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Multi-level Significant Bit (MLSB) Embedding Based on Weighted Container Model and Weighted F5 Concept

Part of the Advances in Intelligent Systems and Computing book series (AISC,volume 427)

Abstract

In this paper the weighted container concept of cover image jointly with error correcting codes perfect in weighted Hamming metric (ECCPWH) is consider. Such approach can improve the efficient of the ECC embedding schemes based on syndrome coding. To show the effectiveness of ECCPWH based scheme the example of multi-level significant bit (MLSB)embedding scheme applied to digital image is provided. ECCPWH based method is compared with the linear error-block codes (LEBC) steganography method that is based on linear error-block codes perfect in \(\pi \)- metric. The examples show that proposed MLSB embedding scheme that is based on ECCPWH approach is efficient for syndrome coding embedding algorithms.

Keywords

  • Digital watermarking
  • Least significant bit embedding
  • Multi-level significant bit (mlsb) embedding
  • Weighted container model
  • Error correcting codes perfect in weighted Hamming metric (ECCPWH)
  • Weighted f5 (wf5) concept
  • Linear error-block codes (lebc)

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  • DOI: 10.1007/978-3-319-29504-6_29
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Acknowledgments

We are grateful to the reviewer for his/her careful reading of the paper and his/her thoughtful comments. His/her comments and advices has helped us improve and clarify the paper.

This work was partly financially supported by the Russian Ministry of Education and Science within a framework of the basic task to the university in 2015 (project number 2452).

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Correspondence to Natalia Voloshina .

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Bezzateev, S., Voloshina, N., Zhidanov, K. (2016). Multi-level Significant Bit (MLSB) Embedding Based on Weighted Container Model and Weighted F5 Concept. In: Abraham, A., Wegrzyn-Wolska, K., Hassanien, A., Snasel, V., Alimi, A. (eds) Proceedings of the Second International Afro-European Conference for Industrial Advancement AECIA 2015. Advances in Intelligent Systems and Computing, vol 427. Springer, Cham. https://doi.org/10.1007/978-3-319-29504-6_29

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  • DOI: https://doi.org/10.1007/978-3-319-29504-6_29

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