Research On Recognition Method Of Rural Highway Traffic Signs Based On Machine Vision In Weak Illumination

Traffic sign recognition based on machine vision is an important part of intelligent transportation system and auxiliary driving system.The main function of the traffic sign is to prompt the road user information,the potential danger of the road,to avoid the occurrence of traffic accidents.Many experts and scholars at home and abroad have carried out in-depth research on the identification of traffic signs,but have encountered many difficulties due to complex environmental factors such as occlusion,color degradation and shadows.There have been some shortcomings in the research process.Based on the research of the detection,extraction and identification of road traffic signs based on machine vision,this paper puts forward the method of detecting and recognizing traffic signs under weak light conditions.The main research direction of this paper is the detection and identification of traffic signs.Firstly,the traffic signs are reclassified from the color and shape characteristics of traffic signs,the concept of color shape pairs is put forward,and the color-geometric model is established.We study the traffic signs collected under weak light conditions,and get the algorithm of image enhancement processing.The main research contents are as follows:Firstly,the image is preprocessed by the uniformity of the histogram to achieve the enhancement effect of the image.Then,the image is reconstructed by inverse filtering and Wiener filtering The image recovery,and finally the Gaussian filter processing.The RGB color image detection and the edge detection based on the shape feature are studied,and the color and shape features are tested to detect the type of traffic signs more effectively.Using MATLAB to carry out the traffic sign detection experiment,the detection rate,false detection rate and missed rate of traffic signs under weak light,good light and rainy weather were obtained.In this paper,we mainly use the fast algorithm of invariant moments and Zernike moments to extract the texture of texture and image.The main research traffic sign image recognition technology is template matching and support vector machine.Experiments show that the algorithm has good effect on image recognition.In this paper,we study the image tag processing technology.Will be identified in the previous traffic signs on the Google Earth to mark,and then save and promote,effectively reducing the potential violations.The experimental results show that it has good robustness in complex environments such as weak light,occlusion and shadow,and has high detection rate,which can improve the recognition rate of image effectively.