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Secured Data Hiding based on Compression Function and Quantization

Ajit Danti, G.R.Manjula Published in Information Systems

International Journal of Applied Information Systems
Year of Publication 2012
© 2010 by IJAIS Journal
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  1. Ajit Danti and G.R.Manjula. Article: Secured Data Hiding based on Compression Function and Quantization. International Journal of Applied Information Systems 1(2):53-58, January 2012. BibTeX

    	author = "Ajit Danti and G.R.Manjula",
    	title = "Article: Secured Data Hiding based on Compression Function and Quantization",
    	journal = "International Journal of Applied Information Systems",
    	year = 2012,
    	volume = 1,
    	number = 2,
    	pages = "53-58",
    	month = "January",
    	note = "Published by Foundation of Computer Science, New York, USA"


Data hiding is the process of secretly embedding information inside a data source without changing its perceptual quality. In this paper, Quantization Index Modulation and the compression function of µ-Law standards for quantization are used. The proposed method transforms the host signal into the logarithmic domain using the µ-Law compression function. Then, the transformed data is quantized uniformly and the result is transformed back to the original domain using the inverse function. The scalar and the vector methods along with a secret key for data hiding will make the method more secure and efficient. The experimental results demonstrate the robustness of the proposed approach.


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Quantization, Data hiding, Information security, Digital water marking