Title: Greedy algorithm for image quality optimisation based on turtle-shell steganography

Authors: Guo-Hua Qiu; Chin-Feng Lee; Chin-Chen Chang

Addresses: School of Electronic and Information Engineering, Fuqing Branch of Fujian Normal University, Fuzhou 350300, China ' Department of Information Management, Chaoyang University of Technology, Taichung 41349, Taiwan ' Department of Information Engineering and Computer Science, Feng Chia University, Taichung 40724, Taiwan

Abstract: Information hiding, also known as data hiding, is an emerging field that combines multiple theories and technologies. In recent years, Chang et al. and Liu et al. have proposed new data hiding schemes based on Sudoku, a turtle-shell, etc. These proposed schemes have their own advantages in terms of visual quality and embedded capacity. However, the reference matrices used in these schemes are not optimal. Based on the characteristics of these schemes, Jin et al. employed particle swarm optimisation to select the reference matrix and achieved approximately optimal results in reducing the distortion of the stego-image. However, the complexity is high. In this paper, a turtle-shell matrix optimisation scheme is proposed using a greedy algorithm. The experimental results show that our proposed greedy algorithm is better than the particle swarm optimisation scheme at finding a near-optimal matrix and achieving better stego-image quality, and it outperforms the particle swarm optimisation scheme in terms of computational amount and efficiency.

Keywords: data hiding; turtle-shell steganography; particle swarm optimisation; PSO; greedy algorithm.

DOI: 10.1504/IJCSE.2020.110192

International Journal of Computational Science and Engineering, 2020 Vol.23 No.1, pp.50 - 62

Received: 31 Oct 2019
Accepted: 05 Feb 2020
Published online: 08 Oct 2020 *

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