Road traffic sign recognition method

Abstract

The invention discloses a road traffic sign recognition method, and the method comprises the steps: constructing a deep convolution neural network, selecting a traffic standard database and a trafficsign image collected on site, carrying out the training and testing of the constructed deep convolution neural network, and obtaining the trained deep convolution neural network; collecting a real-time traffic sign image; adding a traffic sign position distribution priori knowledge to an Itti model, so as to adjust the collected traffic sign image; carrying out the brightness equalization and color enhancement, and then extracting an AOI of the traffic signal through an MSER algorithm; inputting the AOI into the trained deep convolution neural network for convolution and pooling processing, and obtaining a one-dimensional feature vector; completing the recognition of the one-dimensional feature vector through a full-connection BP neural network, outputting a recognition result, and carrying out the real-time display and broadcasting. According to the invention, the method can accurately recognize various types of collected traffic signs, and achieves the timely prompt of a driver through texts or voice so that the driver takes corresponding action.

Description

technical field [0001] The invention relates to the fields of image processing and intelligent transportation, in particular to a road traffic sign recognition method for an assisted driving system. Background technique [0002] In recent years, with the sharp increase in the number of cars in my country, the occurrence of vehicle traffic accidents has shown a rising trend, and traffic safety has become an increasingly serious social problem. Therefore, real-time understanding of the traffic environment is very important for vehicle driving safety. The traffic sign recognition (Traffic Sign Recognition, TSR) in the car safety assisted driving system is to collect and recognize the traffic signs that appear on the road ahead during driving, and provide the results to the driver through text or voice information in real time. judging system. Therefore, as an important part of the assisted driving system, TSR can effectively improve the driving safety of the vehicle, thereby r...

AI Technical Summary

Problems solved by technology

However, most of the current TSR prompt information is obtained through map data, and most of them are to recognize traffic signs in static images. Second, during the driving process of the vehicle, the acquisition of traffic signs is affected by factors such as motion blur, background interference and light changes, and the quality of the obtained images is often not high, which seriously affects the recognition rate and recognition speed. Therefore, TSR is one of the key technologies in the field of current automotive safety assisted driving system research, and it is also one of the more difficult real-scene image recognition problems. The recognition results directly affect the performance of the assisted driving system and the user's evaluation of the system.

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