期刊文献+

相似模式类鉴别分析方法

Similar pattern discriminant analysis
下载PDF
导出
摘要 针对多类识别时原始特征空间中相近的类经过线性鉴别分析(LDA)降维后,在低维空间中易被混淆,不利于识另4的问题,提出了一种通过对相似类对抽取鉴别向量构成特征变换矩阵的相似模式类鉴别分析(SPDA)方法,并将该方法与LDA降维相结合,应用于级联改进二次鉴别函数(MQDF)分类器中,实现了对手写汉字识别性能的进一步提高。在脱机手写汉字字符集2000(HCL2000)上的识别率为98.82%,识别结果高于可查文献中相应的识别结果,这表明该方法是有效的。 In multi-class recognition, neighbor classes in the original feature space are prone to be more confused after feature dimensionality reduction by linear discriminant analysis (LDA). It does not benefit the recognition. To solve this problem, this paper proposes a similar pattern discriminant analysis (SPDA) method, which constructs the feature transformation matrix based on discriminant vectors extracted from similar pattern pairs. The proposed SPDA method was applied together with LDA to the cascade modified quadratic discriminant function (MQDF) classifiers to improve the performance of recognizing handwritten Chinese characters. The results show that the rec- ognition accuracy on handwritten character library 2000 (HCL2000) reaches up to 98.82%, which is higher than the corresponding results found in the literature. The experiment indicates that the proposed method is effective.
出处 《高技术通讯》 CAS CSCD 北大核心 2012年第3期249-255,共7页 Chinese High Technology Letters
基金 国家自然科学基金(60933010)资助项目.
关键词 线性鉴别分析 相似模式鉴别 级联分类器 脱机手写汉字识别 linear discriminant analysis (LDA), similar pattern discriminant, cascade classifier, offline Chi- nese handwriting recognition
  • 相关文献

参考文献13

  • 1Fisher R A. The statistical utilization of multiple measurements. Ann Eugenics, 1938, 8:376-386.
  • 2Rao C R. The utilization of multiple measurements in problems of biological classification. Journal of Royal Statistical Society B, 1948, 10:159-203.
  • 3TaoD C, Li X L, Wu X D, et al. Geometric mean for subspace selection. IEEE Trans On Pattern Analysis and Machine Intelligence, 2009, 31 ( 2 ) : 260-274.
  • 4Rueda L, Oommen B J, Henri'quez C. Multi-class pairwise linear dimensionality reduction using heteroscedastic schemes. Pattern Recognition, 2010,43 ( 7 ) : 2456 - 2465.
  • 5Kimura F, Takashina K, Tsuruoka S, et al. Modified quadratic discriminate functions and its application to Chinese character recognition. IEEE Trans On Pattern Analysis and Machine Intelligence, 1987, 9( 1 ) : 149-153.
  • 6Fu Q, Ding X Q, Li T Z, et al. An effective and practical classifier fusion strategy for improving handwritten character recognition. In : Proceedings of the International Conference on Document Analysis and Recognition, Curitiba, Brazil, 2007. I038-I042.
  • 7Lin X F, Ding X Q, Chen M, et al. Adaptive confidence transform based classifier combination for Chinese character recognition. Pattern Recognition Letters, 1998, 19 (10) : 975-988.
  • 8Zhang H G, Guo J, Chen G, et al. HCL2000: a largescale handwritten Chinese character database for handwritten character recognition. In: Proceedings of the International Conference on Document Analysis and Recognition, Barcelona, Spain, 2009. 286-290.
  • 9Liu C L, Nakashima K, Sako H, et al. Handwritten digit recognition: investigation of normalization and feature extraction techniques. Pattern Recognition, 2004, 37 (2) : 265 -279.
  • 10Liu H L, Ding X Q. Handwritten character recognition using gradient feature and quadratic classifier with multiple discrimination schemes. In. Proceedings of the International Conference on Document Analysis and Recognition, Seoul, South Korea, 2005. 19-23.

相关作者

内容加载中请稍等...

相关机构

内容加载中请稍等...

相关主题

内容加载中请稍等...

浏览历史

内容加载中请稍等...
;
使用帮助 返回顶部