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A combined eye states identification method for detection of driver fatigue

机译:用于驾驶员疲劳检测的组合式眼睛状态识别方法

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For driver fatigue detection system, the correct identification of open and shut eye states matters much to the subsequent calculation of driver fatigue degree. A combined eye state detection algorithm is proposed after a detailed introduction of three algorithms: template matching recognition, upper eyelid curvature calculation, and projection for closed eye detection. First the algorithm of template matching recognition is used as the main method to identify the eye states. Then, before outputting the final result, with an advanced threshold, some images would have a second or third detection for eye states by the use of upper eyelid curvature calculation and projection for closed eye detection. An accuracy of 95.67% for eye states identification in our experiments shows that this algorithm is time saving and robust to illumination and has good prospect of application in a fatigue warning system for drivers.
机译:对于驾驶员疲劳检测系统,正确识别睁眼和闭眼状态对驾驶员疲劳程度的后续计算非常重要。在详细介绍以下三种算法后,提出了一种组合式眼睛状态检测算法:模板匹配识别,上眼睑曲率计算和用于闭眼检测的投影。首先,将模板匹配识别算法用作识别眼睛状态的主要方法。然后,在输出具有高级阈值的最终结果之前,某些图像将通过使用上眼睑曲率计算和投影用于闭眼检测来对眼睛状态进行第二次或第三次检测。在我们的实验中,用于眼睛状态识别的准确率为95.67%,表明该算法省时且对照明具有鲁棒性,在驾驶员疲劳预警系统中具有良好的应用前景。

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