ISSN (Print) : 2320 – 3765 ISSN (Online): 2278 – 8875 International Journal of Advanced Research in Electrical, Electronics and Instrumentation Engineering (An ISO 3297: 2007 Certified Organization) Vol. 4, I ssue 2, February 2015 Copyright to IJAREEIE 10.15662/ijareeie.2015.0402057 825 Human Eye Blink Detection using YCbCr Color Model, Haar-Like Features and Template Matching Sukhwinder Kaur 1 , Hari Singh 2 M. Tech. Student, Dept. of ECE DAV Institute of Engineering and Technology, Jalandhar, India 1 Assistant Professor, Dept. of ECE, DAV Institute of Engineering and Technology, Jalandhar, India 2 ABSTRACT: 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. KEYWORDS: Face localization, Eye localization, Eye blink detection, YCbCr Color models, Viola Jones, Morphological operations and Template matching. I.INTRODUCTION Paralysis is the complete loss of muscle function for one or more muscle groups. Paralysis can cause loss of feeling or mobility in the affected areas. Paralysis is most often caused by damage to the nervous system, especially the spinal cord [2]. Fully paralysed patients require 24 hour support. But, it is not possible for anyone to be available at all times. In this paper an improved efficiency of eye blink is given. Before starting work on eye blink we have to go through from some steps as shown in fig.1. There are some techniques devised for blink detection as well. This research work is to improve the efficiency of eye blink detection rate. Before doing work on eye blink we have to go through a survey as explained below. II. LITRATURE SURVEY Ijaz Khan, Hadi Abdullah et al [2013]: In this paper the author presents improved algorithms for face, eyes and mouth detection in an image. Viola Jones and skin color pixel detection as face detection techniques are widely used. Viola Jones gives accurate face detection but consumes more time whereas skin color pixel detection technique consumes less time but lacks in accuracy. Atish Udayashankar et al [2012]: The main aim of this paper is to design a real time interactive system that can assist the paralyzed to control appliances such as lights, fans etc. or by playing pre-recorded audio messages, through a predefined number of eye blinks. Image processing techniques have been implemented in order to detect the eye blinks. K Takahashi et al [2012]: This paper proposed a practical method for eye blink detection using a monocular system. Eye blink detection is an important technology in many situations such as facial action analysis and signal processing. However, automatic eye blink detection is quite difficult since the eye blink is occurred fast