Face recognition based on singular-value feature vectors

Automatic human face recognition is a difficult but significant problem. A method for face recognition based on singular-value feature vectors is discussed. Three algorithms of face recognition based on singular-value feature vectors are proposed. These algorithms are face recognition using principal component analysis based on singular-value feature vectors, face recognition by Fisher linear discriminant analysis based on singular-value feature vectors, and face recognition using the discriminant Karhunen Loeve (DKL) transform based on singular-value feature vectors. Experimental results show that face recognition based on singular-value feature vectors is effective.