Fast Calculation for Fisher Criteria in Small Sample Size Problem

Wei Shi Zheng, Jian Huang Lai, Pong Chi Yuen

Research output: Chapter in book/report/conference proceedingConference proceedingpeer-review

Abstract

LDA is popularly used in the pattern recognition field. Unfortunately LDA always confronts the small sample size problem (S3), which leads the within-class scatter matrix to be singular. In this case, PCA is always used for dimensional reduction to solve the problem in practice. This paper analyzes that when the small sample size problem happens, the PCA processing is not only to play the role of solving the S3 problem but also can be used to induce a fast calculation algorithm for solving the fisher criteria. This paper will show that calculating the eigenvectors of within-class scatter matrix after dimensional reduction can solve the optimal projection for fisher criteria.

Original languageEnglish
Title of host publicationAdvances in Biometric Person Authentication
Subtitle of host publication5th Chinese Conference on Biometric Recognition, SINOBIOMETRICS 2004, Guangzhou, China, December 13-14, 2004, Proceedings
EditorsStan Z. Li, Jianhuang Lai, Tieniu Tan, Guocan Feng, Yunhong Wang
Place of PublicationBerlin, Heidelberg
PublisherSpringer
Pages330-338
Number of pages9
Edition1st
ISBN (Electronic)9783540305484
ISBN (Print)9783540240297
DOIs
Publication statusPublished - 29 Nov 2004
Event5th Chinese Conference on Biometric Recognition, SINOBIOMETRICS 2004 - Guangzhou, China
Duration: 13 Dec 200414 Dec 2004
https://link.springer.com/book/10.1007/b104239

Publication series

NameLecture Notes in Computer Science
PublisherSpringer
Volume3338
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349
NameSINOBIOMETRICS: Chinese Conference on Biometric Recognition

Conference

Conference5th Chinese Conference on Biometric Recognition, SINOBIOMETRICS 2004
Country/TerritoryChina
CityGuangzhou
Period13/12/0414/12/04
Internet address

Scopus Subject Areas

  • Theoretical Computer Science
  • Computer Science(all)

User-Defined Keywords

  • Face Recognition
  • Linear Discriminant Analysis
  • Scatter Matrix
  • Optimal Projection
  • Fisher Criterion

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