| 基于Matlab多核集群的人脸识别算法的并行化设计 |
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| 引用本文： | 郑晓薇,于梦玲. 基于Matlab多核集群的人脸识别算法的并行化设计[J]. 计算机应用, 2011, 31(10): 2597-2599. DOI: 10.3724/SP.J.1087.2011.02597 |
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| 作者姓名： | 郑晓薇 于梦玲 |
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| 作者单位： | 辽宁师范大学 计算机与信息技术学院, 辽宁 大连 116081 |
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| 基金项目： | 国家自然科学基金资助项目(60603047) |
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| 摘 要： | 为了充分利用多核处理器资源,研究了多线程构建模块并行编程模式,从而提高程序的性能。在Matlab集群环境下对主成分分析(PCA)人脸识别算法设计了训练识别生成样本的功能模块train(),通过任务分割实现了算法的并行化。实验结果表明,94.167%的稳定识别率和趋近线性的加速比验证了并行算法的正确性和高效性。
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| 关 键 词： | 人脸识别 主成分分析 Matlab集群 多核 任务分割 并行计算 |
| 收稿时间： | 2011-04-28 |
| 修稿时间： | 2011-06-12 |
Parallelization design of face recognition algorithm based on Matlab multi-core clusters |
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| ZHENG Xiao-wei,YU Meng-ling. Parallelization design of face recognition algorithm based on Matlab multi-core clusters[J]. Journal of Computer Applications, 2011, 31(10): 2597-2599. DOI: 10.3724/SP.J.1087.2011.02597 |
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| Authors: | ZHENG Xiao-wei YU Meng-ling |
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| Affiliation: | College of Computer and Information Technology, Liaoning Normal University, Dalian Liaoning 116081, China |
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| Abstract: | In order to take full advantage of multi-core processor resources,the parallel programming model by building blocks with multithreading was studied,hence improving the performance of the program.According to the integral structure of Principal Component Analysis(PCA)-based face recognition algorithm,a functional module named train() was designed for the training of recognizing generated samples in the environment of Matlab cluster.The parallelization of this algorithm was realized by task partition.The expe... |
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| Keywords: | face recognition Principal Component Analysis(PCA) Matlab cluster multi-core task partition parallel computing |
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