눈과 입 개폐의 상태검출을 통한 운전자의 졸음판단 분석

Abstract

In this paper, we propose an analysis method of drowsiness status of a driver from the opening and closing of eye and mouth. For this purpose, eyes, nose and mouth are detected to improve the area of interest using the spatial correlation in the existing Viola-Jones algorithm. Then, histogram equalization is performed for detection at night driving, and drowsiness status of the driver data with the accumulation value through opening and closing of eye and mouth using SVM (Support Vector Machine) and PERCLOS (Percentage Closure of Eyes). The experimental result using Caltect face database showed that the detection rate of two eyes and nose were increased by about 3% and 13.78%, respectively. Experimental results were confirmed that the performance of drowsiness through the opening and closing of the eyes was 90.72% and the performance of state through the opening and closing of the mouth was 98.26%.