American Journal of Applied Sciences

Eye Detection Using Composite Cross-Correlation

Kutiba Nanaa, Mohamed Rizon, Mohd Nordin Abd Rahman, Ali Almejrad, Azim Zaliha Abd Aziz and Saiful Bahri Mohamed

DOI : 10.3844/ajassp.2013.1448.1456

American Journal of Applied Sciences

Volume 10, Issue 11

Pages 1448-1456

Abstract

This study presents a new eye detection method depending on composite template matching for facial images. The objective of this study is to utilize template match method to detect the eyes from given images and to improve this method to obtain higher rate of detection. The idea of our method is to integrate cross correlations of various eye templates. Thus, the correct values of single template matching based eye detection dominated the final output. It also contributed to the re-correct the detection in the event of failure of all single templates. The study also presents a method to obtain candidate eye pixels which contribute to abbreviate the time required to implement up to 91%. The formula of composite cross correlation has been generalized taking into account the differences between the sizes, shifts and irregular single templates. The experiments applied on PICS database reported 98.76% as eye detection rate.

Copyright

© 2013 Kutiba Nanaa, Mohamed Rizon, Mohd Nordin Abd Rahman, Ali Almejrad, Azim Zaliha Abd Aziz and Saiful Bahri Mohamed. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.