Perceptual video hashing robust against geometric distortions

Abstract

In this paper, we propose a robust perceptual hashing algorithm by using video luminance histogram in shape. The underlying robustness principles are based on three main aspects: 1) Since the histogram is independent of position of a pixel, the algorithm is resistant to geometric deformations; 2) the hash is extracted from the spatial Gaussian-filtering low-frequency component for those common video processing operations such as noise corruption, low-pass filtering, lossy compression, etc.; 3) a temporal Gaussian-filtering operation is designed so that the hash is resistant 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 can provide satisfactory robustness and uniqueness.