An improved algorithm for face recognition using wavelet and facial parameters
Kanchan Singh, Ashok K. Sinha · 2010
In this paper, the problem of face recognition in still color images is addressed. An improved algorithm for face recognition is proposed here. The algorithm comprises of designing a feature vector which has discrete wavelet coefficients of the face and, a coefficient representing parameters of the face. Global features of the face are captured by wavelet coefficients and the local feature of the face is captured by facial parameter. The coefficients of the feature vector are used as inputs to the back-propagation architecture of the neural network. The network is trained for different images in the database. The proposed algorithm has been tested on various real images and its performance is found to be quite satisfactory when compared with the performance of conventional methods of face recognition such as the Eigen-face method.