Road intersection detection method and device based on improved YOLOv3

A detection method and a technology of a detection device, which are applied in the field of image processing, can solve the problems of difficult detection of small-sized road intersections and low detection accuracy, and achieve the effect of enhancing expression ability and improving detection accuracy

Active Publication Date: 2020-02-28
PLA STRATEGIC SUPPORT FORCE INFORMATION ENG UNIV PLA SSF IEU
View PDF16 Cites 5 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

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

Method used

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
View more

Image

Smart Image Click on the blue labels to locate them in the text.
Viewing Examples
Smart Image
  • Road intersection detection method and device based on improved YOLOv3
  • Road intersection detection method and device based on improved YOLOv3
  • Road intersection detection method and device based on improved YOLOv3

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0034] In order to elaborate on the purpose, technical solutions and advantages of the present invention, the present invention will be further described in detail below in conjunction with 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 collects road images first; performs network training to build an improved YOLOv3 network model; the improved YOLOv3 network model includes a feature extraction terminal and a feature detection terminal, 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 improved YOLOv3 network model is used to perform the road image to be detected. Identify and output the result.

[0037] Concrete, the road intersection detection ...

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to view more

PUM

No PUM Login to view more

Abstract

The invention relates to a road intersection detection method and device based on improved YOLOv3. The method mainly comprises the following steps: firstly, acquiring a road image; then, performing network training, and constructing an improved YOLOv3 network model; wherein the improved YOLOv3 network model comprises a feature extraction end and a feature detection end, the feature detection end comprises a plurality of channels, and in each channel, transversely broadening a corresponding convolution module to generate different feature maps, and then performing longitudinal aggregation; andadopting the improved YOLOv3 network model to identify a road image to be detected, and outputting a result. According to the invention, the convolution module in each channel of the improved YOLOv3 feature detection terminal is broadened transversely. different feature maps are generated according to the feature map set, and then longitudinal aggregation is carried out, so that the network widthof the convolution module of each channel can be wider, the expression capability of the network is enhanced, the detection difficulty of small-size road intersections in a complex remote sensing scene is reduced, and the detection precision is improved.

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. During the road network extraction process, the extracted roads will appear discontinuous due to the interference of many complex factors. At this time, taking the location of road intersections as the base point, information such as directions and topological relationships can be used to assist and guide the construction of road networks. [0003] However, based on the fact that road intersections are generally small planar targets in remote sensing images, the commonly used detection algorithms are mainly based on texture, shape, grayscale and other features for de...

Claims

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to view more

Application Information

Patent Timeline
no application Login to view more
Patent Type & Authority Applications(China)
IPC IPC(8): G06K9/00G06N3/08
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
Who we serve
  • R&D Engineer
  • R&D Manager
  • IP Professional
Why Eureka
  • Industry Leading Data Capabilities
  • Powerful AI technology
  • Patent DNA Extraction
Social media
Try Eureka
PatSnap group products

Browse by: Latest US Patents, China's latest patents, Technical Efficacy Thesaurus, Application Domain, Technology Topic.

© 2024 PatSnap. All rights reserved.Legal|Privacy policy|Modern Slavery Act Transparency Statement|Sitemap