Video perceptual hashing using interframe similarity
Xuebing Zhou, Martin Schmücker, Christopher Leslie Brown · Publikationsdatenbank der Fraunhofer-Gesellschaft (Fraunhofer-Gesellschaft) · 2006
Automatic content identification and verification are required in numerous application scenarios.This can be achieved by perceptual hash functions. This article describes a general structure of video perceptual hashing. An algorithm based on interframe similarity is investigated. We analyze its performance and compare it with an algorithm that uses mean luminance. The proposed algorithm shows increased identification reliability with respect to robustness and receiver operating characteristics.