Performance Parameter Based Comparison of the Slantlet Transform and Discrete Cosine Transform (DCT) for Steganography in Biomedical Signals
In this paper, we present patient’s information hiding using the Slantlet Transform and Discrete Cosine Transform (DCT). DCT transforms the signal from spatial domain to frequency domain. It can separate the image into high-, middle- and low-frequency components. In DCT-based technique, insertion of secret information in carrier depends on the DCT coefficients. The Slantlet Transform is known as Orthogonal Discrete Wavelet Transform (ODWT). It separates 1-D signal in two sub-bands, LL and HH. It divides 2-D signal into four sub-bands, HH, HL, LH and LL and the secret information is embedded in these sub-bands. At first, DCT is used for data hiding. For that, 1-D ECG signal and some biomedical images (2-D) are used as cover signal. The secret information is embedded in lower DCT coefficients. Similarly, Slantlet transform is used for hiding patient’s data in same biomedical signals ECG and biomedical images, respectively. Original signals and embedded signals are compared. To analyse the performance of the transforms used for data hiding, Mean Squared Error (MSE), Normalised Root Mean Squared Error (NRMSE) and Peak Signal to Noise Ratio (PSNR) are calculated. MSE between original and embedded signals is less.
KeywordsDiscrete Cosine Transform (DCT) The Slantlet Transform Mean Squared Error (MSE) Normalised Root Mean Squared Error (NRMSE) Peak Signal to Noise Ratio (PSNR)
We would like to acknowledge Dr. Ivan W. Selesnick for their efforts for helping us in the implementation and study of Slantlet Transform. The support of The Instrumentation and Control Department, the Management and the Principal Dr. M. B. Khambete of MKSSS’s Cummins College of Engineering for Women Karvenagar, Pune is gratefully acknowledged.
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