Abstract
This paper proposes a novel fingerprint classification method. It uses an SPCNN (Simplified Pulse Coupled Neural Network) to estimate directional image of fingerprint, and quantizes them to obtain fingerprint vector. Then, a fully trained LVQ (Learning Vector Quantization) neural network is used as classifier for the fingerprint vector to determine the corresponding fingerprint classification. Experiments show this proposed method is robust and has high classification accuracy.
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References
Henry, E.R.: Classification and Uses of Finger Prints. Routledge, London (1900)
Johnson, J.L., Padgett, M.L.: PCNN Models and Applications. IEEE Transactions On Neural Networks 10, 480–498 (1999)
Khaled, A.N.: On learning to estimate the block directional image of a fingerprint using a hierarchical neural network. Neural Networks 16, 133–144 (2003)
Candela, G.T., et al.: PCASYSA Pattern-Level Classification Automation System for Fingerprints. NIST Technical Report NISTIR 5647 (August 1995)
Jain, A.K., Prabhakar, S., Hong, L.: A Multichannel Approach to Fingerprint Classification. IEEE Transactions on Pattern Analysis and Machine Intelligence 21, 348–359 (1999)
Yuan, Y., Gian, L., et al.: Combining flat and structured representations for fingerprint classification with recursive neural networks and support vector machines. Pattern Recognition 36, 397–406 (2003)
Khaled, A.N.: Fingerprints classification using artificial neural networks: a combined structural and statistical approach. Neural Networks 14, 1293–1395 (2001)
Mohhamad, T., Vakil, B., Nikola, P.: Premature clustering phenomenon and new trainning algorithms for LVQ. Pattern Recognition 36, 1901–1912 (2003)
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© 2006 Springer-Verlag Berlin Heidelberg
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Ji, L., Yi, Z., Pu, X. (2006). Fingerprint Classification by SPCNN and Combined LVQ Networks. In: Jiao, L., Wang, L., Gao, Xb., Liu, J., Wu, F. (eds) Advances in Natural Computation. ICNC 2006. Lecture Notes in Computer Science, vol 4221. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11881070_55
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DOI: https://doi.org/10.1007/11881070_55
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-45901-9
Online ISBN: 978-3-540-45902-6
eBook Packages: Computer ScienceComputer Science (R0)