Design of Portable Security System Using Face Recognition with Back-Propagation Algorithm and MATLAB

  • M. Hareesh Babu
  • M. Bala Naga Bhushanamu
  • B. Benarji
  • M. Purnachandra Rao
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 324)


In our globally connected world, threats from various aspects are going at an alarming rate. These are controlling with different security systems such as metal detector, closed circuit cameras, and scanning systems. All these aids are meant to recognize and identify the explosives and others weapons. Here, it is more important to identify the particular person or persons, who were planning to distract the society or particular event. This paper is aimed to design that to control the threats by identifying the suspected people by a simple face recognition technique using simple PC or laptop with the help of scientific software MATLAB and its neural network tool box. In general, all major events are fully securitized with well-developed protection systems but only problem with non-major and small events, where security systems are matter of financial issues. So, militants and other destroyers are taking advantage of these situations and creating a panic and terror situations. This paper is also designed like that a PC or laptop with camera can be a face recognition system to identify the suspected peoples and most wanted criminal. By recognizing the people, we can mostly avoid the threats from these people and dangerous situations. Neural network is a science that has been extensively applied to numerous pattern recognition problems such as character recognition, object recognition, and face recognition, where this paper has programmed for face recognition with the back-propagation algorithm and simulated with the software MATLAB and its neural network tool box. Here, the back propagation plays the central operation role to get the key features were extracted from the picture for training the network. Since the major role of the project is mainly focusing on the training of the neural network, already extracted key features of the person’s image from the database were taken for training the back-propagation network. Here, we have taken 7 input units, 6 hidden units, and 4 output units contained back-propagation network. The output unit, 4 output units, generates the 4-bit output which gives the person identity.


Security Back-propagation Face recognition Neural network Images MATLAB Data learning rate Weight Train 



We thank to our beloved Guide and Head of the Department Prof. M. Purnachanra Rao, who gave us such an opportunity to work on NEURAL NETWORK, ARTIFICIAL INTELLIGENCE, and MATLAB SOFTWARE and his assistance on our presentation.


  1. 1.
    J.R. Anderon, Cognitive psychology and its implications, 2nd edn. (Freeman, San Francisco, 1985)Google Scholar
  2. 2.
    D.H. Ballard, Parameter nets. Artif. Intell 22(3), 235–267 (1984)CrossRefGoogle Scholar
  3. 3.
    E.A. Feigenbaum, A. Barr, P.R. Cohen (eds) The Handbook of Artificial Intelligence (Addison-Wesley, New York, 1989)Google Scholar
  4. 4.
    M.A. Eshera, K.S. Fu, A graph distance measure for image analysis. IEEE Trans. syst. Man Cybern. SMC 14(3)Google Scholar
  5. 5.
    K.S. Fu, Sequential methods in pattern recognition and matching of pictorial structures. IEEE Trans. Comput (1968)Google Scholar
  6. 6.
    J.L. Kolodener, Reconstructive memory: a computer model. Cogn. Sci. 7(4), 281–328 (1983)CrossRefGoogle Scholar

Copyright information

© Springer India 2015

Authors and Affiliations

  • M. Hareesh Babu
    • 1
  • M. Bala Naga Bhushanamu
    • 1
  • B. Benarji
    • 2
  • M. Purnachandra Rao
    • 1
  1. 1.Department of Systems DesignAndhra UniversityVisakhapatnamIndia
  2. 2.Department of Electronics and CommunicationAndhra UniversityVisakhapatnamIndia

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