dc.contributor.author | Hanmandlu, M.H. | |
dc.contributor.author | Ansari, A.Q. | |
dc.contributor.author | Kour, J. | |
dc.contributor.author | Goyal, K. | |
dc.contributor.author | Malekar, R. | |
dc.date.accessioned | 2016-11-29T06:52:30Z | |
dc.date.available | 2016-11-29T06:52:30Z | |
dc.date.issued | 2016-11-29 | |
dc.identifier.uri | http://localhost:8080/xmlui/handle/123456789/664 | |
dc.description.abstract | The detection of singular points (core and delta) accurately and reliably is very important for classification and matching of fingerprints. This paper presents a new approach for core point detection based on scale invariant feature transform (SIFT). Firstly, SIFT points are extracted, then reliability and ridge frequency criteria are applied to reduce the candidate points required to make a decision on the core point. Finally a suitable mask is applied to detect an accurate core point. Experiments on FVC2002 and FVC2004 databases show that our approach locates a unique reference point with high accuracy. Results of our approach are compared with those of the existing methods in terms of accuracy of core point detection. | en_US |
dc.language.iso | en_US | en_US |
dc.subject | Biometrics | en_US |
dc.subject | Corepoint | en_US |
dc.subject | Fingerprint | en_US |
dc.subject | Scale invariant feature transform | en_US |
dc.title | Scale invariant feature transform based fingerprint corepoint detection | en_US |
dc.type | Article | en_US |