A PCA-based Face Recognition Method by Applying Fast Fourier Transform in Pre-processing

Principal Component Analysis (PCA) is a well-studied method in face recognition. Noticing that few researches focus on pre-processing of images, which will also improve the performance of feature extraction of PCA algorithm, we present an improved approach of PCA based face recognition algorithm using Fast Fourier Transform (FFT). In our method, FFT is presented as a method to combine amplitude spectrum of one image with phase spectrum of another image as a mixed image. PCA is applied to do feature extraction and a kernel SVM is harnessed as a classifier. To test and evaluate the performance of the proposed approach, a series of experiments are performed on Yale face database A. The experimental results show that our proposed method is encouraging.