A novel face recognition system using hybrid neural and dual eigenspaces methods

Dapeng Zhang, Hui Peng, Jie Zhou, Sankar K. Pal

Research output: Journal article publicationJournal articleAcademic researchpeer-review

20 Citations (Scopus)

Abstract

In this paper, we present an automated face recognition (AFR) system that contains two components: eye detection and face recognition. Based on invariant radial basis function (IRBF) networks and knowledge rules of facial topology, a hybrid neural method is proposed to localize human eyes and segment the face region from a scene. A dual eigenspaces method (DEM) is then developed to extract algebraic features of the face and perform the recognition task with a two-layer minimum distance classifier. Experimental results illustrate that the proposed system is effective and robust.
Original languageEnglish
Pages (from-to)787-793
Number of pages7
JournalIEEE Transactions on Systems, Man, and Cybernetics Part A:Systems and Humans.
Volume32
Issue number6
DOIs
Publication statusPublished - 1 Nov 2002

Keywords

  • Dual eigenspaces method
  • Eyes detection
  • Face recognition
  • Hybrid neural method

ASJC Scopus subject areas

  • Software
  • Control and Systems Engineering
  • Human-Computer Interaction
  • Computer Science Applications
  • Electrical and Electronic Engineering

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