This paper proposes a method to address issues regarding uncontrolled conditions in face recognition. This method extracts affecting factor from the test sample utilizing mask projection. Current methods remove occlusion from the test sample and reconstruct it. Unlike these methods, the proposed method tries to add extracted occlusion to all normal training samples and compares the test sample with all synthetic affected training samples. The method has been applied for multi-factor authentication/ verification based on face biometrics. Obtained results indicate high accuracy, comparable to the best sparse method, in the lake of sufficient training samples for each class(single sample classes).