计算机科学 ›› 2011, Vol. 38 ›› Issue (5): 190-193.

• 人工智能 • 上一篇    下一篇

基于正交投影的分类器算法

王卫东,苗帅,杨静宇   

  1. (江苏科技大学计算机科学与工程学院 镇江212003);(南京理工大学计算机系 南京210094)
  • 出版日期:2018-11-16 发布日期:2018-11-16
  • 基金资助:
    本文受国家自然科学基金(60632050)资助。

Classifier Algorithm Based on Orthogonal Projection

WANG Wei-dong,MIAO Shuai,YANG Jing-yu   

  • Online:2018-11-16 Published:2018-11-16

摘要: 提出了一种新颖的基于正交投影的分类器算法。该算法将测试样本正交投影到由各类训练样本生成的子空间中,并计算测试样本到各子空间的距离,以此作为分类的依据。该算法不需要计算样本协方差矩阵的逆阵,因此特别适合于小样本问题。在ORL人脸库上的实验结果表明,该算法的模式识别率高于传统分类器方法。

关键词: 正交投影,分类器,小样本问题,人脸识别

Abstract: In this paper,a novel classifier algorithm based on orthogonal projection was presented. This classifier projecled testing samples to orthogonal subspaces that were spanned by training samples of per class, and calculated the dislance of the testing samples and subspaces,then classified the testing samples according to the distance. The character of this classifier is that it need not calculate the covariance matrices' inverses, so it is very suit for small sample size problem. The experimental results in ORI. database prove this classifier algorithm outperforms the traditional classifier algorithm in recognition rate.

Key words: Orthogonal projection,Classifier,Sma11 sample size problem,Face recognition

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