In this paper we present an evaluation study of decision fusion strategies for infrared (IR) and visible face recognition. Several decision fusion methods based on voting scheme (minimization, product and averaging) are discussed and experiments for various conditions of probe set are performed on two databases with paired IR and visible face imageries. The Eigenfaces and Fisherfaces classification techniques are used to extract the face features and the performance of fusion methods are discussed.