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ECG steganography based on tunable Q‐factor wavelet transform and singular value decomposition
Author(s) -
Mathivanan P.,
Balaji Ganesh A.
Publication year - 2021
Publication title -
international journal of imaging systems and technology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.359
H-Index - 47
eISSN - 1098-1098
pISSN - 0899-9457
DOI - 10.1002/ima.22477
Subject(s) - singular value decomposition , steganography , watermark , wavelet transform , singular value , algorithm , computer science , residual , wavelet , quantization (signal processing) , transformation (genetics) , signal (programming language) , discrete wavelet transform , mathematics , artificial intelligence , physics , embedding , chemistry , quantum mechanics , gene , programming language , biochemistry , eigenvalues and eigenvectors
The article presents a novel ECG steganography scheme based on the tunable Q‐factor wavelet transformation (TQWT) and also singular value decomposition (SVD) techniques that ensure better safety and confidentiality of patient information. Initial parameters such as Q , r , and J are used to decompose the cover signal into individual frequency sub‐bands with the tunable Q‐factor wavelet transform (TQWT). The singular value decomposition (SVD) technique is used to further decompose high‐frequency sub‐band coefficients into singular values. The watermark information is then embedded with high‐frequency sub‐band coefficients by involving the quantization process. The performance of this proposed system is successfully evaluated by considering various metrics, such as peak signal to noise ratio (PSNR), structural similarity index (SSIM), percentage residual difference (PRD), and bit error rate (BER). The simulation results of the proposed scheme are observed to be better than other traditional algorithms.