Spatio–Temporal Transform Based Video Hashing

Identification and verification of a video clip via its fingerprint find applications in video browsing, database search and security. For this purpose, the video sequence must be collapsed into a short fingerprint using a robust hash function based on signal processing operations. We propose two robust hash algorithms for video based both on the discrete cosine transform (DCT), one on the classical basis set and the other on a novel randomized basis set (RBT). The robustness and randomness properties of the proposed hash functions are investigated in detail. It is found that these hash functions are resistant to signal processing and transmission impairments, and therefore can be instrumental in building database search, broadcast monitoring and watermarking applications for video. The DCT hash is more robust, but lacks security aspect, as it is easy to find different video clips with the same hash value. The RBT based hash, being secret key based, does not allow this and is more secure at the cost of a slight loss in the receiver operating curves