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Asian Applied Computing Conference

AACC 2004: Applied Computing pp 9–16Cite as

Development of Genetic Algorithm Embedded KNN for Fingerprint Recognition

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Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 3285))

Abstract

A Kohonen self-organizing neural network embedded with genetic algorithm for fingerprint recognition is proposed in this paper. The genetic algorithm is embedded to initiate the Kohonen classifers. By the proposed approach, the neural network learning performance and accuracy are greatly enhanced. In addition, the genetic algorithm can successfully avoid the neural network from being trapped in a local minimum. The proposed method was tested for the recognition of fingerprints. The results were promising to applications.

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References

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Author information

Authors and Affiliations

  1. University BDT College of Engg, Davanagere, 57704, India

    H. R. Sudarshana Reddy

  2. Manipal Institute of Technology, Manipal, India

    N. V. Subba Reddy

Authors
  1. H. R. Sudarshana Reddy
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  2. N. V. Subba Reddy
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Editor information

Editors and Affiliations

  1. Department of Computer Science, The University of York, YO10 5NG, Heslington, York, UK

    Suresh Manandhar

  2. Advanced Computer Architectures Group, Department of Computer Science, University of York, York, UK

    Jim Austin

  3. Department of Electrical Engineering, Indian Institute of Technology, 400076, Powai, Bombay, India

    Uday Desai

  4. Department of Computer Science, University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, 113-8654, Tokyo, Japan

    Yoshio Oyanagi

  5. Indian Institute of Information Technology, Bangalore, 26/C, Electronics City, Hosur Road, 560100, Bangalore, India

    Asoke K. Talukder

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© 2004 Springer-Verlag Berlin Heidelberg

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Reddy, H.R.S., Reddy, N.V.S. (2004). Development of Genetic Algorithm Embedded KNN for Fingerprint Recognition. In: Manandhar, S., Austin, J., Desai, U., Oyanagi, Y., Talukder, A.K. (eds) Applied Computing. AACC 2004. Lecture Notes in Computer Science, vol 3285. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-30176-9_2

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  • DOI: https://doi.org/10.1007/978-3-540-30176-9_2

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-23659-7

  • Online ISBN: 978-3-540-30176-9

  • eBook Packages: Springer Book Archive

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