Recognition of Eye States in Real Time Video

A composite algorithm is proposed to identify the opened and shut states of eye in real-time video. Sequentially, each frame of the video is processed first to find and separate the eye regions; then, the accumulation array of circular Hough transform is applied for detecting circles to recognize the opened state of the eye, and the upper eyelid curve is cal-culated to identify its bending direction to recognize the shut state; after that, if the state cannot be determined yet, judging by the standard deviation of distance between eyelids, the eye state of blinking is determined finally. An accuracy of 94% for eye state detection is obtained in our experiments by using the proposed algorithm. As an important part, the algorithm is going to be utilized in a fatigue warning system for drivers.