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计算机工程 ›› 2012, Vol. 38 ›› Issue (24): 166-170. doi: 10.3969/j.issn.1000-3428.2012.24.039

• 人工智能及识别技术 • 上一篇    下一篇

融合过滤和封装方式的特征选择算法

代 旺,方昱春,李 杨   

  1. (上海大学计算机工程与科学学院,上海 200072)
  • 收稿日期:2012-02-28 修回日期:2012-03-27 出版日期:2012-12-20 发布日期:2012-12-18
  • 作者简介:代 旺(1988-),男,硕士,主研方向:图像处理,模式识别;方昱春,副研究员、博士;李 杨,硕士
  • 基金资助:
    国家自然科学基金资助项目(61170155);上海市重点学科建设基金资助项目(J50103);上海大学研究生创新基金资助项目(SHUCX1 12152)

Feature Selection Algorithm Fused with Filtering and Packaging Mode

DAI Wang, FANG Yu-chun, LI Yang   

  1. (School of Computer Engineering and Science, Shanghai University, Shanghai 200072, China)
  • Received:2012-02-28 Revised:2012-03-27 Online:2012-12-20 Published:2012-12-18

摘要: 已有特征选择算法不能有效降低特征维数,且稳定性较低。为此,提出一种融合过滤和封装方式的特征选择算法。在封装式算法中,设计能保持图像之间拓扑结构的特征选择判据,在过滤式算法中,以Fisher Score为判据,采用单独最优的特征搜索策略。实验结果表明,将算法应用于人脸识别中,能提高识别率,降低特征维数,且具有较好的稳定性。

关键词: 特征选择, 过滤式方法, 封装式方法, Fisher Score判据, 人脸识别, 降维

Abstract: The feature selection algorithm can not effectively reduce the feature dimension, and the stability is lower. In order to solve this problem, this paper proposes a feature selection algorithm of fusing filtering and packaging mode. In packaging type algorithm, it designs the feature selection criterion which can maintain topological structure between image, uses Fisher Score as criterion in the filtering type algorithm, and the individual optimum search strategy is used in this paper. Experimental results show that this algorithm can improve recognition rate, reduces the feature dimension, and has good stability in face recognition application.

Key words: feature selection, filtering type method, packaging type method, Fisher Score criterion, face recognition, dimension reduction

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