Multiple watermarking is used to share the copyright of multiple users, increase robustness and high security. The proposed method is comparison of multiple-watermarking techniques based on Discrete Wavelet Transform and Singular Value Decomposition using Genetic algorithm. This research elaborates the three main categories of multiple watermarking techniques such as successive, segmented and composite watermarking. The experimental results show that the DWT-based watermarking algorithms possess multi-resolution description characteristics achieving imperceptibility. The SVD-based watermarking algorithms add the watermark information to the singular values of the diagonal matrix achieving robustness requirements. The optimization is to maximize the performance of peak signal to noise ratio and normalized correlation in multiple watermarking techniques using genetic algorithms. 
Comparison of multiple watermarking techniques using genetic algorithms