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Road traffic sign recognition method based on neural network

A technology of road traffic and recognition methods, which is applied in the field of target recognition, can solve the problems of low hardware configuration, cost increase, and increased calculation load of traffic recognition, and achieve the effects of improving accuracy, reducing the number of parameters, and reducing large differences

Pending Publication Date: 2021-10-22
SHANGHAI HEQIAN ELECTRONICS TECH CO LTD
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  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

However, in automobiles, the hardware configuration is often low. Such a large amount of parameters increases the calculation load for traffic recognition, and also brings about an increase in cost.

Method used

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  • Road traffic sign recognition method based on neural network
  • Road traffic sign recognition method based on neural network
  • Road traffic sign recognition method based on neural network

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Embodiment Construction

[0055] In order to have a clearer understanding of the technical features, purposes and effects of this document, the specific implementation manners of the present invention will now be described with reference to the accompanying drawings, and the same symbols in each figure represent the same parts. In order to make the drawings concise, the schematic diagrams in the drawings show the relevant parts of the present invention, but do not represent the actual structure of the product. In addition, in order to make the drawings concise and easy to understand, in some drawings, only one of the components having the same structure or function is schematically shown, or only one of them is marked.

[0056] As for the control system, functional modules and application programs (APP) are well known to those skilled in the art, they can take any appropriate form, either hardware or software, multiple functional modules discretely set, or It is multiple functional units integrated int...

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Abstract

The invention provides a road traffic sign recognition method based on a neural network. According to the method, equalization processing is carried out on training set images to obtain consistency difference distribution, first conversion, second conversion, third conversion and image enhancement are carried out on the images, a neural network model is improved, and the parameter quantity of the neural network model is reduced. After the model is optimized, compared with a traditional model, the parameter quantity is only 9.23% of that of the original model, but the recognition precision is not reduced, and a better effect is obtained.

Description

technical field [0001] The invention relates to the field of object recognition, in particular to a neural network-based road traffic sign recognition method. Background technique [0002] Traffic sign recognition is the key technology of intelligent transportation system. It is widely used in vehicle control, traffic monitoring and intelligent driving systems. Accurate identification of traffic signs with various tilt angles and shooting angles is an important basis for realizing vehicle intelligent driving. The traffic sign recognition system mainly includes four links: traffic sign detection, traffic sign area segmentation, traffic sign classification and traffic sign recognition, and traffic sign classification is the central link of the traffic sign recognition system, and it is also a particularly important link. Sign shape recognition algorithms can achieve better recognition results under their own specific conditions, but when the traffic sign image is tilted and th...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06K9/00G06K9/40G06K9/62G06N3/04G06N3/08
CPCG06N3/084G06N3/047G06N3/048G06N3/045G06F18/2415G06F18/241
Inventor 肖文平何敖东潘永靖
Owner SHANGHAI HEQIAN ELECTRONICS TECH CO LTD
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