Bright Pupil Detection in an Embedded, Real-time Drowsiness Monitoring System

Driver’s drowsiness is stated as an important cause of road and highway accidents. Therefore, the development of a system for monitoring the driver’s level of fatigue is desirable in order to prevent accidents. The paper presents the design and the implementation of a system able to find and evidence the drowsiness level of a driver in an ordinary motor vehicle, in order to prevent car accidents. The system, made up of a car installed infrared video camera connected to the Celoxica RC203E FPGA based board, is able to perform a real time video stream processing. The system exploits the “bright pupil” phenomenon produced by the retina, that reflects the 90% of the incident light when a radiation of 850 nm wavelength hit the retina itself. While acquiring the video, a processing chain is executed to detect driver’s eyes and to compute a PERCLOS (Percentage of Eye Closure) function linked to the drowsiness level of a driver. The achieved experimental results show that an entire 720*576 frame processing requires only 16.7ms, so that the system is able to perform real-time PAL video stream processing and has the potentiality to process 60 frames/sec. The effectiveness of the proposed drowsiness detection system has been successfully tested with a human subject in real operating condition, tracking driver’s eyes and detecting drowsiness failures.