A Fast Identification Method of Human Eye State Based on Grid Region Segmentation and Threshold Adaptation

Abstract

The invention discloses a method for quickly identifying the human eye state based on grid area segmentation and threshold self-adaptation, using the Adaboost algorithm to locate the geometric area of ​​the human eye position, and using the grid thirds method to calibrate the eye pupil feature area; Adapt to the binarization algorithm for finding the best threshold for background image separation, and perform black and white enhancement processing on the images of the three eye regions; modify the standard relational formula for calculating pupil closure to one that introduces drift factors Relational formula; finally, based on the PERCLOS method, it is judged whether it is in a state of fatigue. The invention solves the problems caused by the driver's head rotation, frequent eye drift, pupil position changes and illumination changes, which cause the gray level changes of the eye images in the front and rear frames, which lead to the uncertainty of the image enhancement processing threshold. The accuracy of fatigue state recognition is not high, it occupies less computing resources and has high real-time performance.

Description

technical field [0001] The invention relates to a recognition method of human eye state, in particular to a fast recognition method of human eye state based on grid area segmentation and threshold value self-adaptation, and belongs to the technical field of image processing and pattern recognition. Background technique [0002] According to statistics from the National Highway Traffic Safety Administration of the United States, about 100,000 traffic accidents are caused by fatigue driving every year; according to the traffic accident statistics of the French National Police Agency, accidents caused by fatigue and drowsiness account for 14.9% of personal injury accidents and 20.6% of fatal accidents. %; On the expressways in Germany, 25% of personal injury accidents are caused by fatigue driving. With the continuous and rapid increase in the number of motor vehicles in my country, the mileage of highways opened to traffic increases year by year, and the pace of modern life is...

AI Technical Summary

Problems solved by technology

This invention has a large amount of calculation and uses edge images. When the edge features are not obvious due to head rotation and uneven illumination, the recognition accuracy is not high, and an effective edge detection algorithm is needed.

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