Fingerprint Recognition Using Hybrid Matching Algorithm
| dc.contributor.advisor | Dagne, Assefa (PhD) | |
| dc.contributor.author | Melese, Biniyam | |
| dc.date.accessioned | 2018-06-27T08:02:09Z | |
| dc.date.accessioned | 2023-11-04T15:14:51Z | |
| dc.date.available | 2018-06-27T08:02:09Z | |
| dc.date.available | 2023-11-04T15:14:51Z | |
| dc.date.issued | 2003-08 | |
| dc.description.abstract | Fingerprint matching is one of the most important problems in fingerprint recognition system. Generally, fingerprint matching algorithm can be classified into two: minutiae based and non‐minutiae based. In minutiae based matching, ridge endings and ridge bifurcations are used as discriminative features for matching, but in non‐minutiae based, features other than minutiae are used. Hybrid approaches by combining minutiae with other non‐minutiae based matching methods are used to improve fingerprint matching methods. In this paper, alignment‐based elastic matching algorithm, is used for minutiae based matching and new non‐minutiae method proposed which solve the shortcomings of the algorithms proposed by Jain et.al. The experiment was done on 320 fingerprints of Fingerprint Verification Competition 2002 set‐B databases and showed that the hybrid matching algorithm improved the Equal Error Rate from ~11.8 % to 7.55% than the minutiae based matching algorithm. Keyword: Image processing, Fingerprint recognition, local orientation, local frequency, minutiae, absolute average deviation from the mean, Gabor filter. | en_US |
| dc.identifier.uri | http://etd.aau.edu.et/handle/123456789/3974 | |
| dc.language.iso | en | en_US |
| dc.subject | Image processing | en_US |
| dc.subject | Fingerprint recognition | en_US |
| dc.subject | local orientation | en_US |
| dc.subject | local frequency | en_US |
| dc.subject | minutiae | en_US |
| dc.subject | absolute average deviation from the mean | en_US |
| dc.subject | Gabor filter | en_US |
| dc.title | Fingerprint Recognition Using Hybrid Matching Algorithm | en_US |
| dc.type | Thesis | en_US |