Fingerprint Valley Extraction Using Local Gabor Filter

Abstract

Fingerprint authentication remains as one of the most prominent biometric identification methods. In this paper, we propose to use the fingerprint valley instead of ridges for the Binarization and Thinning process to extract fingerprint valley minutiae, because lots of research has done on ridges not on valleys. We first use several preprocessing steps on the binary image in order to eliminate the spurious lakes and dots, and to reduce the spurious islands, bridges, and spurs in the skeleton image. By removing all the bug pixels introduced at the thinning stage, our algorithm can detect a maximum number of minutiae from the fingerprint skeleton using the Gabor filter. This allows the true minutiae preserved and false minutiae removed in post processing stages. Gabor filter has also given lots of best results on ridges extraction. So we tried gabor filter for valley extraction and we got number of minutiae extracted differs from ridges to valleys. The proposed method saves memory space, and also speeds up the whole procedure.