Abstrakt

Human Eye Blink Detection using YCbCr Color Model, Haar-Like Features and Template Matching

Sukhwinder Kaur, Hari Singh

This paper presents comparison of two image processing algorithms used for eye blink detection. The motivation of this research work is the need of disabled persons who are unable to move their body parts except eyes. The process of blink detection is divided into three parts viz.face localization, eye pair localization and template matching method. In method 1, YCbCr color model and morphological operations are used for the face and eyes localization. In method 2 face and eyes pair localization is performed by using Viola Jones method. After eye pair localization, the concept of template matching is applied for blink detection, in both the methods. A performance comparison is made for both the methods based upon detection accuracy and processing time. It is observed that method 1, gives better accuracy (80.75%) with low processing time (0.38sec.). The overall success rate of method 1 and method 2 is 71% and55% respectively.