Algorithm design and hardware implementation of driver fatigue monitoring

作者：Jiang, Siyu^*; Wu, Bin; Qiu, Shaojian; Yang, Meijun

来源：Journal of Harbin Institute of Technology, 2014, 46(5): 95-100.

• DM642
• Driver fatigue monitoring
• Hardware implementations
• Installation position
• Online identify
• Pulse coupled neural network
• Pulse neural network
• Training sample

To reduce the loss of people's property caused by traffic accidents because of driver fatigue, a new driver fatigue monitoring method based on non-contact is proposed. First, a camera gets driver's facial image, and then by using online method of identifying to identify the driver's facial features after pre-processing, the fatigue state of the driver can be acquired. Hardware system including TMS320DM642 as the core processor will alarm when driver is fatigue. Experimental results show that the use of pulse coupled neural network method to enhance and identify image, can determine the area of face and eye effectively, the master chip TMS320DM642 meets the requirement of detection distance between 30 cm and 150 cm when camera focal length is 8 mm. Coupled pulse neural network method has high reliability in driver fatigue detection, and choosing the right hardware platform and installation position have important influences on the detection results.

• 出版日期2014-5
• 单位华南理工大学