M. Akkermans2 1 Signals and Systems Group Faculty of Electrical Engineering University of Twente P. O. Box 217 7500 AE Enschede The Netherlands 2Philips Research High Tech Campus 5656 AE Eindhoven The Netherlands Correspondence should be addressed to C. Chen Received 23 January 2009 Accepted 8 April 2009 Recommended by Yasar Becerikli Extracting binary strings from real-valued biometric templates is a fundamental step in many biometric template protection systems such as fuzzy commitment fuzzy extractor secure sketch and helper data systems. Previous work has been focusing on the design of optimal quantization and coding for each single feature component yet the binary string concatenation of all coded feature components is not optimal. In this paper we present a detection rate optimized bit allocation DROBA principle which assigns more bits to discriminative features and fewer bits to nondiscriminative features. We further propose a dynamic programming DP approach and a greedy search GS approach to achieve DROBA. Experiments of DROBA on the FVC2000 fingerprint database and the FRGC face database show good performances. As a universal method DROBA is applicable to arbitrary biometric modalities such as fingerprint texture iris signature and face. DROBA will bring significant benefits not only to the template protection systems but also to the systems with fast matching requirements or constrained storage capability. Copyright 2009 C. Chen et al. This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use distribution and reproduction in any medium provided the original work is properly cited. 1. .

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