An embedding strategy on fusing multiple image features for data hiding in multiple images

• Published in: Journal of visual communication and image representation 2020-08, Vol.71, p.102822, Article 102822
• Main Authors: Yang, Junxue, Liao, Xin
• Format: Article
• Language: English
• Subjects: Embedding strategy; Image complexity; Multiple image features; Multiple images steganography; Steganographic capacity
• ISSN: 1047-3203; 1095-9076
• DOI: 10.1016/j.jvcir.2020.102822

•Employ multiple image features to depict image complexity, and propose the new computing method of steganographic capacity.•A novel embedding strategy is proposed, in which we select image with high capacity in priority.•Experiment results show the new proposed strategy can obtain better performance. Data hiding in multiple images has been a significant research direction in information security. How to reasonably design the embedding strategy to spread the payload among multiple images is still an open issue. In this paper, we propose an embedding strategy on fusing multiple features. We utilize the typical characteristic parameters of gray level co-occurrence matrix, the image entropy and the shape parameter to describe image complexity. Furthermore, we combine with the number of cover images, the number of cover images assigned to steganographer and the size of cover image to estimate the steganographic capacity of each image. The strategy is implemented together with some state-of-the-art single image steganographic algorithms. Experimental results demonstrate that the security performance of the proposed strategy is higher than that of the state-of-the-art embedding strategy against the blind universal pooled steganalysis.