Abstract-This paper aims to effectively recognize human faces from images, which is an important problem in the multimedia information process. After analyzing the related research works, the framework of the face recognition system is illustrated as first, which contains the training process and the testing process. Particularly, the improved PCA algorithm is use in the feature extraction module. The main innovations of this paper lie in that, in the improved PCA, we utilize a radial basis function to construct a kernel matrix by computing the distance of two different vectors, which are calculated by the parameter of 2-norm exponential. Afterwards, human faces can be recognized by computing the distance of test image and the training images by the nearest neighbor classifier, of which the cosine distance is utilized. Finally, experiments are conducted to make performance evaluation. Compared with the existing face recognition methods, the proposed scheme is more effective in recognizing human faces with high efficiency.
Furthermore, in the same year, Yue REF proposed to use a radial basis function to construct a kernel matrix by computing the distance of two different vectors calculated by the parameter of 2-norm exponential and then applying a cosine distance to calculate the matching distance leading to higher recognition rate over a traditional PCA.
Human Face Recognition based on Improved PCA Algorithm
Journal of Multimedia
Journal of Multimedia
Computer Science