DeAR: A Deep-Learning-Based Audio Re-recording Resilient Watermarking

DWT-based audio watermarking

Many effective watermarking algorithms have been proposed and implemented for digital images and digital video, however, few algorithms have been proposed for audio watermarking. This is due to the fact that, the human audio system is far more complex and sensitive than the human visual system. In this paper, we describe an imperceptible and robust audio watermarking algorithm based on the disc...

Combining pattern recognition and deep-learning-based algorithms to automatically detect commercial quadcopters using audio signals (Research Article)

Commercial quadcopters with many private, commercial, and public sector applications are a rapidly advancing technology. Currently, there is no guarantee to facilitate the safe operation of these devices in the community. Three different automatic commercial quadcopters identification methods are presented in this paper. Among these three techniques, two are based on deep neural networks in whi...

Muteness-Based Audio Watermarking Technique

Audio watermarking is a promising approach to copyright protection of audio data, especially music and songs. Several waternzarking techniques have been developed and commercialized. The watermarks produced by those techniques can withstand a number of single attacks such as MPEG, resampling, filtering, and quantization. However, the waterniurks are easily destroyed i f subjected to chopping or...

Audio watermarking benchmarking: a profile based approach

Cropping Resilient Watermarking Based on Histogram Modification

This paper proposes a watermarking scheme robust against most common geometric and signal processing operations, for applications that require an accurate detection of the owner watermark even if the digital image suffers intentional and non-intentional attacks. The proposed scheme is based on two modifications introduced in two 2D histograms. In the first modification a selected region of a 2D...