A Parallel PSO Algorithm for a Watermarking Application on a GPU
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| Formato: | Artículo científico |
| Lenguaje: | en |
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Instituto Politécnico Nacional
2013
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| _version_ | 1876443162698842112 |
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| author | Edgar García Cano |
| author_facet | Edgar García Cano |
| contents | A Parallel PSO Algorithm for a Watermarking Application on a GPU Edgar García Cano Katya Rodríguez Computación CUDA image security Parallel particle swarm watermarking 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. 2013 artículo científico 1405-5546 https://www.redalyc.org/articulo.oa?id=61528316009 en http://www.redalyc.org/revista.oa?id=615 Computación y Sistemas application/pdf Instituto Politécnico Nacional Computación y Sistemas (México) Num.3 Vol.17 |
| format | Artículo científico |
| id | redalyc_61528316009 |
| institution | Redalyc |
| language | en |
| publishDate | 2013 |
| publisher | Instituto Politécnico Nacional |
| spellingShingle | A Parallel PSO Algorithm for a Watermarking Application on a GPU Edgar García Cano Computación CUDA image security Parallel particle swarm watermarking A Parallel PSO Algorithm for a Watermarking Application on a GPU Edgar García Cano Katya Rodríguez Computación CUDA image security Parallel particle swarm watermarking 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. 2013 artículo científico 1405-5546 https://www.redalyc.org/articulo.oa?id=61528316009 en http://www.redalyc.org/revista.oa?id=615 Computación y Sistemas application/pdf Instituto Politécnico Nacional Computación y Sistemas (México) Num.3 Vol.17 |
| title | A Parallel PSO Algorithm for a Watermarking Application on a GPU |
| topic | Computación CUDA image security Parallel particle swarm watermarking |
| url | https://www.redalyc.org/articulo.oa?id=61528316009 |