Human face recognition using Zernike moments and nearest neighbor classifier

A. J. Nor'aini, P. Raveendran, N. Selvanathan

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

11 Citations (Scopus)

Abstract

This paper presents a human face recognition system using an orthogonal invariant moment namely Zernike moment (ZM) as a feature extractor and a simple Euclidean square distance classifier or Nearest Neighbor. Changes in illumination condition, pose, facial expression and others are challenging task in recognizing face images. Solving these problems requires a feature extractor that can generate distinct features for each class of image and a classifier that able to recognize and classify the face image precisely. The experiments utilized database face images from Olivetti research laboratory (ORL) consisting of 40 subjects of 10 images each where none of them are identical [I]. They vary in position, rotation, scale, expression, with and without glasses. The performance of the classification depends on the moment order and classification error is observed below 10%.

Original languageEnglish
Title of host publicationSCOReD 2006 - Proceedings of 2006 4th Student Conference on Research and Development "Towards Enhancing Research Excellence in the Region"
Pages120-123
Number of pages4
DOIs
Publication statusPublished - 2006
Externally publishedYes
EventIEEE Student Conference on Research and Development (SCOReD) 2006 - Shah Alam, Malaysia
Duration: 27 Jun 200628 Jun 2006
Conference number: 4th
https://ieeexplore.ieee.org/xpl/conhome/4339287/proceeding (Proceedings)

Conference

ConferenceIEEE Student Conference on Research and Development (SCOReD) 2006
Abbreviated titleSCOReD 2006
Country/TerritoryMalaysia
CityShah Alam
Period27/06/0628/06/06
Internet address

Keywords

  • Euclidean square distance
  • Nearest neighbor
  • Orthogonal invariant moment
  • Zernike moments

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