A fuzzy C-Means algorithm for fingerprint segmentation
Date
2015
Embargo
Advisor
Coadvisor
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Language
English
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Abstract
Fingerprint segmentation is a crucial step of an automatic fingerprint identification system, since an accurate segmentation promote both the elimination of spurious minutiae close to the foreground boundaries and the reduction of the computation time of the following steps. In this paper, a new, and more robust fingerprint segmentation algorithm is proposed. The main novelty is the introduction of a more
robust binarization process in the framework, mainly based on the fuzzy C-means clustering algorithm. Experimental results demonstrate significant benchmark progress on three existing FVC datasets.
Keywords
Fingerprint segmentation, Fuzzy C-means clustering, Morphological processing
Document Type
conferenceObject
Publisher Version
10.1007/978-3-319-19390-8n
Dataset
Citation
Ferreira, P., Sequeira, A., Rebelo, A. (2015). A fuzzy C-Means algorithm for fingerprint segmentation. In Iberian Conference on Pattern Recognition and Image Analysis (IbPRIA), Santiago de Compostela, Spain, 2015. doi: 10.1007/978-3-319-19390-8n. Disponível no Repositório UPT, http://hdl.handle.net/11328/2475
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Access Type
Open Access