Automatic face recognition using principal component analysis and neural network

Mirabeau Nguela, Zenghui Wang, Yanxia Sun

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

Automatic face recognition is a very important research area in computer science since it has been widely used in security systems. It has drawn a lot of attention in the recent ten years from the scientific communities with the aim to provide highly intelligent human-machine interaction with high performance. This paper proposes an automatic face recognition method that encompasses a reduction of significant variable features using the principal components analysis and classification method through Neural Network. The experimental results obtained show an improvement in term of recognition rate compared with the existing method.

Original languageEnglish
Title of host publication2017 7th International Workshop on Computer Science and Engineering, WCSE 2017
PublisherInternational Workshop on Computer Science and Engineering (WCSE)
Pages272-277
Number of pages6
ISBN (Electronic)9789811136719
Publication statusPublished - 2017
Event2017 7th International Workshop on Computer Science and Engineering, WCSE 2017 - Beijing, China
Duration: 25 Jun 201727 Jun 2017

Publication series

Name2017 7th International Workshop on Computer Science and Engineering, WCSE 2017

Conference

Conference2017 7th International Workshop on Computer Science and Engineering, WCSE 2017
Country/TerritoryChina
CityBeijing
Period25/06/1727/06/17

Keywords

  • Covariance matrix
  • Eigenvalues and eigenvectors
  • Feed forward network
  • Neural network
  • Principal component analysis

ASJC Scopus subject areas

  • Information Systems and Management
  • Computer Science Applications
  • Signal Processing
  • Computer Networks and Communications
  • Software

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