Face Recognition Using Discrete Tchebichef-Krawtchouk Transform

In this paper, a face recognition system based on Discrete Tchebichef-Krawtchouk Transform DTKT and Support Vector Machines SVMs is proposed. The objective of this paper is to present the following: (1) the mathematical and theoretical frameworks for the definition of the DTKT including transform equations that need to be addressed. (2) the DTKT features used in the classification of faces. (3) results of empirical tests that compare the representational capabilities of this transform with other types of discrete transforms such as Discrete Tchebichef transform DTT, discrete Krawtchouk Transform DKT, and Discrete Cosine transform DCT. The system is tested on a large number of faces collected from ORL and Yale face databases. Empirical results show that the proposed transform gives very good overall accuracy under clean and noisy conditions.