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Quaternion-based discriminant analysis method for color face recognition

  • Yong Xu*
  • *Corresponding author for this work
  • Harbin Institute of Technology Shenzhen
  • Key Laboratory of Network Oriented Intelligent Computation

Research output: Contribution to journalArticlepeer-review

Abstract

Pattern recognition techniques have been used to automatically recognize the objects, personal identities, predict the function of protein, the category of the cancer, identify lesion, perform product inspection, and so on. In this paper we propose a novel quaternion-based discriminant method. This method represents and classifies color images in a simple and mathematically tractable way. The proposed method is suitable for a large variety of real-world applications such as color face recognition and classification of the ground target shown in multispectrum remote images. This method first uses the quaternion number to denote the pixel in the color image and exploits a quaternion vector to represent the color image. This method then uses the linear discriminant analysis algorithm to transform the quaternion vector into a lower-dimensional quaternion vector and classifies it in this space. The experimental results show that the proposed method can obtain a very high accuracy for color face recognition.

Original languageEnglish
Article numbere43493
JournalPLOS ONE
Volume7
Issue number8
DOIs
StatePublished - 24 Aug 2012
Externally publishedYes

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 3 - Good Health and Well-being
    SDG 3 Good Health and Well-being

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