2009 International Conference on Computational Intelligence and Security Proof of Two Kinds of Fingerprint Feature Extraction CNN Beijing, China December 11-December 14 ISBN: 978-0-7695-3931-7
DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/CIS.2009.69
The researches and applications of image processing based on the cellular neural network (CNN) have made great progress. The fingerprint feature extraction CNN are two kinds of CNN, which are able to extract the endings and bifurcations, two important features in a fingerprint image. This paper makes a further contribution to this topic. We first present the global tasks and the local rules of these two kinds of CNN. Then, we proof the correctness of those local rules mathematically.
Index Terms:
Cellular Neural Networks; von neumann neighborhood; fingerprint feature extraction
Citation:
LongMei Jie, Hui Wang, DeRong Li, GuoQiang Shao, "Proof of Two Kinds of Fingerprint Feature Extraction CNN," cis, vol. 1, pp.307-310, 2009 International Conference on Computational Intelligence and Security, 2009 Usage of this product signifies your acceptance of the Terms of Use. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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