Face Identification using Back-Propagation Adaptive Multiwavenet | ||
| Journal of Engineering | ||
| Article 1, Volume 18, Issue 3, March 2012, Pages 392-402 | ||
| Authors | ||
| Nuha Abdul Sahib Alwan; Ali Ibrahim Abbas; Waleed Ameen Mahmoud | ||
| Abstract | ||
| Face Identification is an important research topic in the field of computer vision and pattern recognition and has become a very active research area in recent decades. Recently multiwavelet-based neural networks (multiwavenets) have been used for function approximation and recognition, but to our best knowledge it has not been used for face Identification. This paper presents a novel approach for the Identification of human faces using Back-Propagation Adaptive Multiwavenet. The proposed multiwavenet has a structure similar to a multi-layer perceptron (MLP) neural network with three layers, but the activation function of hidden layer is replaced with multiscaling functions. In experiments performed on the ORL face database it achieved a recognition rate of 97.75% in the presence of facial expression, lighting and pose variations. Results are compared with its wavelet-based counterpart where it obtained a recognition rate of 10.4%. The proposed multiwavenet demonstrated very good recognition rate in the presence of variations in facial expression, lighting and pose and outperformed its wavelet-based counterpart. | ||
| Keywords | ||
| Face Identification; multiwavelet neural network; Back; Propagation Adaptive Multiwavenet | ||
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