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Multimedia Systems

, Volume 25, Issue 5, pp 551–563 | Cite as

Cloud image watermarking: high quality data hiding and blind decoding scheme based on block truncation coding

  • Yung-Yao ChenEmail author
  • Kuan-Yu Chi
Special Issue Paper

Abstract

Cloud computing is an Internet-based computing model that shares computing resources such as computers, servers, and storage. In future smart cities, new applications can take advantage of cloud computing; for example, a cloud-based home health-care system can provide immediate disease management by analyzing medical images. However, if the size of cloud data is large (e.g., medical images), their transition through the Internet is time consuming. Cloud data authentication is another problem that should be addressed. To address the aforementioned problems, this study presents a novel data hiding method based on the block truncation coding (BTC) image compression technique. This method has two advantages: reduces image size and increases security. This study also proposes a block classification scheme for determining smooth blocks, complex_1 blocks, and complex_2 blocks in an image. Secret data are embedded in these three block types using different approaches. To improve the quality of images without damaging the secret data, we propose a progressive data hiding strategy and integrating an iteration-based halftoning method into BTC. When decoding, the secret data are extracted without recalling the original image. According to experimental results, the proposed method outperforms existing methods in both embedding capacity and image quality evaluations.

Keywords

Cloud data security Data hiding Blind decoding Block truncation coding (BTC) Direct binary search (DBS) 

Notes

Acknowledgements

This work was supported in part by the Ministry of Science and Technology (104-2221-E-027-032).

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Copyright information

© Springer-Verlag GmbH Germany 2017

Authors and Affiliations

  1. 1.Graduate Institute of Automation TechnologyNational Taipei University of TechnologyTaipeiTaiwan, ROC

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