Data Adaptive Multi-Band Approach for Robust Audio Watermarking Using Adaptive Threshold

Abstract

This paper presents a data adaptive digital audio watermarking process with the use of Empirical Mode Decomposition (EMD) and Hilbert Transform (HT). The host audio signal is decomposed into several Intrinsic Mode Functions (IMFs). A binary image or a set of -1 and 1, which is obtained by mapping from standard normal distributed pseudo random numbers, is embedded as secret information into the significant coefficients of the highest energetic IMF that are greater than a specified adaptive threshold. Thus watermarked IMF is less sensitive to common signal processing attack. As a result this method increases more robustness. The experimental results show that the proposed method has good imperceptibility and robustness under common signal processing attacks such as additive noise (in time domain and in frequency domain), low pass filtering, re-sampling, re-quantization, MP3 compression, and sound processing effects such as, delay, a natural sounding reverberation (Schroeder’s Reverberator), flanging effect, equalization effect, etc. A Bit Error calculation equation is provided to measure the accuracy of the extracted watermark.

A Study of Conflict Issues Affecting Ugandan Housemaids who Migrate to Saudi Arabia and How to Mitigate them

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This study aims to comprehensively analyse the complex interplay between