A Parallel PSO Algorithm for a Watermarking Application on a GPU
Posgrado en Ciencia e Ingenieria de la Computacion, Universidad Nacional Autonoma de Mexico, Mexico
Computacion y Sistemas, 17(3), 2013
@article{cano2013parallel,
title={A Parallel PSO Algorithm for a Watermarking Application on a GPU},
author={Cano, Edgar Garc{‘i}a and Rodr{‘i}guez, Katya},
journal={Computaci{‘o}n y Sistemas},
volume={17},
number={3},
pages={381–390},
year={2013},
publisher={Instituto Polit{‘e}cnico Nacional}
}
In this paper, a research about the usability, advantages and disadvantages of using Compute Unified Device Architecture (CUDA) is presented, implementing an algorithm based on populations called Particle Swarm Optimization (PSO) [5]. In order to test the performance of the proposed algorithm, a hide watermark image application is put into practice. The PSO is used to optimize the positions where a watermark has to be inserted. This application uses the insertion/extraction algorithm proposed by Shieh et al. [1]. This algorithm was implemented for both sequential and CUDA architectures. The fitness function-used in the optimization algorithm – has two objectives: fidelity and robustness. The measurement of fidelity and robustness is computed using Mean Squared Error (MSE) and Normalized Correlation (NC), respectively; these functions are evaluated using Pareto dominance.
October 24, 2013 by hgpu
