Fatigue driving monitoring device and method

Abstract

The present invention provides a device and method for monitoring fatigue driving. The method includes: 1) Obtaining the collected image; 2) Transforming the collected image into YCbCr space, extracting the skin color area and performing binarization, and obtaining a rectangular frame of the face ;3) Scan the pixels in the rectangular frame of the face, and use it as the center of the circle, increase the radius until the pixels in the scanning area exceeding the preset ratio are white points or the scanning area reaches the boundary of the rectangular frame, and the scanning ends. The diameter of the largest scanning area is the diameter of the pupil; 4) By monitoring the pupil size in real time, it is judged whether the driver is fatigued according to the PERCLOS algorithm. The invention can quickly, simply and accurately frame a rectangular human face frame in the YCbCr space, and then detect the fatigue state of the driver through real-time monitoring of the pupil size combined with the PERCLOS fatigue detection method. The invention is simple and efficient, has fast operation speed and high accuracy, and the monitoring process and results are not affected by the inclination angle of the human face.

Description

technical field [0001] The invention relates to the field of face detection technology and fatigue driving detection technology based on eye fatigue feature detection, in particular to a fatigue driving monitoring device and method. Background technique [0002] The 2013 "Global Road Safety Status Report" shows that traffic accidents are the eighth leading cause of death in the world. About 1 million people die in traffic accidents every year in the world. Further statistical analysis shows that fatigue driving is the It is one of the important causes of traffic accidents, so it is necessary to detect and alarm fatigue. [0003] Methods for detecting drowsy driving can be broadly classified into three categories: [0004] 1. Based on the detection of vehicle driving status, such as detecting whether the vehicle deviates from the driving track; [0005] 2. Detection based on the driver's physiological parameters, such as the detection of the driver's EEG, ECG, etc.; [000...

AI Technical Summary

Problems solved by technology

[0011] However, the general face detection algorithm is more complicated, and the real-time performance is not so good, especially when the face is tilted at a relatively large angle.

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