Biometric cryptosystem based on discretized fingerprint texture descriptors

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摘要

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.

论文关键词:BCH,Bose–Chaudhuri–Hocquenghem,BPA,belief propagation algorithm,DROBA,detection rate optimized bit allocation,ECC,error-correcting code,EER,error equal rate,FAR,false accept rate,FCS,fuzzy commitment scheme,FRR,false reject rate,GAR,genuine acceptance rate,LCM,least common multiple,LBP,local binary pattern,LDerivP,local derivative pattern,LDP,local direction pattern,LDPC,low-density parity-check,MPA,message-passing algorithm,PEG,progressive edge-growth,ROI,region of interest,SPA,sum-product algorithm,Fuzzy commitment scheme,Fingerprint texture descriptors,Local binary pattern,Biometric discretization,Error-correcting code

论文评审过程:Available online 16 October 2012.

论文官网地址:https://doi.org/10.1016/j.eswa.2012.10.009