Bumsoo Kim¹, Wonseop Shin², Yonghoon Jung¹, Youngsup Park³, Sanghyun Seo^1,4,*

CMES-Computer Modeling in Engineering & Sciences, Vol.141, No.3, pp. 2143-2164, 2024, DOI:10.32604/cmes.2024.056079 - 31 October 2024

Abstract Arbitrary style transfer aims to perceptually reflect the style of a reference image in artistic creations with visual aesthetics. Traditional style transfer models, particularly those using adaptive instance normalization (AdaIN) layer, rely on global statistics, which often fail to capture the spatially local color distribution, leading to outputs that lack variation despite geometric transformations. To address this, we introduce Patchified AdaIN, a color-inspired style transfer method that applies AdaIN to localized patches, utilizing local statistics to capture the spatial color distribution of the reference image. This approach enables enhanced color awareness in style transfer, adapting… More >

Xiong Zhang^1,2, Minqing Zhang^1,2,3,*, Xu’an Wang^1,2,3,*, Siyuan Huang^1,2, Fuqiang Di^1,2

CMC-Computers, Materials & Continua, Vol.81, No.1, pp. 1433-1448, 2024, DOI:10.32604/cmc.2024.056742 - 15 October 2024

Abstract Traditional information hiding techniques achieve information hiding by modifying carrier data, which can easily leave detectable traces that may be detected by steganalysis tools. Especially in image transmission, both geometric and non-geometric attacks can cause subtle changes in the pixels of the image during transmission. To overcome these challenges, we propose a constructive robust image steganography technique based on style transformation. Unlike traditional steganography, our algorithm does not involve any direct modifications to the carrier data. In this study, we constructed a mapping dictionary by setting the correspondence between binary codes and image categories and… More >

Xiong Zhang^1,2, Minqing Zhang^1,2,3,*, Xu An Wang^1,2,3, Wen Jiang^1,2, Chao Jiang^1,2, Pan Yang^1,4

CMC-Computers, Materials & Continua, Vol.79, No.2, pp. 1925-1938, 2024, DOI:10.32604/cmc.2024.050899 - 15 May 2024

Abstract This paper proposes an artificial intelligence-based robust information hiding algorithm to address the issue of confidential information being susceptible to noise attacks during transmission. The algorithm we designed aims to mitigate the impact of various noise attacks on the integrity of secret information during transmission. The method we propose involves encoding secret images into stylized encrypted images and applies adversarial transfer to both the style and content features of the original and embedded data. This process effectively enhances the concealment and imperceptibility of confidential information, thereby improving the security of such information during transmission and… More >