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Steganography Using Reversible Texture Synthesis Based on Seeded Region Growing and LSB

Qili Zhou1, Yongbin Qiu1, Li Li1,*, Jianfeng Lu1, Wenqiang Yuan1, Xiaoqing Feng2, Xiaoyang Mao3

School of Computer Science and Technology, Hangzhou Dianzi University, Hangzhou, 310018, China.
School of Information, Zhejiang University of Finance & Economics, Hangzhou, 310000, China.
University of Yamanashi, Yamanashi-ken, 409-3866, Japan.

* Corresponding Author: Li Li. Email: .

Computers, Materials & Continua 2018, 55(1), 151-163.


Steganography technology has been widely used in data transmission with secret information. However, the existing steganography has the disadvantages of low hidden information capacity, poor visual effect of cover images, and is hard to guarantee security. To solve these problems, steganography using reversible texture synthesis based on seeded region growing and LSB is proposed. Secret information is embedded in the process of synthesizing texture image from the existing natural texture. Firstly, we refine the visual effect. Abnormality of synthetic texture cannot be fully prevented if no approach of controlling visual effect is applied in the process of generating synthetic texture. We use seeded region growing algorithm to ensure texture’s similar local appearance. Secondly, the size and capacity of image can be decreased by introducing the information segmentation, because the capacity of the secret information is proportional to the size of the synthetic texture. Thirdly, enhanced security is also a contribution in this research, because our method does not need to transmit parameters for secret information extraction. LSB is used to embed these parameters in the synthetic texture.


Cite This Article

Q. . Zhou, Y. . Qiu, . . Li, J. . Lu, W. . Yuan et al., "Steganography using reversible texture synthesis based on seeded region growing and lsb," Computers, Materials & Continua, vol. 55, no.1, pp. 151–163, 2018.

This work is licensed under a Creative Commons Attribution 4.0 International License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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