Progressive Data Hiding in Integer Wavelet Transform of Electrocardiogram by Using Simple Decision Rule and Coefficient Calibration
Ching-Yu Yang, Wen-Fong Wang · Revue d intelligence artificielle · 2020
Based on one dimensional (1D) integer wavelet transform (IWT) domain, patient's data can be effectively embedded in electrocardiogram (ECG) via the proposed criterion and coefficient alignment.Multiple data bits can be sequentially hidden in host bundles (with different lengths) of the low and high subbands of IWT coefficients.Simulations indicated that the average signal-to-noise ratio (SNR) and the payload of the proposed method are superior to those of existing techniques.Additionally, the proposed method exhibited a robustness that has rarely been observed in conventional ECG steganography.Our method is capable of resisting attacks such as cropping, inversion, scaling, translation, truncation, and Gaussian noise addition.Because bit embedding and extraction procedures are quite simple, our method can be applied in portable biometric devices.