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文章基本信息

  • 标题:Face Recognition based Texture Analysis Methods
  • 本地全文:下载
  • 作者:Marwa Y. Mohammed
  • 期刊名称:International Journal of Image, Graphics and Signal Processing
  • 印刷版ISSN:2074-9074
  • 电子版ISSN:2074-9082
  • 出版年度:2019
  • 卷号:11
  • 期号:7
  • 页码:1-8
  • DOI:10.5815/ijigsp.2019.07.01
  • 出版社:MECS Publisher
  • 摘要:A unimodal biometric system based Local Binary Pattern (LBP) and Gray Level Co-occurrence Matrix (GLCM) is developed to recognize the facial of 40 subjects. The matching process is implemented using three classifiers: Euclidean distance, Manhattan distance, and Cosine distance. The maximum accuracy (100%) is satisfied when GLCM and LBP are applied with Euclidean distance. The accuracy result of these two methods is advanced the Principle Component Analysis (PCA) and Fourier Descriptors (FDs) recognition rate. The ORL database is considered for constructing the proposed biometric system.
  • 关键词:Face recognition;LBP;GLCM;Euclidean distance;Cosine distance;Manhattan distance
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