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2018 | OriginalPaper | Buchkapitel

Fingerprint Pore Extraction Using Convolutional Neural Networks and Logical Operation

verfasst von : Yuanhao Zhao, Feng Liu, Linlin Shen

Erschienen in: Biometric Recognition

Verlag: Springer International Publishing

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Abstract

Sweat pores have been proved to be discriminative and successfully used for automatic fingerprint recognition. It is crucial to extract pores precisely to achieve high recognition accuracy. To extract pores accurately and robustly, we propose a novel coarse-to-fine detection method based on convolutional neural networks (CNN) and logical operation. More specifically, pore candidates are coarsely estimated using logical operation at first; then, coarse pore candidates are further judged through well-trained CNN models; precise pore locations are finally refined by logical and morphological operation. The experimental results evaluated on the public dataset show that the proposed method outperforms other state-of-the-art methods in comparison.

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Titel: Fingerprint Pore Extraction Using Convolutional Neural Networks and Logical Operation
verfasst von: Yuanhao Zhao
Feng Liu
Linlin Shen
Verlag: Springer International Publishing
Buch: Biometric Recognition
Print ISBN: 978-3-319-97908-3

Electronic ISBN: 978-3-319-97909-0

Copyright-Jahr: 2018
DOI: https://doi.org/10.1007/978-3-319-97909-0_5

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