PCA Encrypted Short Acoustic Data Inculcated in Digital Color Images

Sunil H. Karamchandani, Krutarth J. Gandhi, Siddharth R. Gosalia, Vinod K. Madan, Shabbir N. Merchant, Uday B. Desai


We propose develop a generalized algorithm for hiding audio signal using image steganography. The authors suggest transmitting short audio messages camouflaged in digital images using Principal Component Analysis (PCA) as an encryption technique. The quantum of principal components required to represent the audio signal by removing the redundancies is a measure of the magnitude of the Eigen values. The aforementioned technique follows a dual task of encryption and in turn also compresses the audio data, sufficient enough to be buried in the image. A 57Kb audio signal is decipher from the Stego image with a high PSNR of 47.49 and a correspondingly low mse of 3.3266 × 10􀀀^(-6) with an equalized high quality audio output. The consistent and comparable experimental results on application of the proposed method across a series of images demonstrate that PCA based encryption can be adapted as an universal rule for a specific payload and the desired compression ratio.


Colour image steganography, principal component analysis, eigen thresholding, Pareto analysis

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DOI: https://doi.org/10.15837/ijccc.2015.5.2029

Copyright (c) 2017 Sunil H. Karamchandani, Krutarth J. Gandhi, Siddharth R. Gosalia, Vinod K. Madan, Shabbir N. Merchant, Uday B. Desai

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