Learning Based No Reference Algorithm for Dropped Frame Identification in Uncompressed Video

For last many years video authentication and detection of tampering in a video are major challenges in the domain of digital video forensics. This paper presents detection of one of the temporal tampering (frame drop) under no reference mode of tampering detection. Inspirit of the scheme presented by Upadhyay and Singh, this paper extends the features to train the SVM classifier and accordingly classify frames of given video as tampered or non-tampered frames, i. e. detects the tampering of frame drop. Subsequently given video is classified as tampered or non-tampered video. The obtained results with enhanced features show significant improvement in classification accuracy.