Pub. online:27 Oct 2025Type:Research ArticleOpen Access
Journal:Informatica
Volume 36, Issue 4 (2025), pp. 959–984
Abstract
A steganographic scheme based on perfect coverings of dichotomous shares with sparse observation windows is presented in this paper. The manipulations with pixels are based on the number of different colours in the sparse cells of the current observation window. The conditions for the existence of perfect coverings for different architectures of sparse observation windows are derived. The number and distribution of active cells in the current observation window contribute to the additional security of the proposed scheme. This paper also provides performance measures, statistical features, and demonstrates the robustness of the proposed steganographic scheme.
Journal:Informatica
Volume 25, Issue 1 (2014), pp. 113–137
Abstract
This paper presents an adaptive image-watermarking technique based on just-noticeable distortion (JND) profile and fuzzy inference system (FIS) optimized with genetic algorithm (GA). Here it is referred to as the AIWJFG technique. During watermark embedding, it embeds a watermark into an image by referring the JND profile of the image so as to make the watermark more imperceptible. It employs image features and local statistics in the construction of an FIS, and then exploits the FIS to extract watermarks without original images. In addition, the FIS can be further optimized by a GA to improve its watermark-extraction performance remarkably. Experimental results demonstrate that the AIWJFG technique not only makes the embedded watermarks further imperceptible but also possesses adaptive and robust capabilities to resist on image-manipulation attacks being considered in the paper.
Journal:Informatica
Volume 16, Issue 3 (2005), pp. 419–430
Abstract
Most recent papers about visual cryptography for halftone images are dedicated to get a higher contrast decoded image. However, the hidden visual pattern often blends into the background image and leads to a confused image. In this paper, we propose an improved method for halftone image hiding. By using the proposed method, the background image can be eliminated and the hidden visual pattern can be revealed precisely. Experimental results show that the decoded visual patterns could reveal good visual quality under various kinds of input patterns. Furthermore, better visual quality can be obtained when more halftone images are overlaid.