Video Hashing Algorithm With Weighted Matching Based on Visual Saliency
Jiande Sun, Jing Wang, Jie Zhang, Xiushan Nie, Ju Liu · IEEE Signal Processing Letters · 2012
In this letter, a novel video hashing algorithm is proposed, in which the weighted hash matching is defined in video hashing for the first time. In the proposed algorithm, the video hash is generated based on the ordinal feature derived from the temporally informative representation image (TIRI). At the same time the representative saliency map (RSM) is constructed by the visual saliency maps in video segments, and it generates the hash weights for hash matching. During hash matching, the traditional bit error rate (BER) is weighted with hash weights to form the weighted error rate (WER). WER is used to measure the similarity between different hashes. Experiments on different kinds of videos with different kinds of attacks verify the robustness and discrimination of the proposed algorithm.