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Fingerprint Classification Method Based on Analysis of Singularities and Geometric Framework

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Part of the book series:Lecture Notes in Computer Science ((LNTCS,volume 4847))

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Abstract

According to the former contributions, the authors present a novel fingerprint classification method based on analysis of singularities and geometric framework. First, a robust pseudoridges extraction algorithm on fingerprints is adopted to extract the global geometric shape of fingerprint ridges of pattern area. Then, by use of the detected singularities and with the help of the analysis of the global geometric shape of fingerprint ridges of pattern area, the fingerprint image is classified into different pre-specified classes. This algorithm has been tested on the NJU fingerprint database which contains 2500 images. For the 1000 images in this database, the classification accuracy is 92.2%.

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Authors and Affiliations

  1. Faculty of Computer, Guangdong University of Technology, Guangzhou 510090, China

    Taizhe Tan, Yinwei Zhan, Lei Ding & Sun Sheng

Authors
  1. Taizhe Tan

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  2. Yinwei Zhan

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  3. Lei Ding

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  4. Sun Sheng

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Editor information

Ming Xu Yinwei Zhan Jiannong Cao Yijun Liu

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© 2007 Springer-Verlag Berlin Heidelberg

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Tan, T., Zhan, Y., Ding, L., Sheng, S. (2007). Fingerprint Classification Method Based on Analysis of Singularities and Geometric Framework. In: Xu, M., Zhan, Y., Cao, J., Liu, Y. (eds) Advanced Parallel Processing Technologies. APPT 2007. Lecture Notes in Computer Science, vol 4847. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-76837-1_76

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