KLPCCA Based on Features Fusion and Application in Facial Recognition

With regard to the high dimensional and small sample facial feature, this paper introduced the Kernel and Canonical Correlation Analysis (CCA) into the Locality Preserving Projections (LPP) algorithm and proposed a new face recognition algorithm based on the Kernel Base Locality Preserving Canonical Correlation Analysis (KLPCCA) with the derivation process. According to this algorithm, first use CCA to extract nonlinear information of a face image, and then make a linear mapping through LPP, at last conduct the calculation process taking into consideration of kernel and other data obtained before, so as to carry out the face recognition more accurately and simply.