4.6 Article

A low cost fragile watermarking scheme in H.264/AVC compressed domain

Journal

MULTIMEDIA TOOLS AND APPLICATIONS
Volume 72, Issue 3, Pages 2469-2495

Publisher

SPRINGER
DOI: 10.1007/s11042-013-1561-2

Keywords

H.264/AVC; Video watermarking; Intra/inter prediction mode; Discrete cosine transform; Content-authentication

Funding

  1. National Science Council [NSC101-2221-E-011-063-MY3]
  2. 111 Project [111-2-14]
  3. One Hundred Talents Program, Sichuan Province
  4. National Science Foundation of China [60902023, 61171096]
  5. Fundamental Research Funds for the Central Universities [SWJTU12CX093]

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H.264/AVC-based products have grown tremendously in social networks; issues of content-based authentication become increasingly important. This paper presents a blind fragile watermarking scheme for content-based H.264/AVC authentication, which enjoys high sensitivity to typical video attacks. A spatiotemporal analysis is exploited to guarantee a minimum impact on perceptual quality and bit-rate increment. The watermark features are extracted from intra/inter prediction modes of intra/inter macroblocks, constituting the content-based Message Authentication Code (MAC) which is embedded/extracted in a Group-of-Pictures GOP-based fashion utilizing the syntactic elements of the Network Application Layer (NAL) units from the compressed bitstream. It's unnecessary to fully decode a compressed bitstream before the embedding or detection processes. A content-based key is generated to control fragile watermark generation, embedding, extraction, and verification algorithms. Additionally, fragility is ensured by selecting the last nonzero quantized ac residuals for watermark embedding. The embedded watermark can be detected and verified by means of partially decoding intra/inter prediction modes from syntactic elements of the bitstream without the prior knowledge of the original video or complete decoding. Experiment results demonstrate that the performance of the proposed scheme is excellent in terms of bit-rate and perceptual quality. Furthermore, various types of content-preserving and/or content-changing attacks can be detected efficiently.

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