抗几何失真的视频Hashing算法研究

文中提出了一种基于视频灰度直方图形状的Hashing算法,能有效抵抗各种常见的几何失真和视频处理操作.算法的鲁棒性原理如下:1)由于直方图的形状与像素位置无关,故基于直方图的视频Hashing算法能有效抵抗各种常见的几何攻击;2)由于在计算Hashing前对视频帧进行了平滑预处理,故算法对加噪攻击、模糊滤波、有损压缩等处理操作有很好的鲁棒性;3)由于计算Hashing前在时间轴上进行了低通滤波预处理,故算法能抵抗帧率变化、帧丢失等时域同步攻击.实验结果表明,所提出的Hashing算法有良好的唯一性和鲁棒性能.

Perceptual video Hashing robust against geometric distortions

In this paper, we propose a robust perceptual hashing algorithm by using the shape of video luminance histogram. The underlying robustness principles are based on three main aspects: 1) since the histogram in shape does not depend on the exact position of a pixel, the algorithm is resistant to geometric deformations; 2) the hash is extracted from the spatial Gaussian-filtering low-frequency component against common video processing operations such as noise permutation, low-pass filtering and lossy compression; 3) temporal Gaussian- filtering operation is designed so that the hash is robust to temporal desynchronization operations, such as frame rate change and dropping. As a result, the hash function is robust to common geometric distortions and video processing operations. Experimental results show that the proposed hashing strategy provides satisfactory robustness and uniqueness.