Different Decision Fusion Methods for Modular Common Vector Approach

Abstract

The partial occlusions in the face image negatively affect the performance of the face recognition system. Modular versions of some methods are used to overcome this problem. Modular Common Vector Approach(MCVA) was successfully applied partial occlusion problem. In this work, we apply some well-known decision fusion methods (product rule, borda count, and majority voting) to the decision stage of MCVA approach to increase the performance. Several face recognition experiments conducted on AR face database provide promising results.