Video hashing is a useful technique of many multimedia systems, such as video copy detection, video authentication, tampering localization, video retrieval, and anti-privacy search. In this paper, we propose a novel video hashing with secondary frames and invariant moments. An important contribution is the secondary frame construction with 3D discrete wavelet transform, which can reach initial data compression and robustness against noise and compression. In addition, since invariant moments are robust and discriminative features, hash generation based on invariant moments extracted from secondary frames can ensure good classification of the proposed video hashing. Extensive experiments on 8300 videos are conducted to validate efficiency of the proposed video hashing. The results show that the proposed video hashing can resist many digital operations and has good discrimination. Performance comparisons with some state-of-the-art algorithms illustrate that the proposed video hashing outperforms the compared algorithms in classification in terms of receiver operating characteristic results.

视频散列是许多多媒体系统的有用技术，例如视频复制检测、视频认证、篡改定位、视频检索和反隐私搜索。在本文中，我们提出了一种具有辅助帧和不变矩的新型视频散列。一个重要的贡献是具有 3D 离散小波变换的辅助框架构造，它可以达到初始数据压缩和抗噪声和压缩的鲁棒性。此外，由于不变矩具有鲁棒性和判别性特征，基于从副帧中提取的不变矩的哈希生成可以确保所提出的视频哈希的良好分类。对 8300 个视频进行了广泛的实验，以验证所提出的视频散列的效率。结果表明，所提出的视频散列可以抵抗许多数字操作，并且具有良好的辨别力。与一些最先进算法的性能比较表明，在接收器操作特征结果方面，所提出的视频散列在分类方面优于比较算法。