Detecting Eye-Direction Using Afterimage and Ocular Movement

A support application for physically handicapped children to communicate with others by blinks is studied in this paper. OpenCv was used to detect an eye area. The method using saturation and using complexity of image are combined to get more accurate results to detect blinks. The technique is developed into a communication application that has the accurate and high precision blink determination system to detect letters. This devise can also put the words into sound. This blink detection method is used to develop the non-contact communication support tool that judges the eye direction by ocular movement. Combination of blink determination and detecting gaze detraction made it possible to choose letters remarkably fast and acclate. Furthermore, the vibration of the center point of the eyes is digitized by the comparison with the afterimage and middle point of the amount of change with scatter diagram is replaced to distinguish the state of an user. In future study, association with fatigue degree, sleep shortage and an intensive degree and the blurring of the eyeball vibration of right and left can be found using neural network.