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  • 标题:FACE LOCALIZATION-BASED TEMPLATE MATCHING APPROACH USING NEW SIMILARITY MEASUREMENTS
  • 本地全文:下载
  • 作者:GHASSAN MARWAN ABDULFATTAH ; MOHAMMAD NAZIR AHMAD
  • 期刊名称:Journal of Theoretical and Applied Information Technology
  • 印刷版ISSN:1992-8645
  • 电子版ISSN:1817-3195
  • 出版年度:2013
  • 卷号:57
  • 期号:3
  • 出版社:Journal of Theoretical and Applied
  • 摘要:In this paper, a number of similarity measurements have been developed, namely: Sum of Absolute Difference (OSAD), Sum of Square Difference (SSD) and Normalized Cross Correlation (NCC) in order to measure the correlation between the input image and the template image. In addition, two metrics were proposed, specifically: Sum Square T-distribution Normalized (SSTN) and Chi-Square distribution (Chi2) by which to measure matching between the two images. The result showed that optimized measurements overcome any drawbacks of NCC. Moreover, our results show SSTN and Chi2 as having the highest performance compared with other measurements. Sets of faces including: Yale, MIT-CBCL, BioID, Indian and Caltech were used to evaluate our techniques with success localization accuracy of up to 100%.
  • 关键词:Face Localization; Template Matching; Similarity Measurements
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