Advertisement

An Indirect and Efficient Approach for Solving Uncorrelated Optimal Discriminant Vectors

  • Quan-Sen Sun
  • Zhong Jin
  • Pheng-Ann Heng
  • De-Shen Xia
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4114)

Abstract

An approach for solving uncorrelated optimal discriminant vectors (UODV), called indirect uncorrelated linear discriminant analysis(IULDA), is proposed. This is done by establishing a relation between canonical correlation analysis (CCA) and Fisher linear discriminant analysis(FLDA). The advantages of our method for solving the UODV over the two existing methods are analyzed theoretically. Experimental result based on the Concordia University CENPARMI handwritten character database has shown that our algorithm can increase the recognition rate and the speed of feature extraction.

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Quan-Sen Sun
    • 1
  • Zhong Jin
    • 1
  • Pheng-Ann Heng
    • 2
  • De-Shen Xia
    • 1
  1. 1.Department of Computer Science, Nanjing University of Science &Technology, Nanjing 210094China
  2. 2.Department of Computer Science and Engineering, The Chinese University of Hong KongHong Kong

Personalised recommendations