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Eye state analysis is critical step for drowsiness detection. In this paper, we propose a robust algorithm for eye state analysis, which we incorporate into a system for driver’s drowsiness detection to extract micro-sleep periods. The proposed system begins by face extraction using Support Vector Machine (SVM) face detector then a new approach for eye state analysis based on Circular Hough Transform (CHT) is applied on eyes extracted regions. Finally, we proceed to drowsy decision. This new system requires no training data at any step or special cameras. The tests performed to evaluate our proposed driver’s drowsiness detection system using real video sequences acquired by low cost webcam, show that the algorithm provides good results and can work in real-time.

EYE STATE ANALYSIS USING IRIS DETECTION TO EXTRACT DRIVER’S MICRO-SLEEP PERIODS