A near-duplicate video retrieval method based on Zernike moments

In this paper, a near-duplicate video retrieval method developed based on invariant features was proposed. After shot change detection, Zernike moments are extracted from each key-frame of videos as invariant features. We obtain the key-frame similarity by computing the difference of Zernike moments between key-frames of the query and test videos. To achieve near-duplicate video retrieval, each key-frame is considered as an individual sensor and then evaluating all of key-frames is considered as multiple sensors. The results of key-frames are fused to obtain a better performance of near-duplicate video retrieval. The experimental results show that the proposed method can not only find the relevant videos effectively but also resist to the possible modifications such as re-scaling and logo insertion.