Identifying the type of modalities of the query image which can be of types visual, NIR, digital camera, web camera etc. have been assumed to be available before face matching. This leads to a major drawback in achieving fully automated heterogeneous face recognition as real world scenarios cannot be reflected. Therefore, modality identification is an important component of the heterogeneous face recognition system which is being overlooked by majority of the state-of-the-art methods. This component should be given similar attention when comparing with other face recognition modules identifying pose, gesture, camera source etc. In this paper inspired from sensor pattern noise (SPN) estimation based approaches, a novel image sharpening based modality pattern noise technique is proposed for modality identification. The proposed system has been evaluated on three challenging benchmarks of heterogeneous face databases. The proposed technique has produced outstanding results and will open new avenues of research for automated HFR methods in future.