Abstract
Eye and mouth state analysis is an important step in fatigue detection. An algorithm that analyzes the state of the eye and mouth by extracting contour features is proposed. First, the face area is detected in the acquired image database. Then, the eyes are located by an EyeMap algorithm through a clustering method to extract the sclera-fitting eye contour and calculate the contour aspect ratio. In addition, an effective algorithm is proposed to solve the problem of contour fitting when the human eye is affected by strabismus. Meanwhile, the value of chromatism s is defined in the RGB space, and the mouth is accurately located through lip segmentation. Based on the color difference of the lip, skin, and internal mouth, the internal mouth contour can be fitted to analyze the opening state of mouth; at the same time, another unique and effective yawning judgment mechanism is considered to determine whether the driver is tired. This paper is based on the three different databases to evaluate the performance of the proposed algorithm, and it does not need training with high calculation efficiency.
Highlights
In recent years, driver fatigue has become one of the most important factors for traffic accidents, which has come at a great cost to the safety and property of drivers and pedestrians
PERCLOS is the abbreviation of percentage of eyelid closure over the pupil over time, which is the percentage of the closing time of the eye over a specific period of time
Ji et al.: Eye and mouth state detection algorithm based on contour feature extraction we use the algorithm of Ref. 21 for color compensation
Summary
Driver fatigue has become one of the most important factors for traffic accidents, which has come at a great cost to the safety and property of drivers and pedestrians. Researchers have proposed many fatigue detection methods to solve this problem, which can be divided into three types: 1 physiological parameters, vehicle behaviors, and facial feature analysis. The first method measures the driver’s physiological parameters[2,3,4,5,6] by using tools such as electroencephalogram and electrocardiogram. PERCLOS is the abbreviation of percentage of eyelid closure over the pupil over time, which is the percentage of the closing time of the eye over a specific period of time. This method is noninvasive and easy to implement and is applied to the fatigue detection in this paper.
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