A novel nonlinear feature extraction and recognition approach based on improved 2D Fisherface plus Kernel discriminant analysis

Yong Fang Yao, Sheng Li, Zhu Li Shao, Xiao Yuan Jing, Dapeng Zhang, Jing Yu Yang

Research output: Chapter in book / Conference proceedingConference article published in proceeding or bookAcademic researchpeer-review

Abstract

A novel nonlinear feature extraction and recognition approach which is based on improved 2D Fisherface plus Kernel discriminant analysis is proposed. We provide an improved 2D Fisherface method that designs a new strategy to select appropriate 2D principal components and discriminant vectors, then we use 2D features to perform the Kernel discriminant analysis. The nearest neighbor classifier with cosine distance measure is adopted in classifying the nonlinear discriminant features. The experiments show that the proposed approach achieves better recognition results than several representative discriminant methods.
Original languageEnglish
Title of host publicationProceedings - 2008 2nd International Symposium on Intelligent Information Technology Application, IITA 2008
Pages333-337
Number of pages5
Volume3
DOIs
Publication statusPublished - 1 Dec 2008
Event2008 2nd International Symposium on Intelligent Information Technology Application, IITA 2008 - Shanghai, China
Duration: 21 Dec 200822 Dec 2008

Conference

Conference2008 2nd International Symposium on Intelligent Information Technology Application, IITA 2008
CountryChina
CityShanghai
Period21/12/0822/12/08

ASJC Scopus subject areas

  • Computer Science Applications
  • Information Systems and Management

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