In this paper, we present a novel and effective feature extraction technique for face
recognition. The proposed technique incorporates a kernel trick with Graph Embedding and
the Fisher's criterion which we call it as Kernel Discriminant Embedding (KDE). The
proposed technique projects the original face samples onto a low dimensional subspace
such that the within-class face samples are minimized and the between-class face samples
are maximized based on Fisher's criterion. The implementation of kernel trick and Graph …