A Novel Approach for Face Recognition System Based on Rotational Invariant Transform and Artificial Neural Networks


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Abstract


Face detection is the first step in the face recognition system. The Neural network as well as Gabor wavelet based face detection is proposed in this paper. The proposed system applies neural network algorithm to make the slanting face upright and Gabor wavelet is used to extract the invariable features from the selected window. The principal component analysis is applied to identify the person from the data base. The Proposed system gives very high detection efficiency with low number of false alarms. We have shown the results on different test sets with different degrees of variability of the face patterns. In this paper, we present a new approach for determining the orientation of face in the selected window and then use this information to rotate the face upright
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Keywords


Face Detection; Artificial Neural Networks; Gabor Wavelets; Principal Component Analysis; Machine Vision

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References


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