Face recognition using discrete cosine transform and fisher linear discriminant

Abstract

In this paper, an efficient method for face recognition based on the Discrete Cosine Transform (DCT), Fisher Linear Discriminant (FLD) and classifier is presented. First, the dimensionality of the original face image is reduced using the DCT and illumination variations are alleviated by discarding the first few low-frequency DCT coefficients. FLD is applied to the selected DCT coefficients to discriminate the invariant facial features. The KNN classifier is used for the recognition of the faces using the features extracted from the FLD. Simulation results show that the proposed system achieves better performance with high training and high recognition rate as well as very good illumination robustness.