Advertisement

Analysis of Different Neural Network Architectures in Face Recognition System

  • E. V. Sudhanva
  • V. N. Manjunath Aradhya
  • C. Naveena
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 380)

Abstract

Face Recognition is considered to be as one of the finest aspects of Computer Vision, also various Feature Extraction and classification techniques including Neural Network Architectures have made it even more interesting. In this paper, an attempt towards developing a model for better feature representation/extraction and cascading it with neural networks classifier is presented. In order to derive better use of face recognition system for faster and better surveillance, analysis is carried out which provides a greater knowledge on the entire process and clarifies on various parameters effecting the system. Most popular Single-Layer Neural Networks such as generalized regression neural network (GRNN) and probabilistic neural network (PNN) are used with different subspace methods to provide a distinguished analysis. The experimental results in this work have revealed that the combination of subspace method with neural networks has increased the robustness and speed of face recognition system. Performance analysis of the proposed model is carried out by conducting the experiments on three benchmarking databases such as ORl, Yale and Feret.

Keywords

Face recognition Eigen values Eigenfaces PCA KPCA GRNN PNN Recognition rate 

References

  1. 1.
    Kumar, K.: Artificial neural network based face detection using gabor feature extraction. Int. J. Adv. Technol. Eng. Res. (IJATER) 2, 220–225 (2012)Google Scholar
  2. 2.
    Revathy, N., Guhan, T.: Face recognition system using back propagation artificial neural network. Int. J. Adv. Eng. Technol. (IJAET) 3, 321–324 (2012)Google Scholar
  3. 3.
    Radha, V., Nallammal, N.: Neural network based face recognition using RBFN classifier. In: Proceedings of the World Congress on Engineering and Computer Science (WCECS), vol. 1 (2011)Google Scholar
  4. 4.
    Turk, M.A., Pentland, A.P.: Eigenfaces for recognition. J. Cognit. Neurosci. 3, 71–86 (1991)Google Scholar
  5. 5.
    Turk, M.A., Pentland, A.P.: Face recognition using eigenfaces. In: Proceedings of IEEE Computer Society Conference on Computer Vision and Pattern Recognition (1991)Google Scholar
  6. 6.
    Scholkopf, B., Smola, A., Müller, K.R.: Kernel principal component analysis. Adv. Kernel Methods Support Vector Learning, pp 327–352 (1999)Google Scholar
  7. 7.
    Belhumer, P.N., Hespanha, J.P., Kriegman, D.J.: Eigenfaces vs fisherfaces: recognition using class specific linear projection. IEEE Trans. Pattern Anal. Mach. Intell. 711–720 (1997)Google Scholar
  8. 8.
    Chaudhary, U., Mubarak, C.M., Rehman, A., Riyaz, A., Mazhar, S.: Face recognition using PCA-BPNN algorithm. Int. J. Modren Eng. Res. (IJMER), 2, 1366–1370 (2012)Google Scholar
  9. 9.
    Daramola, S.A., Odeghe, O.S.: Efficient face recognition system using artificial neural network. Int. J. Comput. Appl. 41(21), 12–15 (2012)Google Scholar
  10. 10.
    Specht, D.F.: A general regression neural network. IEEE Trans. Neural Networks 2(6), 568–576 (1991)CrossRefGoogle Scholar
  11. 11.
    Demuth, H.B., Beale, M.: Neural network toolbox for use with MATLAB Users Guide Version 4. Mathworks (2002)Google Scholar
  12. 12.
    Specht, D.F.: Probabilistic neural networks. IEEE Int. Conf. Neural Networks, pp. 525–532 (1990)Google Scholar
  13. 13.
    Beale, H., Hagan, M.T., Demuth, H.B.: Neural network toolbox users guide 2013a, Mathworks (2013)Google Scholar
  14. 14.
  15. 15.
  16. 16.
  17. 17.
    Sahoolizadeh, A.H., Heidari, B.Z., Dehghani, C.H.: A new face recognition method using PCA, LDA and neural network. Int. J. Electr. Electron. Eng. 2(5), 6–12 (2008)Google Scholar
  18. 18.
    Esbati, H., Shirazi, J.: Face recognition with PCA and KPCA using Elman neural network and SVM. Int. J. Electr. Electron. Eng. 5(10), 135–140 (2011)Google Scholar
  19. 19.
    Hoang, L.T.: Applying artificial neural networks for face recognition. In: Advances in Artificial Neural System, vol. 2011, Hindawi Publishing CorpGoogle Scholar

Copyright information

© Springer India 2016

Authors and Affiliations

  • E. V. Sudhanva
    • 1
  • V. N. Manjunath Aradhya
    • 2
  • C. Naveena
    • 3
  1. 1.Department of CSJain UniversityBangaloreIndia
  2. 2.Department of MCASri Jayachamarajendra College of EngineeringMysoreIndia
  3. 3.Department of CSEHKBK College of EngineeringBangaloreIndia

Personalised recommendations