DocumentCode :
2603732
Title :
Ground truth and evaluation for latent fingerprint matching
Author :
Mikaelyan, Anna ; Bigun, Josef
Author_Institution :
Halmstad Univ., Halmstad, Sweden
fYear :
2012
fDate :
16-21 June 2012
Firstpage :
83
Lastpage :
88
Abstract :
In forensic fingerprint studies annotated databases is important for evaluating the performance of matchers as well as for educating fingerprint experts. We have established ground truths of minutia level correspondences for the publicly available NIST SD27 data set, whose minutia have been extracted by forensic fingerprint experts. We performed verification tests with two publicly available minutia matchers, Bozorth3 and k-plet, yielding Equal Error Rates of 36% and 40% respectively, suggesting that they have similar (poor) ability to separate a client from an impostor in latent versus tenprint queries. However, in an identification scenario, we found performance advantage of k-plet over Bozorth3, suggesting that the former can rank the similarities of fingerprints better. Regardless of the matcher, the general poor performance is a confirmation of previous findings related to latent vs tenprint matching. A finding influencing future practice is that the minutia level matching errors in terms of FA and FR may not be balanced (not equally good) even if FA and FR have been chosen to be so at finger level.
Keywords :
fingerprint identification; image matching; Bozorth3; NIST SD27 data set; forensic fingerprint studies annotated databases; ground truth; k-plet; latent fingerprint matching; minutia level correspondences; minutia level matching errors; tenprint queries; Databases; Engines; Fingerprint recognition; Forensics; Humans; NIST; Software;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Computer Vision and Pattern Recognition Workshops (CVPRW), 2012 IEEE Computer Society Conference on
Conference_Location :
Providence, RI
ISSN :
2160-7508
Print_ISBN :
978-1-4673-1611-8
Electronic_ISBN :
2160-7508
Type :
conf
DOI :
10.1109/CVPRW.2012.6239220
Filename :
6239220
Link To Document :
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