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3D Multilayered Turtle Shell Models for Image Steganography

Ji-Hwei Horng1, Juan Lin2,*, Yanjun Liu3, Chin-Chen Chang3,4,*
1 National Quemoy University, Kinmen County, 892, Taiwan
2 Engineering Research Center for ICH Digitalization and Multi-Source Information Fusion, Fuqing Branch of Fujian Normal University, Fujian Province University, Fuzhou, 350300, China
3 Department of Information Engineering and Computer Science, Feng Chia University, Taichung, 40724, Taiwan
4 School of Computer Science and Technology, Hangzhou Dianzi University, Hangzhou, 310018, China
* Corresponding Authors: Juan Lin. Email: ; Chin-Chen Chang. Email:
(This article belongs to this Special Issue: Information Hiding and Multimedia Security)

Computer Modeling in Engineering & Sciences 2020, 125(2), 879-906. https://doi.org/10.32604/cmes.2020.09355

Received 06 December 2019; Accepted 09 March 2020; Issue published 12 October 2020

Abstract

By embedding secret data into cover images, image steganography can produce non-discriminable stego-images. The turtle shell model for data hiding is an excellent method that uses a reference matrix to make a good balance between image quality and embedding capacity. However, increasing the embedding capacity by extending the area of basic structures of the turtle shell model usually leads to severe degradation of image quality. In this research, we innovatively extend the basic structure of the turtle shell model into a three-dimensional (3D) space. Some intrinsic properties of the original turtle shell model are well preserved in the 3D version. Theoretic analysis shows that the new proposed models have good performance both in the image quality and in the complexity of the reference matrix. Our experimental results justify the theoretic conclusions.

Keywords

3D turtle shell; data hiding; reference matrix; image quality

Cite This Article

Horng, J., Lin, J., Liu, Y., Chang, C. (2020). 3D Multilayered Turtle Shell Models for Image Steganography. CMES-Computer Modeling in Engineering & Sciences, 125(2), 879–906.

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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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