Perceptual Video Hashing for Content Identification and Authentication

Khelifi, Fouad and Bouridane, Ahmed (2017) Perceptual Video Hashing for Content Identification and Authentication. IEEE Transactions on Circuits and Systems for Video Technology. ISSN 1051-8215 (In Press)

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Official URL: https://doi.org/10.1109/TCSVT.2017.2776159

Abstract

Perceptual hashing has been broadly used in the literature to identify similar contents for video copy detection. It has also been adopted to detect malicious manipulations for video authentication. However, targeting both applications with a single system using the same hash would be highly desirable as this saves the storage space and reduces the computational complexity. This paper proposes a perceptual video hashing system for content identification and authentication. The objective is to design a hash extraction technique that can withstand signal processing operations on one hand and detect malicious attacks on the other hand. The proposed system relies on a new signal calibration technique for extracting the hash using the discrete cosine transform (DCT) and the discrete sine transform (DST). This consists of determining the number of samples, called the normalizing shift, that is required for shifting a digital signal so that the shifted version matches a certain pattern according to DCT/DST coefficients. The rationale for the calibration idea is that the normalizing shift resists signal processing operations while it exhibits sensitivity to local tampering (i.e., replacing a small portion of the signal with a different one). While the same hash serves both applications, two different similarity measures have been proposed for video identification and authentication, respectively. Through intensive experiments with various types of video distortions and manipulations, the proposed system has been shown to outperform related state-of-the art video hashing techniques in terms of identification and authentication with the advantageous ability to locate tampered regions.

Item Type: Article
Uncontrolled Keywords: Video hashing, Robustness, Identification, Authentication, Forgery detection
Subjects: G900 Others in Mathematical and Computing Sciences
Department: Faculties > Engineering and Environment > Computer and Information Sciences
Depositing User: Becky Skoyles
Date Deposited: 15 Dec 2017 15:37
Last Modified: 15 Dec 2017 15:38
URI: http://nrl.northumbria.ac.uk/id/eprint/32873

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