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Title: Adaptive pore model for fingerprint pore extraction
Authors: Zhao, Q
Zhang, L 
Zhang, D 
Luo, N
Bao, J
Issue Date: 2008
Source: Proceedings - International Conference on Pattern Recognition, 2008, 4761458 How to cite?
Abstract: Sweat pores have been recently employed for automated fingerprint recognition, in which the pores are usually extracted by using a computationally expensive skeletonization method or a unitary scale isotropic pore model. In this paper, however, we show that real pores are not always isotropic. To accurately and robustly extract pores, we propose an adaptive anisotropic pore model, whose parameters are adjusted adaptively according to the fingerprint ridge direction and period. The fingerprint image is partitioned into blocks and a local pore model is determined for each block. With the local pore model, a matched filter is used to extract the pores within each block. Experiments on a high resolution (1200dpi) fingerprint dataset are performed and the results demonstrate that the proposed pore model and pore extraction method can locate pores more accurately and robustly in comparison with other state-of-the-art pore extractors.
Description: 2008 19th International Conference on Pattern Recognition, ICPR 2008, Tampa, FL, 8-11 December 2008
ISBN: 9781424421756
ISSN: 1051-4651
Appears in Collections:Conference Paper

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