A road intersection detection method and device based on improved yolov3

A detection method and intersection technology, which is applied in the field of image processing, can solve the problems of difficulty in detecting small road intersections and low detection accuracy, and achieve the effect of enhancing expression ability and improving detection accuracy

Active Publication Date: 2022-06-28
PLA STRATEGIC SUPPORT FORCE INFORMATION ENG UNIV PLA SSF IEU
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Problems solved by technology

[0004] The purpose of the present invention is to provide a road intersection detection method and device based on improved YOLOv3, which is used to solve the problem that the detection of small-sized road intersections is very difficult and the detection accuracy is not high in complex remote sensing scenarios

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  • A road intersection detection method and device based on improved yolov3
  • A road intersection detection method and device based on improved yolov3
  • A road intersection detection method and device based on improved yolov3

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Embodiment Construction

[0034] In order to elaborate the objectives, technical solutions and advantages of the present invention, the present invention will be further described in detail below with reference to specific implementation steps and accompanying drawings.

[0035] Embodiment of road intersection detection method

[0036] The invention provides a road intersection detection method based on improved YOLOv3, which mainly includes first collecting road images; performing network training to construct an improved YOLOv3 network model; the improved YOLOv3 network model includes a feature extraction end and a feature detection end, The feature detection end includes multiple channels. In each channel, the corresponding convolution module is first widened horizontally to generate different feature maps, and then vertically aggregated; the road image to be detected is processed by using the improved YOLOv3 network model. Identify and output the results.

[0037] Specifically, the road intersecti...

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Abstract

The present invention relates to a road intersection detection method and device based on improved YOLOv3, which mainly obtains road images first; then performs network training to construct an improved YOLOv3 network model; the improved YOLOv3 network model includes a feature extraction terminal and a feature The detection end, the feature detection end includes a plurality of channels, and in each channel, the corresponding convolution module is first widened horizontally to generate different feature maps, and then vertically aggregated; the improved YOLOv3 network model is used to treat The detected road image is recognized and the result is output. That is, the present invention first expands the convolution module in each channel of the improved YOLOv3 feature detection end horizontally to generate different feature maps, and then performs vertical aggregation to make the network width of the convolution module of each channel wider. , enhance the expressive ability of the network, thereby reducing the difficulty of detecting small-sized road intersections in complex remote sensing scenarios, and improving the detection accuracy.

Description

technical field [0001] The invention belongs to the technical field of image processing, and in particular relates to a road intersection detection method and device based on improved YOLOv3. Background technique [0002] As the hub of road connections, road intersections provide important information such as accurate location, direction, and topological relationship for the rapid construction of road networks. In the process of road network extraction, due to the interference of various complex factors, the extracted roads will appear discontinuous. At this time, the location of the road intersection is used as the base point, and the information such as direction and topological relationship can be used to assist and guide the construction of the road network. [0003] However, based on the characteristics that road intersections are generally small-shaped surface targets in remote sensing images, the commonly used detection algorithms are mainly based on texture, shape, ...

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06V20/58G06N3/08
CPCG06N3/08G06V20/588
Inventor 金飞陈佳怡王龙飞刘智芮杰王淑香官恺吕虎
Owner PLA STRATEGIC SUPPORT FORCE INFORMATION ENG UNIV PLA SSF IEU
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