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A MV-Based Steganographic Algorithm for H.264/AVC without Distortion

Hongqiong Tang1, 2, Xiaoyuan Yang1, 2, *, Yingnan Zhang1, Ke Niu1, 2

1 Engineering University of PAP, Xi’an, 710086, China.
2 Key Laboratory of Network and Information Security under the PAP, Xi’an, 710086, China.

* Corresponding Author: Xiaoyuan Yang, Email: email.

Computers, Materials & Continua 2020, 63(3), 1205-1219. https://doi.org/10.32604/cmc.2020.010075

Abstract

H.264/AVC video is one of the most popular multimedia and has been widely used as the carriers of video steganography. In this paper, a novel motion vector (MV) based steganographic algorithm is proposed for the H.264/AVC compressed video without distortion. Four modules are introduced to eliminate the distortion caused by the modifications of motion vectors and guarantee the security of the algorithm. In the embedding block, the motion vector space encoding is used to embed a (2n+1)-ary notational number into an n-dimension vector composed of motion vectors generated from the selection block. Scrambling is adopted to disturb the order of steganographic carriers to improve the randomness of the carrier before the operation of embedding. The re-motion compensation (re-MC) block will re-construct the macroblock (MB) whose motion vectors have been modified by embedding block. System block plays the role of the generator for chaotic sequences and encryptor for secret data. Experimental results demonstrate that our proposed algorithm can achieve high embedding capacity without stego video visual quality distortion, it also presents good undetectability for existing MV-based steganalysis feature. Performance comparisons with other existing algorithms are provided to demonstrate the superiority of the proposed algorithm.

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Cite This Article

H. Tang, X. Yang, Y. Zhang and K. Niu, "A mv-based steganographic algorithm for h.264/avc without distortion," Computers, Materials & Continua, vol. 63, no.3, pp. 1205–1219, 2020. https://doi.org/10.32604/cmc.2020.010075



cc This work is licensed under a Creative Commons Attribution 4.0 International License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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