A Strategy of Clustering Modification Directions in Spatial Image Steganography
Abstract— Most of the recently proposed steganographic schemes are based on minimizing an additive distortion function deﬁned as the sum of embedding costs for individual pixels. In such an approach, mutual embedding impacts are often ignored. In this paper, we present an approach that can exploit the interactions among embedding changes in order to reduce the risk of detection by steganalysis. It employs a novel strategy, called clustering modiﬁcation directions < Final Year Projects 2016 > CMDs, based on the assumption that when embedding modiﬁcations in heavily textured regions are locally heading toward the same direction, the steganographic security might be improved. To implement the strategy, a cover image is decomposed into several subimages, in which message segments are embedded with well-known schemes using additive distortion functions. The costs of pixels are updated dynamically to take mutual embedding impacts into account.
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