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Segmentation of low quality fingerprint images
Högskolan Dalarna, Akademin Industri och samhälle, Datateknik.ORCID-id: 0000-0002-1429-2345
Högskolan Dalarna, Akademin Industri och samhälle, Datateknik.ORCID-id: 0000-0001-6526-6537
Högskolan Dalarna, Akademin Industri och samhälle, Datateknik.
2010 (engelsk)Konferansepaper, Publicerat paper (Fagfellevurdert)
Abstract [en]

This paper presents a new algorithm to segment fingerprint images. The algorithm uses four features, the global mean, the local mean, variance and coherence of the image to achieve the fingerprint segmentation. Based on these features, a rule based system is built to segment the image. The proposed algorithm is implemented in three stages; pre-processing, segmentation, and post-processing. Gaussian filter and histogram equalization are applied in the pre-processing stage. Segmentation is applied using the local features. Finally, fill the gaps algorithm and a modified version of Otsu thresholding are invoked in the post-processing stage. In order to evaluate the performance of this method, experiments are performed on FVC2000 DB1. Segmentation of 100 images is performed and compared with manual examinations of human experts. It shows that the proposed algorithm achieves a correct segmentation of 82% of images under test.

sted, utgiver, år, opplag, sider
IEEE conference proceedings, 2010.
HSV kategori
Forskningsprogram
Komplexa system - mikrodataanalys
Identifikatorer
URN: urn:nbn:se:du-4682DOI: 10.1109/MCIT.2010.5444844OAI: oai:dalea.du.se:4682DiVA, id: diva2:522117
Konferanse
International Conference on Multimedia Computing and Information Technology (MCIT-2010) , Sharja, UAE, March 2-4, 2010
Tilgjengelig fra: 2010-05-06 Laget: 2010-05-06 Sist oppdatert: 2016-02-12bibliografisk kontrollert

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