Difference between revisions of "Publications:Pyramid-based Image Enhancement of Fingerprints"
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| − | |Name=Fronthaler, Hartwig | + | |Name=Fronthaler, Hartwig (harfrox) (Högskolan i Halmstad (2804), Sektionen för Informationsvetenskap, Data– och Elektroteknik (IDE) (3905), Halmstad Embedded and Intelligent Systems Research (EIS) (3938));Kollreider, Klaus (klakolx) (Högskolan i Halmstad (2804), Sektionen för Informationsvetenskap, Data– och Elektroteknik (IDE) (3905), Halmstad Embedded and Intelligent Systems Research (EIS) (3938));Bigun, Josef (josef) (Högskolan i Halmstad (2804), Sektionen för Informationsvetenskap, Data– och Elektroteknik (IDE) (3905), Halmstad Embedded and Intelligent Systems Research (EIS) (3938)) |
|Title=Pyramid-based Image Enhancement of Fingerprints | |Title=Pyramid-based Image Enhancement of Fingerprints | ||
|PublicationType=Conference Paper | |PublicationType=Conference Paper | ||
Latest revision as of 21:39, 30 September 2016
| Title | Pyramid-based Image Enhancement of Fingerprints |
|---|---|
| Author | Hartwig Fronthaler and Klaus Kollreider and Josef Bigun |
| Year | 2007 |
| PublicationType | Conference Paper |
| Journal | |
| HostPublication | 2007 IEEE Workshop on Automatic Identification Advanced Technologies proceedings : 7-8 June 2007, Alghero, Italy |
| Conference | 2007 IEEE Workshop on Automatic Identification Advanced Technologies proceedings : 7-8 June 2007, Alghero, Italy |
| DOI | http://dx.doi.org/10.1109/AUTOID.2007.380591 |
| Diva url | http://hh.diva-portal.org/smash/record.jsf?searchId=1&pid=diva2:239349 |
| Abstract | Reliable feature extraction is crucial for accurate biometric recognition. Unfortunately feature extraction is hampered by noisy input data, especially so in case of fingerprints. We propose a method to enhance the quality of a given fingerprint with the purpose to improve the recognition performance. A Laplacian like image-scale pyramid is used for this purpose to decompose the original fingerprint into 3 smaller images corresponding to different frequency bands. In a further step, contextual filtering is performed using these pyramid levels and 1D Gaussians, where the corresponding filtering directions are derived from the frequency-adapted structure tensor. All image processing is done in the spatial domain, avoiding block artifacts while conserving the biometric signal well. We report on comparative results and present quantitative improvements, by applying the standardized NIST FIS2 fingerprint matcher to the FVC2004 fingerprint database along with our as well as two other enhancements. The study confirms that the suggested enhancement robustifies feature detection, e.g. minutiae, which in turn improves the recognition (20% relative improvement in equal error rate on DB3 of FVC2004). |
