Eye Fatigue Prediction System Using Blink Detection Based on Eye Image

Today, information devices such as smartphones have become indispensable in our daily life. As a result, the increased use of information devices has led to the accumulation of eye strain and the development of various eye diseases. As the accumulation of eye-fatigue is manifested in the change in the number of blinks, blink detection technology is necessary. In the previous paper, we proposed a highly accurate blink detection method called EARM. However, there is a problem with this technique, which is that the noise generated by the movement of the face can reduce the accuracy of blink detection. In this study, we used face image normalization to improve the blink detection system by reducing the noise associated with face movement. We found that the proposed system outperformed the results of blink detection accuracy using EARM in all subjects.