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...

Full description

Bibliographic Details
Main Authors: Abdulfattah, Ghassan Marwan (Author), Ahmad, Mohammad Nazir (Author)
Format: Article
Language:English
Published: Asian Research Publishing Network (ARPN), 2013.
Subjects:
Online Access:Get fulltext
LEADER 01324 am a22001453u 4500
001 49650
042 |a dc 
100 1 0 |a Abdulfattah, Ghassan Marwan  |e author 
700 1 0 |a Ahmad, Mohammad Nazir  |e author 
245 0 0 |a Face localization-based template matching approach using new similarity measurements 
260 |b Asian Research Publishing Network (ARPN),   |c 2013. 
856 |z Get fulltext  |u http://eprints.utm.my/id/eprint/49650/1/MohammadNazirAhmad2013_Facelocalization-basedtemplate.pdf 
520 |a 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% 
546 |a en 
650 0 4 |a QA76 Computer software