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- W2159458144 abstract "We describe a method of detecting the existence of messages, which are randomly scattered in the least significant bits (LSB) of both 24-bit RGB color and 8-bit grayscale images. The method is based on gathering and inspecting a set of image relevant features from the pixel groups of the stego-image, whose similarities and correlations change with different ratios of LSB embedding. The proposed detection scheme is based on support vector regression (SVR). It is shown that the measurement of a selected set of features forms a multidimensional feature space which allows estimation of the length of hidden messages embedded in the LSB of cover-images with high precision." @default.
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- W2159458144 date "2005-06-07" @default.
- W2159458144 modified "2023-09-26" @default.
- W2159458144 title "LSB steganalysis using support vector regression" @default.
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- W2159458144 doi "https://doi.org/10.1109/iaw.2004.1437803" @default.
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