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IAPR Workshop on Artificial Neural Networks in Pattern Recognition

ANNPR 2012: Artificial Neural Networks in Pattern Recognition pp 115–126Cite as

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Improving Iris Recognition through New Target Vectors in MLP Artificial Neural Networks

Improving Iris Recognition through New Target Vectors in MLP Artificial Neural Networks

  • José Ricardo Gonçalves Manzan22,
  • Shigueo Nomura22,
  • Keiji Yamanaka22,
  • Milena Bueno Pereira Carneiro22 &
  • …
  • Antônio C. Paschoarelli Veiga22 
  • Conference paper
  • 1307 Accesses

  • 3 Citations

Part of the Lecture Notes in Computer Science book series (LNAI,volume 7477)

Abstract

This paper compares the performance of multilayer perceptron (MLP) networks trained with conventional bipolar target vectors (CBVs) and orthogonal bipolar new target vectors (OBVs) for biometric pattern recognition. The experimental analysis consisted of using biometric patterns from CASIA Iris Image Database developed by Chinese Academy of Sciences - Institute of Automation. The experiments were performed in order to obtain the best recognition rates, leading to the comparison of results from both conventional and new target vectors. The experimental results have shown that MLPs trained with OBVs can better recognize the patterns of iris images than MLPs trained with CBVs.

Keywords

  • Biometric pattern
  • iris image
  • conventional bipolar vector
  • multilayer perceptron
  • orthogonal bipolar vector
  • pattern recognition
  • target vector

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Author information

Authors and Affiliations

  1. Faculty of Electrical Engineering, Federal University of Uberlândia, Av. João Naves de Ávila, 2160, Bloco 3N - Campus Santa Mônica, CEP: 38400-902, Uberlândia, MG, Brasil

    José Ricardo Gonçalves Manzan, Shigueo Nomura, Keiji Yamanaka, Milena Bueno Pereira Carneiro & Antônio C. Paschoarelli Veiga

Authors
  1. José Ricardo Gonçalves Manzan
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  2. Shigueo Nomura
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  3. Keiji Yamanaka
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  4. Milena Bueno Pereira Carneiro
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  5. Antônio C. Paschoarelli Veiga
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Editor information

Editors and Affiliations

  1. Fondazione Bruno Kessler (FBK), 38123, Trento, Italy

    Nadia Mana

  2. Institute of Neural Information Processing, University of Ulm, 89069, Ulm, Germany

    Friedhelm Schwenker

  3. Dipartimento di Ingegneria dell’Informazione, Università di Siena, 53100, Siena, Italy

    Edmondo Trentin

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© 2012 Springer-Verlag Berlin Heidelberg

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Manzan, J.R.G., Nomura, S., Yamanaka, K., Bueno Pereira Carneiro, M., Veiga, A.C.P. (2012). Improving Iris Recognition through New Target Vectors in MLP Artificial Neural Networks. In: Mana, N., Schwenker, F., Trentin, E. (eds) Artificial Neural Networks in Pattern Recognition. ANNPR 2012. Lecture Notes in Computer Science(), vol 7477. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-33212-8_11

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  • DOI: https://doi.org/10.1007/978-3-642-33212-8_11

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