Abstract: Linear Discriminant Analysis(LDA) is one of the classical and popular methods used for feature extraction. In this paper, a new algorithm called Symmetrical LDA(SLDA) based on frontal facial symmetry is proposed. This algorithm is based on the theory of function decomposition and mirror symmetry. In the algorithm, mirror transform is introduced. Original face samples are decomposed into even symmetrical images and odd symmetrical ones. Even/odd symmetrical discriminant features are extracted from the corresponding samples respectively. Both theoretical analysis and experimental results demonstrate this algorithm not only enlarges the number of training samples, but also remarkably improves the recognition rates.
Symmetrical Linear Discriminant Analysis(SLDA)