Road intelligent extraction method and device, extraction model construction method and hybrid navigation system

An extraction method and road extraction technology, applied in the field of image recognition, can solve problems such as large amount of calculation, large extraction deviation of remote sensing images, and difficulty in automatic classification, and achieve the effect of improving the accuracy rate and recall rate.

Inactive Publication Date: 2018-07-17
NAVINFO
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Problems solved by technology

However, this method relies on high-resolution remote sensing images, which is computationally intensive and difficult to automatically classify
The finite element method mostly focuses on the use of the geometric characteristics of the road, and is carried out in low (edge ​​detection and texture analysis), medium (analysis, selec

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  • Road intelligent extraction method and device, extraction model construction method and hybrid navigation system
  • Road intelligent extraction method and device, extraction model construction method and hybrid navigation system
  • Road intelligent extraction method and device, extraction model construction method and hybrid navigation system

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[0032] For example, certain words are used in the description and claims to refer to specific components. Those skilled in the art should understand that hardware manufacturers may use different terms to refer to the same component. This specification and claims do not use differences in names as a way to distinguish components, but use differences in functions of components as a criterion. If the "include" mentioned in the entire specification and claims is an open term, it should be interpreted as "include but not limited to". "Approximately" means that within the acceptable error range, those skilled in the art can solve the technical problem within a certain error range, and basically achieve the technical effect. The following description of the specification is a preferred embodiment for implementing the present invention, but the description is for the purpose of explaining the general principles of the present invention and is not intended to limit the scope of the pre...

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Abstract

The invention provides a satellite image road intelligent extraction method and device base on deep learning. The method comprises the following steps: selecting a part of satellite image pictures, marking roads in the pictures with specific colors and constructing a mark database; carrying out autonomous learning through a convolutional neural network, constructing a learning model and utilizingthe learning model to carry out road extraction on newly-input satellite image pictures; judging the road extraction result, if the result is correct, carrying out road grid vectorization, or otherwise, returning to the mark database to carry out remarking and learning; and for extracted roads, traversing each road and carrying out road centerline extraction, and connecting central coordinates inseries to form a vector road line. The method carries out autonomous learning by providing a lot of mark data, then, carries out road extraction on the newly-input satellite image pictures and judgesthe extraction result, thereby correcting errors constantly and improving accuracy and recall rate of remote sensing image road extraction.

Description

technical field [0001] The present invention relates to the field of image recognition, in particular to a method and device for extracting roads from satellite images using a method based on deep learning. Background technique [0002] For road recognition in the prior art, a method based on image segmentation or a finite element method can be used. For the method based on image segmentation, according to certain algorithms, such as K-means clustering algorithm, fuzzy C-means clustering algorithm, etc., the image is divided into meaningful patches, and roads are identified according to the characteristics of the patches, and roads are extracted. Segment or road seed point. However, this method relies on high-resolution remote sensing images, which has a large amount of calculation and is difficult to automatically classify. The finite element method mostly focuses on the use of the geometric characteristics of the road, and is carried out in low (edge ​​detection and text...

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Application Information

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IPC IPC(8): G06K9/00G06K9/62G06F17/30G01C21/36
CPCG06F16/29G01C21/3608G01C21/3626G01C21/3629G01C21/3635G01C21/3664G06V20/182G06F18/217G06F18/214
Inventor 史川
Owner NAVINFO
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