Author/Authors :
A. Aziz, Khairul Azha bin Universiti Teknikal Malaysia Melaka - Faculty of Electronic Engineering and Computer Engineering, Malaysia , Hamzah, Rostam Affendi Universiti Teknikal Malaysia Melaka (UTeM) - Faculty of Electronics Computer Engineering, Malaysia , Abdullah, Shahrum Shah Universiti Teknologi Malaysia (UTM) - Faculty of Electrical Engineering, Malaysia , Jahari, Ahmad Nizam Universiti Teknikal Malaysia Melaka (UTeM) - Faculty of Electronics and Computer Engineering, Malaysia , Damni, Siti Dhamirah ‘Izzati Universiti Teknikal Malaysia Melaka (UTeM) - Faculty of Electronics and Computer Engineering, Malaysia
Abstract :
This paper presents face recognition using spread fixed spread radial basis function neural network for security system. The face recognition system can be applied to security system such as door lock system etc. Acquired image will be going through image processing process. General preprocessing approach is use for normalizing the image. Radial Basis Function Neural Network is use for face recognition and Support Vector Machine is used as the face detector. RBF Neural Networks offer several advantages compared to other neural network architecture such as they can be trained using fast two stages training algorithm and the network possesses the property of best approximation. The output of the network can be optimized by setting suitable values of the center and spread of the RBF but in this paper fixed spread is used as there is only one train image for every user and to limit the output value.
Keywords :
component , Face recognition, Radial Basis Function Neural Network, Image Processing.
