Open/Closed Eye Analysis for Drowsiness Detection

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 an easy algorithm for pupil center and iris boundary localization and 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 eye detection algorithm uses Eye Map, thus achieving excellent pupil center and iris boundary localization results on the IMM database. Our novel eye state analysis algorithm detects eye state using the saturation (S) channel of the HSV color space. We analyze our eye state analysis algorithm using five video sequences and show superior results compared to the common technique based on distance between eyelids.