Automatic Eye Blink Generation and Detection System in Digital Image Processing

The eyes are tracked and correlation scores between the actual eye and the corresponding “closed-eye” template are used to detect blinks. However, it requires offline training for different depths from the camera for the computation of the distance. In addition, the system requires initialization in which an Eye blinking is one of the prominent areas to solve many real world problems. The process of blink detection consists of two phases. These are eye tracking followed by detection of blink. The work that has been carried out for eye tracking only is not suitable for eye blink detection. Stored template for a particular depth is chosen. Once the template is chosen and the system is in operation, the subject will be restricted to be at the specified distance. Another disadvantage of the system is that changing camera Positions require the whole system to be retrained. Further more. The same system in lay not be as effective if it were used on people of different races with disparate eye sizes and distance between the eyes. Therefore some approaches had been proposed for eye tracking along with eyes blink detection. This paper implements one of the approaches given by Michael et al [1,2,3]. The result of template creation accuracy and total blink detection to count number of eye blinks in an image sequence. Online template is completely independent of any past templates that may have been created during the run of the system. At last after analyzing all these approaches some of the parameters we obtained on which better performance of eye blink detection algorithm depend. Keywordstemplate, frames, Interface, testing, automatically, involuntary.