A modified discriminant sparse representation method for face recognition
Taif Alobaidi, Wasfy B. Mikhael · 2018
Recently, a new discriminative sparse representation method for robust face recognition that uses ℓ2-norm regularization was reported. In this paper, direct data-driven calculation of the balance parameter used in the objective function is presented. The modified system preserves the advantages of the original method while improving the recognition accuracy and making the system more automated, i.e., less dependent on the user's input. Extensive simulations are performed on six face databases, namely, ORL, YALE, FERET, FEI, Cropped AR, and Georgia Tech. Sample results are given demonstrating the properties of the modified system.