Sunil Lee and Chang D. Yoo: Video Fingerprinting Based on Centroids of Gradient Orientations



Fingerprints are feature vectors that can uniquely characterize the video signal. The goal of a video fingerprinting system is to judge whether two videos have the same contents by measuring distance between fingerprints extracted from the videos. In this paper, a novel video fingerprinting method based on the centroids of gradient orientations is proposed. The centroid of gradient orientations is chosen due to its reliability and robustness against common video processing steps. A threshold used to reliably determine a fingerprint match is theoretically derived, and its validity is experimentally verified. The experimental results show that the proposed fingerprint is not only pairwise independent but also robust against common video processing steps.