Paper
9 May 2000 Topological-ordered color table for BPCS-steganography using indexed color images
Robert Ouellette, Hideki Noda, Michiharu Niimi, Eiji Kawaguchi
Author Affiliations +
Abstract
Image index tables values generally give the best possible representation of the color information of the image. However, no consideration is given to the arrangement of the color table itself. Thus, depending on the image, pixels with similar colors may have different index values and can therefore have considerably different index binary makeups. Consequently, regions of similarly colored indexed pixels can be noise-like at the bitplane level while the output colors themselves may imply simple bitplane patterns. BPCS image steganography hides information in images based on the principle that if regions in a bitplane are noise-like, those regions can be replaced with noise-like secret data. Therefore, applying traditional BPCS steganography to indexed image data results in drastic visible changes to the image. To overcome this problem, we used a self-organizing neural network to reorder the index table, based on samples from the image, such that similar colors in the index table are near each other with respect to their index values. As a result, regions with similar color information have only slight binary differences at the bitplane level, whereas regions with mixed color information will have considerable binary differences. Using this technique, we can embed secret data that is 15 to 35 percent the size of the image with little or no noticeable degradation in the image.
© (2000) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Robert Ouellette, Hideki Noda, Michiharu Niimi, and Eiji Kawaguchi "Topological-ordered color table for BPCS-steganography using indexed color images", Proc. SPIE 3971, Security and Watermarking of Multimedia Contents II, (9 May 2000); https://doi.org/10.1117/12.385004
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Cited by 12 scholarly publications.
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KEYWORDS
Steganography

Neural networks

Binary data

Neurons

Image processing

Image quality

Computer security

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