Face Recognition using Energy Probability in DCT Domain

In this paper, we propose a novel feature extraction method for face recognition. This method is based on discrete cosine transform (DCT), energy probability (EP), and linear discriminant analysis (LDA). We define an energy probability as magnitude of effective information. It is used to create a frequency mask in DCT domain. Our method consists of three steps. First, the spatial domain of face images is transformed into the frequency domain called DCT domain. Second, for energy probability is applied on DCT domain which acquires from face image, dimension reduction of data and optimization of valid information. At last, in order to obtain the most significant feature of face images, LDA is applied to the extracted data using frequency mask. Our experimental results show that the proposed method improves on the dimension reduction of feature space and the face recognition over the previously proposed methods