Please use this identifier to cite or link to this item: https://dspace.iiti.ac.in/handle/123456789/5315
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dc.contributor.authorChauhan, Niteshen_US
dc.contributor.authorSoni, Mayanken_US
dc.contributor.authorAnand, Vijayen_US
dc.contributor.authorKanhangad, Viveken_US
dc.date.accessioned2022-03-17T01:00:00Z-
dc.date.accessioned2022-03-17T15:41:30Z-
dc.date.available2022-03-17T01:00:00Z-
dc.date.available2022-03-17T15:41:30Z-
dc.date.issued2017-
dc.identifier.citationChauhan, N., Soni, M., Anand, V., & Kanhangad, V. (2017). Fingerprint classification using crease features. Paper presented at the 2016 IEEE Students' Technology Symposium, TechSym 2016, 56-60. doi:10.1109/TechSym.2016.7872655en_US
dc.identifier.isbn9781509051632-
dc.identifier.otherEID(2-s2.0-85017028839)-
dc.identifier.urihttps://doi.org/10.1109/TechSym.2016.7872655-
dc.identifier.urihttps://dspace.iiti.ac.in/handle/123456789/5315-
dc.description.abstractExisting fingerprint classification techniques make use of Level-1 or Level-2 features or their combination for fingerprint classification. On the other hand, Level-3 features have not been explored much for fingerprint classification. Specifically, the use of crease for fingerprint classification does not exist in the literature. In this work, we explore the use of crease features for fingerprint classification. Experiments are performed on the publicly available Hong Kong PolyU high-resolution fingerprint database DBII. Our experimental results are very encouraging and indicate that creases have huge potential to improve the performance of fingerprint classification. © 2016 IEEE.en_US
dc.language.isoenen_US
dc.publisherInstitute of Electrical and Electronics Engineers Inc.en_US
dc.source2016 IEEE Students' Technology Symposium, TechSym 2016en_US
dc.subjectBiometricsen_US
dc.subjectcreaseen_US
dc.subjectFingerprint classificationen_US
dc.subjectFingerprint databaseen_US
dc.subjectHigh resolutionen_US
dc.subjectHong-kongen_US
dc.subjectLevel-1en_US
dc.subjectLevel-3 featuresen_US
dc.subjectClassification (of information)en_US
dc.titleFingerprint classification using crease featuresen_US
dc.typeConference Paperen_US
Appears in Collections:Department of Electrical Engineering

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