TUNED BACTERIAL FORAGING ALGORITHM FOR FACE RECOGNITION TECHNIQUE

Authors

  • M.Blessy Queen Mary Assistnat Professor, Department of Information Technology, Coimbatore.
  • N.Nirmal Singh Assistnat Professor, Department of Information Technology, Coimbatore.

DOI:

https://doi.org/10.24297/jac.v12i24.1320

Keywords:

Bacterial Foraging, Face Recognition, Support Vector Machines, Radial Basis Functions, Principal Component Analysis.

Abstract

This article presents an efficient face recognition technique with the optimal selection of components through Bacterial Foraging Algorithm (BFA) based on Support Vector Machines (SVM). The shortcomings in the field of recognition are non-linear and accuracy which has been considered to resolve by an effective classifier. SVMs are kernel machines which uses minimal optimization algorithm for solving non-linear problems and it has a good perspective in face recognition application. This paper also analyzes how the functionality can be improved by choosing optimum parameters. Experimental results reveal that tuned BFA based SVM trained by RBF neural network lends itself to higher face recognition accuracy than normal SVM, BFA and RBF. Therefore the proposed method trained by RBF is of surpassing that of the existing techniques in face recognition. This Chemical journal is preferred because of Bacterial Foraging process of algorithm, viz chemical correlation and bacterium in Image processing.

Downloads

Download data is not yet available.

References

[1] Te-Hsiu Sun and Fang-Chih Tien, “Using Back propagation neural network for face recognition with 2D+3D hybrid information”, Expert systems with Applications 35, 361-372, 2008.
[2] Julia Fernandez-Getino Garcia, Luis Rojo-Alvarez, J.: “Support Vector Machines for robust channel estimation”, IEEE Signal Process Lett., vol.13, no.7, pp 397-400, 2006
[3] Kevin M.Passino,”Biomimicry of Bacterial Foraging for distributed Optimization and Control”, in Proc. IEEE Control Systems Mag., pp. 52-67, 2002.
[4] Rutuparna Panda, Manoj Kumar Naik and B.K.Panigrahi,”Face Recognition using Bacterial foraging Strategy”, Swarm and Evolutionary Computation, 2011.
[5] B.scholkopf, K.Sung, C.Burges, F.Girosi, P.Niyogi, T.Poggio and V.Vapnik,”Comparing support vector machines with Gaussian kernels to radial basis function classifiers”, IEEE Trans. Signal Process.,vol. 45, no.11, pp. 2758-2765, Nov. 1997.
[6] Irene Kotcia and Ioannis Pitas,”Facial Expression Recognition in Image Sequences using Geometric Deformation Features and Support Vector Machines”,IEEE Trans. Image Processing, vol.16, no.1, pp. 172-187,2007.
[7] Meng Joo, Shiqian Wu, Juwei Lu and Hock Lye Toh, ”Face Recognition with Radial Basis Function(RBF) neural networks”, IEEE Trans. Neural Networks, vol.13, no.3, pp. 697-710, 2002.
[8] Available [Online]: http://www.cam-orl.co.uk/facedatabase.html
Author’ biography
M.Mlessy Queen Mary is working as an Assistant Professor at Government college of Technology, Coimbatore. She had her post graduation at Government College of Engineering, Tirunelveli. Her research areas are Artificial Intelligence, Image Processing and interdisciplinary research.
Dr.N.Nirmal Singh is working as professor and Head of the Department /ECE at VV College of Engineering. He has a vast experience in Research and has published various research publications. He has completed his Ph.D at Jadavpur University.

Downloads

Published

2016-12-20

How to Cite

Queen Mary, M., & Singh, N. (2016). TUNED BACTERIAL FORAGING ALGORITHM FOR FACE RECOGNITION TECHNIQUE. JOURNAL OF ADVANCES IN CHEMISTRY, 12(24), 5541–5546. https://doi.org/10.24297/jac.v12i24.1320

Issue

Vol. 12 No. 24 (2016)

Section

Articles

License

Creative Commons License All articles published in Journal of Advances in Linguistics are licensed under a Creative Commons Attribution 4.0 International License.