VQ-oriented data hiding based on adjustable error compensation strategy. Issue 4 (2nd October 2021)

• Record Type: Journal Article
• Authors: Chang, Chin-Chen; Horng, Ji-Hwei; Shih, Chia-Shou; Wang, Xu
• Is Part Of: Connection science. Volume 33:Issue 4(2021)
• Page Start: 835
• Page End: 853
• Publication Date: 2021-10-02
• Subjects: Vector quantisation -- data hiding -- error compensation -- codebook; Neural computers -- Periodicals; Artificial intelligence -- Periodicals; Cognitive science -- Periodicals; Connectionism -- Periodicals; 006.3
• DOI: 10.1080/09540091.2021.1900073
• Languages: English
• ISSNs: 0954-0091

Abstract

Abstract : Nowadays, we greatly depend on Internet mass transmission, of all kinds of data, including critical information among them. Therefore, secure communication is an important topic. Data hiding can embed critical information into carriers, such as images, videos, and so on. Efficiently embedding information into images is the goal of this research. Image steganography techniques utilise a cover image to hide secret data and produce a stego-image by modifying pixel values. After modification, the stego-image is distorted with respect to the cover image. Vector quantisation (VQ) is a lossy image compression technique. The image recovered from the VQ compressed code has distortion compared to the original image. Based on the VQ image, we can hide secret data by modifying the pixel value in a way that the distortion is compensated. The embedding rate of the proposed scheme is adjustable. Experimental results show that our scheme can achieve a high embedding rate in comparison with related works. For low-quality VQ images, embedding can improve the visual quality of the stego-image at the same time.