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Robust image hashing with tampering recovery capability via low-rank and sparse representation

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Abstract

Multimedia hash is an effective solution to image authentication and tampering identification. We propose an image hashing scheme based on Low-Rank and Sparse Representation. Low-Rank Representation is applied to the attacked image to obtain image feature matrix and error matrix. Then the properties of dimension reduction and tampering recovery inherent in Low-Rank Representation and Compressive Sensing are exploited for hash design. We use Compressive Sensing to recover the primary feature of image. Furthermore we use Low-Rank Representation to recover the image from tampering. Thanks to the error correction and structure recover capabilities of Low-Rank Representation, experiments reveal that our proposed hashing scheme is robust to content preserving modifications and has better image recovery performance compared with existing hashing schemes.

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Acknowledgments

The work was supported by Chongqing Youth Innovative Talent Project (Grant No. cstc2013kjrc-qnrc40004), the open research fund of Chongqing Key Laboratory of Emergency Communications (Grant No. CQKLEC, 20140504), Project Nos. 106112013CDJZR180005, 106112014CDJZR185501, XDJK2015C077 supported by the Fundamental Research Funds for the Central Universities, the Natural Science Foundation of Chongqing Science and Technology Commission (Grant Nos. cstc2013jcyjA40017, cstc2013jjB40009) and the National Natural Science Foundation of China (Grant Nos. 61173178, 61272043, 61302161, 61472464).

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Authors and Affiliations

  1. Key Laboratory of Dependable Service Computing in Cyber Physical Society (Chongqing University) of Ministry of Education, College of Computer Science, Chongqing University, Chongqing, 400044, China

    Hong Liu & Di Xiao

  2. College of Software Engineering, Chongqing University of Posts and Telecommunications, Chongqing, 400065, China

    Hong Liu & Yunpeng Xiao

  3. School of Electronics and Information Engineering, Southwest University, Chongqing, 400715, China

    Yushu Zhang

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  1. Hong Liu
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  2. Di Xiao
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  3. Yunpeng Xiao
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  4. Yushu Zhang
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Correspondence to Di Xiao.

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Liu, H., Xiao, D., Xiao, Y. et al. Robust image hashing with tampering recovery capability via low-rank and sparse representation. Multimed Tools Appl 75, 7681–7696 (2016). https://doi.org/10.1007/s11042-015-2688-0

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  • DOI: https://doi.org/10.1007/s11042-015-2688-0

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