Research On The Detection System Of Eye Information Based On Embedded

According to statistical analysis,fatigue driving is one of the main reasons that caused traffic accidents, so detecting driver fatigue timely and effectively and reduce the traffic accident caused by driver fatigue has important practical significance. Real-time collecting driver's images through CCD camera, this paper designs a detection system of eye information based on the TMS320DM642 DSP chip. The system is used to detect driver fatigue.This paper mainly research on the eye location, eye tracking and eye state recognition in detection system and theirs algorithm implementation in the DSP. First skin color face detection algorithm based on blob analysis was proposed, which can remove the background noise whose color is similar to human skin effectively; Then to locate eye, locating eyes accurately using gray projection algorithm and modified Hough transform; In the eye tracking, using iris tracking and the template matching algorithm based on Kalman prediction to tracking eyes real-time; In the eye state recognition, the method of combining Gabor transform extracting eye characteristic and SVM was proposed to recognizing eye state, open or closed; finally using PERCLOS and AECS parameters to detect driver fatigue.This paper use C language to program and debug in the CCS environment based on the theoretical study and SEED-DM642 system development platform. The experiment results show that the system can locate the eye and recognize eye state quickly and accurately, so it can detect drowsiness effectively.