Road traffic sign automatic identification and management system based on deep learning

Abstract

The invention provides a road traffic sign automatic identification and management system based on deep learning, wherein the system is used for the field of environment perception technology of a smart vehicle. The system comprises a traffic sign acquisition module, a traffic sign identification module and a traffic sign management module. The traffic sign acquisition module acquires a video which comprises the traffic sign and performs matching on each image frame and latitude-and-longitude of equipment in acquiring the image. The traffic sign identification module performs functions of processing the input image, performing positioning detection on the traffic sign, acquiring a candidate area which comprises the traffic sign, and performing classification identification on the traffic sign. The traffic sign management module transmits traffic sign and latitude-and-longitude information to a traffic management department, thereby determining whether placement of the traffic sign is reasonable and performing corresponding adjustment. The road traffic sign automatic identification and management system has advantages of large number of kinds of identified traffic signs, high precision, high real-time performance, etc. The road traffic sign automatic identification and management system further has beneficial effects of reducing effect of factors such as illumination change to image identification, improving interference resistance, and obtaining high identification accuracy and low error identification rate.

Description

technical field [0001] The invention relates to the field of environment perception technology and positioning and communication technology of smart cars, in particular to an automatic recognition and management system of road traffic signs based on deep learning, which is suitable for automobile auxiliary driving systems and traffic management departments. [0002] technical background [0003] With the progress of the society and the sustainable development of the economy, my country's highway transportation industry has been developing continuously and rapidly, and the circulation of automobiles is also increasing. Nowadays, there are many types of traffic signs and they are widely distributed geographically. Especially, the traffic signs set up in some places will need to be adjusted accordingly due to road maintenance, expansion, renovation or new house construction. Therefore, it is very necessary for the traffic management department to regularly adjust and update the ...

AI Technical Summary

Problems solved by technology

In actual work, the traffic signs in the images captured by the camera have different degrees of projection distortion, such as regular triangles into general shape triangles, circles into ellipses, and traffic signs may be partially damaged. The classification accuracy of this method is may drop

Some scholars use the traffic sign recognition method of Gabor wavelet and support vector machine. This method is not sensitive to lighting conditions, but the recognition rate is not good when the traffic sign is rotated or scaled.

[0006] In natural scenes, factors such as illumination changes, color fading, blur caused by motion, complex background, partial occlusion, etc., bring great challenges to the automatic detection and recognition of traffic signs

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