Research Article Open Access

Eye Detection Using Composite Cross-Correlation

Kutiba Nanaa1, Mohamed Rizon2, Mohd Nordin Abd Rahman1, Ali Almejrad3, Azim Zaliha Abd Aziz1 and Saiful Bahri Mohamed2
  • 1 School of Computer Science, Faculty of Informatics and Computing, Malaysia
  • 2 School of Manufacturing Technology, Faculty of Design and Engineering Technology, Universiti Sultan Zainal Abidin (UniSZA), Terengganu, Malaysia
  • 3 Deparment of Biomedical Technology, College of Applied Medical Science, King Saud University, Riyadh, Saudi Arabia


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.

American Journal of Applied Sciences
Volume 10 No. 11, 2013, 1448-1456


Submitted On: 26 August 2013 Published On: 3 October 2013

How to Cite: Nanaa, K., Rizon, M., Rahman, M. N. A., Almejrad, A., Aziz, A. Z. A. & Mohamed, S. B. (2013). Eye Detection Using Composite Cross-Correlation. American Journal of Applied Sciences, 10(11), 1448-1456.

  • 7 Citations



  • Eye Detection
  • Template Matching
  • Cross Correlation
  • Facial Features
  • Pattern Recognition