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Binary in Binary for Secret Writing – A Cryptic’s Cousin Approach

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International Journal of Computer Applications
© 2010 by IJCA Journal
Number 11 - Article 8
Year of Publication: 2010
Authors:
R. Amirtharajan
Venkata Abhiram Murarisetty
Dr. R.John Bosco Balaguru
10.5120/951-1328

Dr. R.John Bosco Balaguru, Venkata Abhiram Murarisetty and R Amirtharajan. Article: Binary in Binary for Secret Writing A Cryptics Cousin Approach. International Journal of Computer Applications 5(11):41–47, August 2010. Published By Foundation of Computer Science. BibTeX

@article{key:article,
	author = {Dr. R.John Bosco Balaguru and Venkata Abhiram Murarisetty and R. Amirtharajan},
	title = {Article: Binary in Binary for Secret Writing  A Cryptics Cousin Approach},
	journal = {International Journal of Computer Applications},
	year = {2010},
	volume = {5},
	number = {11},
	pages = {41--47},
	month = {August},
	note = {Published By Foundation of Computer Science}
}

Abstract

Binary images, like cartoons, text documents, signatures captured by signing pads and/or 2-color images are very commonly used in our daily life. The JPEG compression method which was designed to efficiently compress color images do not do a good job on a monochromatic (binary) image. Changing the pixel values in these images for hiding the data, may produce a noticeable change in the cover media. Embedding capacity and preservation of visible artifacts are the potential problems of this technique. This paper proposes several methods for hiding data in binary images (including fax). The proposed algorithms alter pixels of the embeddable blocks of cover image depending on the characteristic values of the block. In addition, the new algorithm deals with statistical embedding for each block, which enhances the security of embedded data and the capacity of the embedding method. The performances of the algorithms are tested over various sizes of binary cover images by embedding various sizes of secured data. The effectiveness of the stego process proposed has been studied by estimating the number of errors, Bit error rate and Relative entropy.

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