Abstract
This paper presents an effective methodology for motion vector-based video steganography. The main principle is to design a suitable distortion function expressing the embedding impact on motion vectors by exploiting the spatial-temporal correlation based on the framework of minimal-distortion steganography. Two factors are considered in the proposed distortion function, which are the statistical distribution change (SDC) of motion vectors in spatial-temporal domain and the prediction error change (PEC) caused by modifying the motion vectors. The practical embedding algorithm is implemented using syndrome-trellis codes (STCs). Experimental results show that the proposed method can enhance the security performance significantly compared with other existing motion vector-based video steganographic approaches, while obtaining the higher video coding quality as well.
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Notes
1 The video sequence can be a series of raw images or a series of decompressed images obtaining from the coded bit stream.
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Acknowledgments
This work was supported in part by the Natural Science Foundation of China under Grant 61170234 and Grant 60803155, and in part by the Strategic Priority Research Program of the Chinese Academy of Sciences under Grant XDA06030601.
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Yao, Y., Zhang, W., Yu, N. et al. Defining embedding distortion for motion vector-based video steganography. Multimed Tools Appl 74, 11163–11186 (2015). https://doi.org/10.1007/s11042-014-2223-8
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DOI: https://doi.org/10.1007/s11042-014-2223-8