Face Recognition Model Using Back Propagation

  • Authors

    • R Aswini Priyanka
    • C Ashwitha
    • R Arun Chakravarthi
    • R Prakash
    2018-09-01
    https://doi.org/10.14419/ijet.v7i3.34.18973
  • Face Recognition, Deep learning, Convolutional Neural Network (CNN), Back Propagation Neural Network (BPNN).

  • In scientific world, Face recognition becomes an important research topic. The face identification system is an application capable of verifying a human face from a live videos or digital images. One of the best methods is to compare the particular facial attributes of a person with the images and its database. It is widely used in biometrics and security systems. Back in old days, face identification was a challenging concept. Because of the variations in viewpoint and facial expression, the deep learning neural network came into the technology stack it’s been very easy to detect and recognize the faces. The efficiency has increased dramatically. In this paper, ORL database is about the ten images of forty people helps to evaluate our methodology. We use the concept of Back Propagation Neural Network (BPNN) in deep learning model is to recognize the faces and increase the efficiency of the model compared to previously existing face recognition models.

     

     

     

  • References

    1. [1] “ Face Recognition system in Android Using Neural Networks†Stoimen Stoimenov, Georgi T. Tsenov, Valeri M. Mladenov, Senior Member, IEEE ,13th Symposium on Neural Networks and Applications (NEUREL) SAVA Center, Belgrade, Serbia, November 22-24, 2016.

      [2] N. Revathy, T. Guhan, “Face recognition system using back propagation artificial neural networksâ€, International Journal of Advanced Engineering Technology, vol.3, no. 1, 2012.

      [3] A. K. Jain, B. Klare and P. Unsang, “Face recognition: Some challenges in forensics,†in Proc. IEEE International Conference on Automatic Face and Gesture Recognition and Workshops, March 21-25, 2011, pp. 726-733.

      [4] Ms. Varsha Gupta and Mr. Dipesh Sharma, “A Study of Various Face Detection Methodsâ€, International Journal of Advanced Research in Computer and Communication Engineering), vol.3, no. 5, May 2014.

      [5] Maria De Marsico, Michele Nappi, Daniel Riccio and Harry Wechsler, “Robust Face Recognition for Uncontrolled Pose and Illumination Changes†IEEE Transaction on Systems, Man and Cybernetics, vol.43,No.1,Jan 2013 .

      [6] Prachi Agarwal, Naveen Prakash, “An Efficient Back Propagation Neural Network Based Face Recognition System Using Haar Wavelet Transform and PCA†International Journal of Computer Science and Mobile Computing, vol.2, no.5,pg.386 – 395, May 2013.

      [7] Dibberi, 4 Jan 2005, “Back propagationâ€, https ://en.Wikipedia.org/wiki/ Back propagation, 20 September 2015.

      [8] “Artificial Neural Networksâ€, https://en.wikipedia.org/wiki/Artificial_neural_network.

      [9] Michael Nielsen, Jan 2016, “Neural networks and deep learningâ€, http://neuralnetworksanddeeplearning.com/chap2.html.

      [10] “Neural Network Design†(2nd Edition) Solutions Manual by Hagan.

      [11] A. HosseinSahoolizadeh, B. ZarghamHeidari and C.HamidDehghani, “A New Face Recognition Method using PCA, LDA and Neural Networkâ€, IEEE 2:8 2008.

      [12] David Monzo, Alberto Albiol, Antonio Albiol, Jose M.Mossi, “A Comparative Study of facial landmark localization methods for Face Recognition using HOG descriptorsâ€, Proceedings of IEEE 2010.

      [13] B. F. Klare, M. J. Burge, J. C. Klontz, R. W. V. Bruegge, and A. K. Jain, “Face recognition performance: Role of demographic information,†IEEE Transactions on Information Forensics and Security, vol. 7, no. 6, pp. 1789-1801, Dec. 2012.

      [14] S. Haykin, "Neural Networks: a comprehensive foundation", 2nd Edition, Prentice Hall, 1999.

      [15] V. D. M. Nhat and S. Lee. “An improvement on PCA algorithm for face recognition,†in Advances in Neural Networks, Springer Berlin Heidelberg, 2005, pp. 1016-1021.

      [16] Anil K. Jain, “Face Recognition: Some Challenges in Forensicsâ€, IEEE International Conference On Automatic Face and Gesture Recognition, pp 726-733, 2011.

      [17] R.Rojas,â€The back propagation algorithmâ€, Springer-Verlag, Neural networks, pp 149-182 1996.

  • Downloads

  • How to Cite

    Aswini Priyanka, R., Ashwitha, C., Arun Chakravarthi, R., & Prakash, R. (2018). Face Recognition Model Using Back Propagation. International Journal of Engineering & Technology, 7(3.34), 237-240. https://doi.org/10.14419/ijet.v7i3.34.18973