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A method and system for extracting road material from remote sensing images

Active Publication Date: 2021-11-23
CHINA TRANSPORT TELECOMM & INFORMATION CENT
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Problems solved by technology

However, in the actual application research, the vehicles driving on the road and the large buildings and green vegetation beside the road will block the road to a certain extent, resulting in an increase in information redundancy and a decrease in accuracy.
In addition, when identifying materials, since the current urban roads mainly use cement and asphalt surfaces, similar materials are also used for urban building roofs, parking lots, and embankments, which further increases the difficulty of road material identification.

Method used

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  • A method and system for extracting road material from remote sensing images
  • A method and system for extracting road material from remote sensing images
  • A method and system for extracting road material from remote sensing images

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Embodiment Construction

[0051] The preferred embodiments of the present invention will be described below in conjunction with the accompanying drawings. It should be understood that the preferred embodiments described here are only used to illustrate and explain the present invention, and are not intended to limit the present invention.

[0052]At present, researchers have extracted a variety of road extraction methods through continuous efforts. The main technical principle is to use road color and shape features to construct a detection / classification framework algorithm. In recent years, with the continuous development and application of convolutional neural networks, especially deep convolutional neural networks, more and more scholars are inclined to construct deep convolutional neural networks to extract road information. Using a deeper network structure, the deep neural network can learn multi-dimensional features such as color and shape of the road at the same time, and extract and identify ro...

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Abstract

The invention discloses a method for extracting road materials from remote sensing images. The method utilizes the processing method of a double network structure to overcome some defects of using a single complex neural network structure, such as the potential overfitting and uncontrollability of the deep network structure to information learning. This improves the stability and reliability of the automatic road extraction model, and has better training characteristics, which can be applied in many fields.

Description

technical field [0001] The invention relates to the technical field of image extraction, in particular to a method and system for extracting road material from remote sensing images. Background technique [0002] The construction level of transportation infrastructure directly reflects the economic strength and development level of a country. As a developing country, my country has been vigorously promoting the construction of transportation infrastructure. The automatic extraction of traffic infrastructure, especially traffic roads, has always been one of the hot issues studied by scientific researchers. The identification and monitoring of road materials is of great significance to road construction and maintenance. In recent years, with the continuous development of remote sensing technology, information extraction technology based on remote sensing images has developed into an efficient scientific method, and related applications have also emerged, such as infrastructure...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06K9/00G06K9/34G06K9/46G06K9/62
CPCG06V20/182G06V10/267G06V10/44G06F18/24G06F18/214
Inventor 夏威刘建张雨泽孙士凯钟南耿丹阳
Owner CHINA TRANSPORT TELECOMM & INFORMATION CENT
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