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Proceedings Paper

Multimedia data authentication in wavelet domain
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Paper Abstract

With the wide application of multimedia data, multimedia content protection becomes urgent. Till now, various means have been reported, which can be classified into several types according to their functionalities, such as data encryption, digital watermarking or data authentication. They are used to protect multimedia data's confidentiality, ownership and integrity, respectively. For multimedia data authentication, some approaches have been proposed. In this paper, a wavelet-based multi-feature semi-fragile authentication scheme is proposed. According to the approximation component and the energy relationship between the subbands of the detail component, global feature and local feature are both generated. Then, the global watermark and local watermark are generated from global feature and local feature, respectively. The watermarks are then embedded into the multimedia data themselves in the wavelet domain. Both the feature extraction and embedding processes are controlled by secret keys to improve the security of the proposed scheme. In the receiver end, the extracted watermark and the one generated from the received image are compared to determine the tampered location. A new authentication method is designed and it is proved valid in the experiments. This authentication scheme is robust to general compression, sensitive to cutting, pasting or modification, efficient in real-time operation, and secure for practical applications.

Paper Details

Date Published: 17 April 2006
PDF: 12 pages
Proc. SPIE 6247, Independent Component Analyses, Wavelets, Unsupervised Smart Sensors, and Neural Networks IV, 62470X (17 April 2006); doi: 10.1117/12.667206
Show Author Affiliations
Jinwei Wang, Nanjing Univ. of Science and Technology (China)
France Telecom Research and Development, Beijing (China)
Shiguo Lian, France Telecom Research and Development, Beijing (China)
Zhongxuan Liu, France Telecom Research and Development, Beijing (China)
Ren Zhen, France Telecom Research and Development, Beijing (China)
Yuewei Dai, Nanjing Univ. of Science and Technology (China)


Published in SPIE Proceedings Vol. 6247:
Independent Component Analyses, Wavelets, Unsupervised Smart Sensors, and Neural Networks IV
Harold H. Szu, Editor(s)

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