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Road traffic sign automatic identification and classification method

A technology of automatic identification and road traffic, applied in the direction of neural learning methods, character and pattern recognition, instruments, etc., can solve problems such as wrong judgments, and achieve the effect of strong practicability and broad application prospects

Pending Publication Date: 2020-08-04
FUJIAN AGRI & FORESTRY UNIV
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  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

Deep learning recognizes and classifies by learning the characteristics of the target object. When there are objects with similar characteristics, it is easy to cause wrong judgments.

Method used

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  • Road traffic sign automatic identification and classification method
  • Road traffic sign automatic identification and classification method
  • Road traffic sign automatic identification and classification method

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Embodiment Construction

[0030] The present invention will be further described in detail below in conjunction with the accompanying drawings and specific embodiments.

[0031] The invention provides a method for automatic recognition and classification of road traffic signs, such as figure 1 shown, including the following steps:

[0032] Step S1: Collecting road images using a vehicle-mounted image acquisition device (vehicle camera). figure 2 The road image captured by the camera is shown.

[0033] Step S2: Select images with traffic signs from the collected road images and mark them to construct the dataset required for Mask_RCNN model training. Specifically include the following steps:

[0034] Step S21: Determine the type of traffic sign

[0035] According to the sign information collection table of Fujian Provincial Expressway Maintenance Center, traffic signs are roughly divided into seven categories: notice signs, prohibition signs, warning signs, tourist area signs, guide signs, instruct...

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Abstract

The invention relates to a road traffic sign automatic identification and classification method. The method comprises the following steps: S1, collecting a road image by using a vehicle-mounted imagecollection device; s2, screening and marking images with traffic signs out from the collected road images, and constructing a data set required by Mask _ RCNN model training; s3, inputting the data set obtained in the step S2 into a Mask _ RCNN model for training to obtain a trained weight; s4, performing road sign recognition and classification on all the acquired road images by using the weighttrained in the step S3; s5, checking the generated result, carrying out the secondary marking of the image with a poor recognition effect, and training the weight again; s6, outputting an identification result. The method is beneficial to improving the recognition and classification effects of the road traffic signs.

Description

technical field [0001] The invention relates to the technical field of automatic road detection, in particular to a method for automatic recognition and classification of road traffic signs. Background technique [0002] At present, traffic sign detection and recognition is a research hotspot of domestic and foreign scholars and institutions. Generally speaking, there are 3 methods for the detection of traffic signs: color segmentation based, shape information based and machine learning based methods. The algorithm based on color segmentation is simple, the calculation speed is fast, and it is not sensitive to geometric deformation, but the disadvantages are obvious in low light or backlight environment, similar background and other scenes, because color is unreliable information, collected at different times and under different light Available colors vary. The algorithm based on shape information is simple and fast, but it is easy to misidentify other objects with the sam...

Claims

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Application Information

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IPC IPC(8): G06K9/00G06K9/62G06N3/04G06N3/08
CPCG06N3/08G06V20/582G06N3/045G06F18/241G06F18/214
Inventor 罗文婷胡辉陈泽斌李林
Owner FUJIAN AGRI & FORESTRY UNIV
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