Urban road recognition method based on multi-spectral images

A multi-spectral image and road recognition technology, which is applied in the field of multi-spectral image urban road recognition, can solve problems such as easy adhesion, salt and pepper phenomenon, and insufficient universality of segmentation algorithms, and achieve good anti-noise ability and good segmentation results.

Active Publication Date: 2018-12-11
NORTH CHINA UNIVERSITY OF TECHNOLOGY
View PDF7 Cites 15 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0004] Due to factors such as vehicles and pedestrians, the road binary image extracted by the pixel-level road extraction algorithm is prone to "salt and pepper phenomenon", and the center line extracted on this basis is prone to breakage
The co

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
  • Urban road recognition method based on multi-spectral images
  • Urban road recognition method based on multi-spectral images
  • Urban road recognition method based on multi-spectral images

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0050] The present invention will be described in detail below in conjunction with the implementations shown in the drawings, but it should be noted that these implementations are not limitations of the present invention, and those of ordinary skill in the art based on the functions, methods, or structural changes made by these implementations Equivalent transformations or substitutions all fall within the protection scope of the present invention.

[0051] ginseng figure 1 As shown, this embodiment provides a multispectral image urban road recognition method. First, the image is preprocessed to reduce the influence of factors such as noise on subsequent processing. The order of attention shifting, using a certain scale of morphological operators to perform morphological operations on the image, so that the image can be divided into coarse-scale images that can effectively reflect color and shape features and important information that can express image edges and vehicles, lan...

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 provides an urban road recognition method based on multi-spectral images. The method includes: 1, based on a object-oriented segmenting method, segmenting a road and surrounding ground objects in a Urban road recognition; 2, extracting low-level features of each segmented area, establishing mapping rules from low-level features to high-level semantic objects, realizing mapping from low-level features to high-level semantic features of an image, and constructing a semantic model for road recognition, wherein the low-level features include geometric features and spectral features,and the high-level semantic objects include green belts, lane lines, and road potential areas. The method adopts the method of combining the SLIC super pixel and the structure tensor rough segmentation, has a good anti-noise ability, and can obtain better segmentation results for complex urban multi-spectral images. The road recognition method based on semantic knowledge solves the problems of lowroad recognition accuracy, tendency of producing holes and fractures in the complex environment of multi-spectral images.

Description

technical field [0001] The invention belongs to the technical field of image recognition, and in particular relates to a multispectral image urban road recognition method. Background technique [0002] Traffic road target recognition in remote sensing images is one of the key technologies in the theory of automatic target recognition. Urban roads are an important part of geographic information databases. How to accurately identify urban road targets from multispectral images is of great significance for surface detection, urban structure description, and road renewal. [0003] The background of multi-spectral images is complex, and it is easily affected by the shadow of surrounding objects and the spectral approximation of roads and houses, so it is difficult to guarantee the recognition accuracy. For the urban road recognition of remote sensing images, the existing technologies mainly include road extraction methods based on pixel level and road extraction algorithms based...

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
IPC IPC(8): G06K9/00G06K9/44
CPCG06V20/176G06V10/34G06V2201/07
Inventor 张永梅马健喆孙海燕张奕
Owner NORTH CHINA UNIVERSITY OF TECHNOLOGY
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