An attack invariant scheme for content-based video copy detection

Due to the advancement in the field of multimedia technology and communication, it has become easier to access, store, and edit video data. Easy manipulation of video data and its rapid distribution have made content-based video copy detection (CBVCD) an active area of research. In a CBVCD system, reference video sequence and query sequence are compared to detect whether the query video sequence is a copy of reference video sequence. Thus, the generation of fingerprint of a video sequence and sequence matching technique are the core tasks of such system. In order to evade such detection process, a copied version may undergo different kinds of transformations like photometric and post-production attack. So the detection system must be robust enough against such attacks. In this work, fingerprint is generated from the sub-bands of wavelet decomposed intensity image and localized intensity gradient histograms of low sub-band. The fingerprint thus obtained reflects considerable discriminating capability and robustness against the attacks. Furthermore, to cope up with the attacks, we have adopted simple pre-processing technique, which enhances the robustness of the system further. A robust sequence matching technique based on multivariate Wald-Wolfowitz test is proposed here. An experiment has been carried out with a database consisting of distinct 642 shots and 1,485 query sequences representing different attacks. Proposed methodology achieves high copy detection rate (99.39 %) and very low false alarm rate (0.14 %) and performs better than other spatio-temporal measure based systems.