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Improved Reversible Data Hiding Scheme Based on AMBTC Compression Technique

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Industrial IoT Technologies and Applications (Industrial IoT 2017)

Abstract

As the compression technique spread on the Internet, data hiding combining with compression techniques is a hot property in recent years. In this paper, a reversible data hiding (RDH) scheme for Absolute Moment Block Truncation Coding (AMBTC) compressed image is proposed. In the proposed scheme, according to the four kinds of situations which the secret data combine with the bitmap value, we provide some rules to embed data by use the mean value and the absolute moment. Experimental results and analysis demonstrate that, the proposed method can achieve high capacity with low distortion. Besides, the proposed method is very simple and can be easily applied to real-time transmission due to its lower computational complexity.

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Acknowledgments

This research work is partly supported by the National Natural Science Foundation of China (61502009, 61671018, 61472002), China Postdoctoral Science Foundation (2016M591650), Anhui Provincial Natural Science Foundation (1508085SQF216), Key Program for Excellent Young Talents in Colleges and Universities of Anhui Province (gxyqZD2016011), Quality Engineering Program for Colleges and Universities in Anhui Province (2015jyxm042) and Undergraduates Training Foundation of Anhui University (J10118515631, J18520229).

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Correspondence to Zhaoxia Yin .

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© 2017 ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering

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Sun, S., Yin, Z., Tang, J., Luo, B. (2017). Improved Reversible Data Hiding Scheme Based on AMBTC Compression Technique. In: Chen, F., Luo, Y. (eds) Industrial IoT Technologies and Applications. Industrial IoT 2017. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 202. Springer, Cham. https://doi.org/10.1007/978-3-319-60753-5_12

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  • DOI: https://doi.org/10.1007/978-3-319-60753-5_12

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-60752-8

  • Online ISBN: 978-3-319-60753-5

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