Fingerprint Recognition using Gabor Filter


The KIPS Transactions:PartB , Vol. 9, No. 5, pp. 653-662, Oct. 2002
10.3745/KIPSTB.2002.9.5.653,   PDF Download:

Abstract

Fingerprint recognition is a task to find a matching pattern in a database for a specific persons fingerprint. To accomplish this task, preprocessing, classification, and matching steps are taken for a large-scale fingerprint database but only the matching step is taken without classification for a small-scale database. The primary matching method is based on minutiae (ridge ending point, bifurcation). This matching method, however, requires a very complex computation to extract minutiae and match minutiae-to-minutiae accurately due to translation, rotation, nonlinear deformation of fingerprint and occurrence of spurious minutiae. In addition, this method requires a laborious preprocessing step in order to improve the quality of fingerprint images. This paper proposes a new simple method to eliminate these problems. With this method, Gabor variance is used instead of minutiae for fingerprint recognition. The Gabor variance is computed from Gabor features that result from filtering a fingerprint image through Gabor filter. In this paper, this method is described and its test result is shown, demonstrating the potential of using this new method for fingerprint recognition.


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Cite this article
[IEEE Style]
H. B. Shim and Y. B. Park, "Fingerprint Recognition using Gabor Filter," The KIPS Transactions:PartB , vol. 9, no. 5, pp. 653-662, 2002. DOI: 10.3745/KIPSTB.2002.9.5.653.

[ACM Style]
Hyun Bo Shim and Young Bae Park. 2002. Fingerprint Recognition using Gabor Filter. The KIPS Transactions:PartB , 9, 5, (2002), 653-662. DOI: 10.3745/KIPSTB.2002.9.5.653.