基于RBF神经网络的汽车危驾限制系统研究

Study on Limited System of Illegally Driving Car Based on RBF Neural Network

针对汽车的危驾问题,给出了危驾检测限制系统.此危驾检测限制系统包括人脸摄像电路、红外检测器和系统控制电路等,算法上采用RBF神经网络算法.MATLAB仿真表明,其识别率可达95%以上.相比较其他人脸检测方法,本系统具有结构简单、成本低的特点.

In order to resolving illegally driving problem, illegally driving limit detection system is studied. This violation of driving restriction system including face detection circuit cameras, infrared detectors and system control circuit and other circuits. RBF neural network algorithm is introduced on the algorithm in detail. The simulation showed that the recognition rate is still more than 95%. Compared to other methods, the system has a simple structure and low cost.