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Face Recognition using Artificial Neural Network

S Endeshaw, K Raimond


Face recognition (FR) is one of the biometric methods to identify the individuals by the features of face. Two Face Recognition Systems (FRS) based on Artificial Neural Network (ANN) have been proposed in this paper based on feature extraction techniques. In the first system, Principal Component Analysis (PCA) has been used to extract the features from face images and classify them using ANN. In the second system, combination of Gabor Filter (GF) and PCA have been used for feature extraction and ANN for classification. The influence of different ANN parameters also has been studied in this work. Experiments have been carried out by using Olivetti Research Laboratory (ORL) face database. The results confirmed the feasibility of the methodologies followed in this work. Further, the systems performed very efficiently when subjected to new unseen images with a false rejection rate of 0% during testing.

Keywords: Face Recognition, Biometrics, Artificial Neural Network, Gabor Filter, Principal Component Analysis.

AJOL African Journals Online