Long-distance traffic sign detection and recognition method suitable for vehicle-mounted system

Abstract

The invention relates to a long-distance traffic sign detection and identification method suitable for a vehicle-mounted system. The method comprises the following steps: 1, preprocessing a traffic sign image sample set; 2, constructing a lightweight convolutional neural network, and completing the convolutional feature extraction of the traffic sign; 3, through a channel-spatial attention moduleembedded into the lightweight convolutional neural network, constructing an attention characteristic graph; 4, using a region generation network RPN to generate a candidate region of the target; 5, introducing context region information into the target candidate region generated by the RPN, and enhancing the mark classification characteristics; 6, sending the feature vector into a full connectionlayer, and outputting the category and position of the traffic sign; 7, establishing an attention loss function, and training an FL-CNN model; 8, repeating the steps 2-7 to complete sample training ofthe FL-CNN model; and 9, repeating 2-6 to finish traffic sign detection and identification of the actual scene. According to the invention, long-distance traffic sign detection and identification arerealized, and the precision reaches 92%.

Description

[0001] 1. Technical field: [0002] The invention relates to the field of intelligent transportation for unmanned driving and assisted driving, and solves the long-distance detection and recognition method of road traffic signs, and specifically relates to a long-distance traffic sign detection and recognition method suitable for vehicle-mounted systems. [0003] 2. Background technology: [0004] In the field of intelligent transportation, traffic sign detection and recognition is an important research issue for systems such as unmanned driving and assisted driving. A lot of research work has been done on this at home and abroad, but there are still great deficiencies, which cannot be practically applied to practice. The reasons are as follows: (1) Traditional detection and recognition methods designed based on features such as color and shape are less robust in the face of sign deformation, motion blur, weather, etc. in actual traffic scenes, and are difficult to implement in...

AI Technical Summary

Problems solved by technology

[0007] The purpose of the present invention is to provide a long-distance traffic sign detection and recognition method suitable for vehicle-mounted systems, which i

Images