Vision-based human face recognition using extended principal component analysis

A. F M Saifuddin Saif, Anton Satria Prabuwono, Zainal Rasyid Mahayuddin, Teddy Mantoro

Research output: Contribution to journalArticle

1 Citation (Scopus)

Abstract

Face recognition has been used in various applications where personal identification is required. Other methods of person's identification and verification such as iris scan and finger print scan require high quality and costly equipment. The objective of this research is to present an extended principal component analysis model to recognize a person by comparing the characteristics of the face to those of new individuals for different dimension of face image. The main focus of this research is on frontal two dimensional images that are taken in a controlled environment i.e. the illumination and the background is constant. This research requires a normal camera giving a 2-D frontal image of the person that will be used for the process of the human face recognition. An Extended Principal Component Analysis (EPCA) technique has been used in the proposed model of face recognition. Based on the experimental results it is expected that proposed the EPCA performs well for different face images when a huge number of training images increases computation complexity in the database.

Original languageEnglish
Pages (from-to)82-94
Number of pages13
JournalInternational Journal of Mobile Computing and Multimedia Communications
Volume5
Issue number4
DOIs
Publication statusPublished - 2013

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Face recognition
Principal component analysis
Lighting
Cameras

Keywords

  • Classification
  • Computer vision
  • Extended principal component analysis (EPCA)
  • Face recognition
  • Personal identification

ASJC Scopus subject areas

  • Computer Networks and Communications

Cite this

Vision-based human face recognition using extended principal component analysis. / Saif, A. F M Saifuddin; Prabuwono, Anton Satria; Mahayuddin, Zainal Rasyid; Mantoro, Teddy.

In: International Journal of Mobile Computing and Multimedia Communications, Vol. 5, No. 4, 2013, p. 82-94.

Research output: Contribution to journalArticle

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