Singular points detection in fingerprint images using Gabor transform

In fingerprints, singular points, including cores and deltas, are very important features. To classify the types of fingerprints, the number and the position of cores and deltas are concerned. For fingerprint matching, some approaches used the core point to align two fingerprint images to overcome t...

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Bibliographic Details
Published in2008 9th International Conference on Signal Processing pp. 2078 - 2081
Main Authors Chih-Jen Lee, I-Homg Jeng, Tai-Ning Yang, Chun-Jung Chen, Keng-Li Lin
Format Conference Proceeding
LanguageEnglish
Published IEEE 01.10.2008
Subjects
Access control
Authentication
Computer science
Fingerprint recognition
Frequency
Gabor filters
Image matching
Internet
Robustness
Sampling methods
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Summary:In fingerprints, singular points, including cores and deltas, are very important features. To classify the types of fingerprints, the number and the position of cores and deltas are concerned. For fingerprint matching, some approaches used the core point to align two fingerprint images to overcome the problems from rotation and translation. Therefore, singular points detection is a critical process for both fingerprint matching and fingerprint classification. The process of singular points detection must be robust; otherwise, the performance of the whole fingerprint recognition system would be influenced heavily. In this paper, we will use Gabor transform, sampling by a complete set of Gabor basis functions, to demonstrate the phenomenon of the regions of singular points. Besides, we will develop a robust method to detect singular points.
ISBN:1424421780
9781424421787
ISSN:2164-5221
DOI:10.1109/ICOSP.2008.4697554