Face localization-based template matching approach using new similarity measurements

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 p...

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Bibliographic Details
Main Authors: Abdulfattah, Ghassan Marwan, Ahmad, Mohammad Nazir
Format: Article
Language:English
Published: Asian Research Publishing Network (ARPN) 2013
Subjects:
Online Access:http://eprints.utm.my/id/eprint/49650/1/MohammadNazirAhmad2013_Facelocalization-basedtemplate.pdf
http://eprints.utm.my/id/eprint/49650/
http://www.jatit.org
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Summary: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%