Adaptation in natural and artificial systems
Adaptation in natural and artificial systems
Fractal functions and wavelet expansions based on several scaling functions
Journal of Approximation Theory
Information Hiding Techniques for Steganography and Digital Watermarking
Information Hiding Techniques for Steganography and Digital Watermarking
Audio Watermarking Algorithm Based on Wavelet Packet and Psychoacoustic Model
PDCAT '05 Proceedings of the Sixth International Conference on Parallel and Distributed Computing Applications and Technologies
A remote sensing image self-adaptive blind watermarking algorithm based on wavelet transformation
SSIP'07 Proceedings of the 7th WSEAS International Conference on Signal, Speech and Image Processing
Blind watermark algorithm based on HVS and RBF neural network in DWT domain
WSEAS Transactions on Computers
An optimal robust digital image watermarking based on genetic algorithms in multiwavelet domain
WSEAS Transactions on Signal Processing
A Robust, Digital-Audio Watermarking Method
IEEE MultiMedia
A new approach for optimization in image watermarking by using genetic algorithms
IEEE Transactions on Signal Processing
IEEE Transactions on Information Theory
Multiwavelet prefilters. II. Optimal orthogonal prefilters
IEEE Transactions on Image Processing
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In this paper, we propose a new approach for optimization in digital audio watermarking using artificial intelligent technique. The watermarks are embedded into the low frequency coefficients in discrete multiwavelet transform domain. The embedding technique is based on quantization process which does not require the original audio signal in the watermark extraction. We have developed an optimization technique using the genetic algorithm to search for optimal quantization step in order to improve both quality of watermarked audio and robustness of the watermark. In addition, we analyze the performance of the proposed algorithm in terms of signal-to-noise ratio, normalized correlation and bit error rate. The experimental results show that our proposed method can improve the quality of the watermarked audio signal and give more robustness of the watermark as compared to previous works.