| With the high development of the highway and the quick increase of the number of people having car, the number of traffic accidents are increasing obviously. It is reported by Ministry of Communications that both absolute number and proportion of our country's traffic accidents are highest in the world. Since accident doesn't happen as soon as fatigue takes place, real time fatigue detection system is absolutely necessary. Therefore, how to supervise and avoid fatigue driving efficiently is one of the significant problems.Some organizations do the reseach of detecting drowsy driver, some methods of detecting drowsy driver by far are: 1. Using head position sensor to detect fatigue.While, the character of head moving is not well related to fatigue, so the accuracy rate is not high. 2. Measure pupil size: estimating the degree of fatigue by measuring the change of pupil diameter.It is not a real-time method, and the driver has to wear a special equipment.So, it is only used to estimate the trend of sleepiness. 3. Using EEG to measure the level of fatigue: it is the earliest method of detecting the fatigue, but it requires installing electrodes to the subject, which take great pale of psychological and physiological burden to them.It is lack of practice. 4 Using the eye closure to detect drowsiness, which has been proved to be the most effective character.In this thesis, we investigate and contrast the principles of current methods and technologies for driver fatigue detection, and analyze the key problems and difficulties of these techniques, propose a quick and effective driver fatigue method based on computer vision, and establish a real-time driver fatigue detection platform of DSP. It can capture, process and display the image in real time. Further more, the system canobtain the eye feature which is used to estimate the fatigue.The main contents of this thesis are as follows: 1 Analyse the key technique and difficulties of detecting system home and abroad,discuss the principle deeply, based on our analysing the detecting methods we find that the driving body feature detecting is objective, exact and practical, propose a novel and practical fatigue detecting system.2 Describe the hardware of fatigue detecting system, use TMS320DM642 of TI company as processing chip, TVP5150 and SAA7121 as video decoder and encoder, TL16C752B as dual universal asynchronism receiver/transmitter and other periphery chips composing the whole hardware system.3 Introduce the system intialization, DSP/BIOS startup and bottom driver such as video driver and UART driver, which can intialize the hardware registers and whole system to be ready for lasting work such as loading program, realizing algorithm and so on.4 Analyse the algorithm detailedly, using skin distribution and background update to locate face, tracking reflection point method under infrared to track and locate eyes, Kalman filter to estimate the location of reflection point and eye-closed state, stable point mothed to solve eye-closed state, threshold division to obtain the pupil image, accumulated histogram to binarize eye area, space gridding method to control pan-and-tile movement, the relativity between fatigue physiological character and fatigue to judge fatigue degree to prove the method validity. |
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