Drowsiness Detection Based on Brightness and Numeral Features of Eye Image

Abstract

Drowsiness detection is vital in preventing traffic accidents. Eye state analysis-detecting whether the eye is open or closed-is critical step for drowsiness detection. In this paper, we propose a new algorithm for eye state analysis, which we incorporate into a four step system for drowsiness detection: face detection, eye detection, eye state analysis, and drowsy decision. This new system requires no training data at any step or special cameras. Our novel eye state analysis algorithm detects open, semi-open, and closed eye during two steps which is based on brightness and numeral features of the eye image. We analyze our eye state analysis algorithm using ten video sequences and show superior results compared to the common technique based on distance between eyelids.