Abstract:  In order to recognize the fatigue state accurately under the condition of the driver wearing glasses, a
method of judging whether to wear glasses is proposed. And the fatigue detection system based on the state of
eyes and mouth is established. Its applied algorithms such as moving object detection, feature extraction and
image recognition and etc are investigated. First, face classifier based on Adaboost algorithm is used to detect
face region from the video frames. The area of eyes and mouth can be detect roughly according to the facial
geometric distribution rules; Secondly, threshold adaptively by Otsu’s method and determine whether driver wear
glasses based on horizontal integral projection method. Then, identify the state of eyes with galsses according to
the method of histogram part statistics characteristic values. In addition, using roundness to judge whether mouth
yawn. Finally, the equivalent PERCLOS(Percentage of Eyelid Closure over the Pupil) value is taken to identify
the fatigue state of eyes, and the frequency of yawning is used to identify the fatigue state of mouth. The system
give an early warning in time when it detects fatigue driving. The experimental results show that these method
can solve the interference of glasses effectively, and is appropriate for different illumination and surroundings.
The accuracy is 95. 8%. It’s better than the method which only use eye or mouth. It can also satisfy the system
requirements of real time, accuracy and robustness.

Key words: glasses judgment, histogram feature,  fatigue detection, state recognition