Binary biometrics: An analytic framework to estimate the performance curves under gaussian assumption

IEEE Transactions on Systems, Man, and Cybernetics Part A:Systems and Humans

Volumn 40, Issue 3, 2010, Pages 555-571

  Kelkboom, Emile J C ^a   Garcia Molina, Gary ^a   Breebaart, Jeroen ^a   Veldhuis, Raymond N J ^b   Kevenaar, Tom A M ^c   Jonker, Willem ^a,b  

^a PHILIPS RESEARCH LABORATORIES   (Netherlands)

^b UNIVERSITY OF TWENTE   (Netherlands)

^c Priv ID   (Netherlands)

Author keywords

Binary biometrics; Binary template matching; Performance estimation; Template protection

Indexed keywords

ANALYTIC EXPRESSIONS; BINARY REPRESENTATIONS; BINARY TEMPLATE MATCHING; BINARY VECTORS; BIOMETRIC DATA; BIOMETRIC DATABASE; BIOMETRIC SYSTEMS; BIT-ERRORS; CANCELABLE BIOMETRICS; CORRECTING CAPACITY; CRYPTOGRAPHIC PRIMITIVES; DATA SYSTEMS; DECISION THRESHOLD; ERROR CORRECTING CODE; FACE RECOGNITION GRAND CHALLENGES; FALSE ACCEPTANCE; FALSE ACCEPTANCE RATE; FALSE REJECTION RATE; FINGERPRINT VERIFICATION; FUZZY COMMITMENT; FUZZY EXTRACTORS; FUZZY VAULT; GAUSSIAN ASSUMPTION; GAUSSIANS; MAXIMUM ERROR; NUMBER OF SAMPLES; PERFORMANCE CURVE; PERFORMANCE ESTIMATION; SCIENTIFIC COMMUNITY; TEMPLATE PROTECTION; TRADE-OFF CURVES;

ARTIFICIAL INTELLIGENCE; BIT ERROR RATE; COMMUNICATION CHANNELS (INFORMATION THEORY); ERROR DETECTION; ESTIMATION; FACE RECOGNITION; HAMMING DISTANCE; PASSIVATION; TEMPLATE MATCHING;

BIOMETRICS;

EID: 77951204673     PISSN: 10834427     EISSN: None     Source Type: Journal    
DOI: 10.1109/TSMCA.2010.2041657     Document Type: Conference Paper

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