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Face recognition with discrete cosine transform

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

Abstract

Face recognition has been a hot issue of concern to people, existing algorithms mainly for how to improve face recognition accuracy, and reduce the use of the feature vector dimension. A face recognition method based on the discrete cosine transform and SVM-based feature classification is presented. Face Recognition on the DCT coefficients as feature vectors in the problem of effective choice. In the training process of SVM, the training sample is divided into two parts, one part of the training samples using the test results of feature selection, and use the resulting accuracy rate as the feature selection criteria, the proposed algorithm on ORL face image standard library of verified experiments, and achieved good results prove the effective and reliable.

Original languageEnglish
Title of host publicationProceedings of the 2012 2nd International Conference on Instrumentation and Measurement, Computer, Communication and Control, IMCCC 2012
Pages802-805
Number of pages4
DOIs
StatePublished - 2012
Event2012 2nd International Conference on Instrumentation and Measurement, Computer, Communication and Control, IMCCC 2012 - Harbin, Heilongjiang, China
Duration: 8 Dec 201210 Dec 2012

Publication series

NameProceedings of the 2012 2nd International Conference on Instrumentation and Measurement, Computer, Communication and Control, IMCCC 2012

Conference

Conference2012 2nd International Conference on Instrumentation and Measurement, Computer, Communication and Control, IMCCC 2012
Country/TerritoryChina
CityHarbin, Heilongjiang
Period8/12/1210/12/12

Keywords

  • Discrete cosine transform
  • Face recognition
  • Support vector machine

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