|International Journal of Applied Information Systems
|Foundation of Computer Science (FCS), NY, USA
|Volume 1 - Number 2
|Year of Publication: 2012
|Authors: Ajit Danti, G.R.Manjula
Ajit Danti, G.R.Manjula . Secured Data Hiding based on Compression Function and Quantization. International Journal of Applied Information Systems. 1, 2 ( January 2012), 53-58. DOI=10.5120/ijais12-450109
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.