Generalized Net Model of Person Recognition Using ART2 Neural Network and Viola-Jones Algorithm

  • Todor PetkovEmail author
  • Sotir Sotirov
  • Stanimir Surchev
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 401)


In this paper we present a method for the purpose to detect a certain person in an image. We use the tools of neural networks and face recognition algorithm to achieve our goal. The type of neural network is unsupervised adaptive resonance theory 2 (ART2). It is trained by the set of person images and divided into two clusters—the first cluster represents the human who has to be found and the second one represents the other people. The algorithm which is used for face detection is Viola-Jones and the combination with neural networks helps to identify the person. The generalized net model is used to describe the recognition process.


ART2 neural network Face recognition Generalized nets 


  1. 1.
    Atanassov, K.: Generalized Nets. World Scientific, Singapore, New Jersey, London (1991)CrossRefzbMATHGoogle Scholar
  2. 2.
    Beale M., Demuth H., Hagan M.: Neural Network Design, PWS Publishing Company (1996)Google Scholar
  3. 3.
    Ben, K., van der Smagt, P.: An Introduction to Neural Networks, Chapter 6 8th edn. University of Amsterdam (1996)Google Scholar
  4. 4.
    Carpenter, G.A., Grossberg, S.: The ART of adaptive pattern recognition by a self-organizing neural network. Computer 21(3), 77–88 (1988)CrossRefGoogle Scholar
  5. 5.
    Chelali, F., Djeradi, A.: Face recognition system using neural network with Gabor and discrete wavelet transform parameterization. In: 6th International Conference on Soft Computing and Pattern Recognition, SoCPaR (2014)Google Scholar
  6. 6.
    Fausett, L.: Fundamentals of Neural Networks; Architecture, Algorithms and Applications (1993)Google Scholar
  7. 7.
    Kramer, O.: Dimensionality Reduction with Unsupervised Nearest Neighbors, Springer, Intelligent systems reference library, vol. 51, (2013)Google Scholar
  8. 8.
    Murphy, T., Schultz, R.: A Viola-Jones based hybrid face detection framework. In: Proceedings of SPIE—The International Society for Optical Engineering, vol. 9025, (2014)Google Scholar
  9. 9.
    Rashidan, M., Mustafah, Y.M.: Analysis of artificial neural network and Viola-Jones algorithm based moving object detection. In: Proceedings—5th International Conference on Computer and Communication Engineering: Emerging Technologies via Comp-Unication Convergence, ICCCE (2014)Google Scholar
  10. 10.
    Tian, D., Liu, Y.H., Shi, J.R.: Dynamic Clustering Algorithm Based on Adaptive Resonance Theory, Springer, 2006Google Scholar
  11. 11.
    Viola, P., Jones, J.: Robust real-time face detection. Int. J. Comput. Vision 57(2), 137–154 (2004)CrossRefGoogle Scholar
  12. 12.
    Wójtowicz, W., Ogiela, M.R.: Biometric watermarks based on face recognition methods for authentication of digital images. Secur. Commun. Netw. 8(9), 1672–1687 (2015)CrossRefGoogle Scholar

Copyright information

© Springer International Publishing Switzerland 2016

Authors and Affiliations

  1. 1.Intelligent Systems LaboratoryUniversity Professor Dr. Assen Zlatarov BurgasBurgasBulgaria

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