LSB Based Steganography
Steganography is an ancient art of conveying messages in a secret way that only the receiver knows the existence of message. So, a fundamental requirement for a stegano- graphic method is imperceptibility; this means that the embedded messages should not be discernible to the human eye. There are two other requirements, one is to maximize the embedding capacity, and the other is security. The least-significant bit (LSB) insertion method is the most common and easiest method for embedding messages in an image. However, how to decide on the maximal embedding capacity for each pixel is still an open issue. An image steganographic model is proposed that is based on variable-sized LSB insertion to maximise the embedding capacity while maintaining the image fidelity. For each pixel of a gray-scale image, at least 4 bits can be used for messages embedding. First, according to contrast and luminance characteristics, the capacity evaluation is provided to estimate the maximum embedding capacity of each pixel. Then, the minimum-error replacement method is adapted to find a gray-scale as close to the original one as possible.
Index Terms: Matlab, source, code, LSB, least, significant, bit, steganography.
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Figure 1. Bitstream |
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A simple and effective source code for High Capacity Image Steganographic Model. |
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Demo code (protected P-files) available for performance evaluation. Matlab Image Processing Toolbox is required.
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Release
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Date
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Major features
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1.0
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2009.06.20
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We recommend to check the secure connection to PayPal, in order to avoid any fraud. |
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High Capacity Image Steganographic Model. Click here for your donation. In order to obtain the source code you have to pay a little sum of money: 100 EUROS (less than 140 U.S. Dollars).
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Once you have done this, please email us luigi.rosa@tiscali.it
As soon as possible (in a few days) you will receive our new release of High Capacity Image Steganographic Model. Alternatively, you can bestow using our banking coordinates:
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The authors have no relationship or partnership with The Mathworks. All the code provided is written in Matlab language (M-files and/or M-functions), with no dll or other protected parts of code (P-files or executables). The code was developed with Matlab 2006a. Matlab Image Processing Toolbox is required. The code provided has to be considered “as is” and it is without any kind of warranty. The authors deny any kind of warranty concerning the code as well as any kind of responsibility for problems and damages which may be caused by the use of the code itself including all parts of the source code.
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