A Parallel PSO Algorithm for a Watermarking Application on a GPU

Authors

  • Edgar García Cano Posgrado en Ciencia e Ingeniería de la Computación, Universidad Nacional Autónoma de México
  • Katya Rodríguez Instituto de Investigaciones en Matemáticas Aplicadas y en Sistemas, Universidad Nacional Autónoma de México

DOI:

https://doi.org/10.13053/cys-17-3-1562

Keywords:

Parallel particle swarm optimization, watermarking, CUDA, image security.

Abstract

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.

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Published

2013-10-01

Issue

Vol. 17 No. 3 (2013): 17(3) July-September 2013

Section

Articles

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