Motivated by the advantages of Trace transform and discrete cosine transform (DCT), an integrated face representation is proposed. In order to construct the discriminatory facial features, Trace transforms are first calculated through various functionals. Then the proposed feature fusion scheme is implemented to DCT filtered Trace transforms to create new Trace features. After extracting the features, Support Vector Machines are employed for training and testing. Experimental results on benchmark face database reveal that proposed facial features are robust and efficient.