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Anchorage, AK, USA
June 23, 2008 to June 28, 2008
ISBN: 978-1-4244-2339-2
pp: 1-6
Tomohiko Ohtsuka , Tokyo National College of Technology, Dept. of Electronic Eng., 1220-2 Kunugida, Hachiohji, 1930997, Japan
Daisuke Watanabe , Tokyo National College of Technology, Dept. of Electronic Eng., 1220-2 Kunugida, Hachiohji, 1930997, Japan
Daisuke Tomizawa , Tokyo National College of Technology, Dept. of Electronic Eng., 1220-2 Kunugida, Hachiohji, 1930997, Japan
Yuta Hasegawa , Tokyo National College of Technology, Dept. of Electronic Eng., 1220-2 Kunugida, Hachiohji, 1930997, Japan
Hiroyuki Aoki , Tokyo National College of Technology, Dept. of Electronic Eng., 1220-2 Kunugida, Hachiohji, 1930997, Japan
ABSTRACT
The singular points of fingerprints, namely, core and delta, are important referential points for the classification of fingerprints. Several conventional approaches such as the Poincaré index method have been proposed; however, these approaches cannot achieve the reliable detection of poor-quality fingerprints. In this paper, we propose a new core and delta detection method by singular candidate analysis using an extended relational graph. In order to use both the local and global features of the ridge direction patterns and to realize a method with high tolerance to local image noise, singular candidate analysis is adopted in the detection process; this analysis involves the extraction of locations in which the probability of the existence of a singular point is high. The experimental results show that the success rate of this approach is higher than that of the Poincaré index method by 10% for singularity detection using the fingerprint image databases FVC2000 and FVC2002. These databases contain several poor quality images, even though the average computation time is 15%–30% greater than the Poincaré index method.
CITATION
Tomohiko Ohtsuka, Daisuke Watanabe, Daisuke Tomizawa, Yuta Hasegawa, Hiroyuki Aoki, "Reliable detection of core and delta in fingerprints by using singular candidate method", CVPRW, 2008, 2012 IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops, 2012 IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops 2008, pp. 1-6, doi:10.1109/CVPRW.2008.4563119
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