Looking for breakthrough ideas for innovation challenges? Try Patsnap Eureka!

A Method for Object Recognition in Remote Sensing Image

A technology for remote sensing image and target recognition, which is applied in the field of image recognition to reduce the impact of background noise, improve efficiency, and improve accuracy.

Active Publication Date: 2020-07-14
HOHAI UNIV
View PDF4 Cites 0 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

The existing visual bag of words model can improve the efficiency of target detection and recognition to a certain extent in remote sensing target recognition, but there are still great limitations

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
  • A Method for Object Recognition in Remote Sensing Image
  • A Method for Object Recognition in Remote Sensing Image
  • A Method for Object Recognition in Remote Sensing Image

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0018] Below in conjunction with specific embodiment, further illustrate the present invention, should be understood that these embodiments are only used to illustrate the present invention and are not intended to limit the scope of the present invention, after having read the present invention, those skilled in the art will understand various equivalent forms of the present invention All modifications fall within the scope defined by the appended claims of the present application.

[0019] The target recognition method of remote sensing images based on the improved visual word bag model, the specific steps are as follows:

[0020] 1. Select remote sensing images of typical categories of targets to construct a training set.

[0021] Manually select multiple remote sensing images of various targets to construct a training set. Because the size and scale of the target categories in the remote sensing image training set are different, the number of SIFT features that can be extr...

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 discloses a remote sensing image target recognition method. It includes the following steps: firstly select remote sensing images of typical categories of targets to construct a training set; then extract the scale-invariant feature transformation (SIFT for short) features of the target images from the training set; then use the spectral clustering algorithm to generate a visual dictionary; then use The local weighted vectorization method reconstructs and codes the dictionary for the features of each image; finally, an appropriate classifier is selected to complete the image classification task. The invention can effectively improve the accuracy of image classification and recognition, and improve the efficiency of remote sensing target detection and recognition.

Description

technical field [0001] The invention relates to a remote sensing image target recognition method based on an improved visual word bag model, and belongs to the technical field of image recognition. Background technique [0002] In recent years, remote sensing technology has made great progress. With the continuous advancement of remote sensing image acquisition technology and the continuous increase in the number of remote sensing images, the existing image analysis and processing capabilities cannot meet the needs of massive remote sensing image data processing. The problem of how to quickly and accurately obtain information of interest from remote sensing images with complex background interference, unstable target features and massive information has gradually become one of the hotspots and difficulties in the development of remote sensing image technology. Furthermore, the detection and identification of targets with the help of remote sensing images has broad applicati...

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 Patents(China)
IPC IPC(8): G06K9/00G06K9/62
CPCG06V20/13G06F18/23213G06F18/24323
Inventor 高红民杨耀李臣明樊悦陈玲慧黄昌运闵海彬张振李雪琨陆迎曙
Owner HOHAI UNIV
Who we serve
  • R&D Engineer
  • R&D Manager
  • IP Professional
Why Patsnap Eureka
  • Industry Leading Data Capabilities
  • Powerful AI technology
  • Patent DNA Extraction
Social media
Patsnap Eureka Blog
Learn More
PatSnap group products

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

© 2024 PatSnap. All rights reserved.Legal|Privacy policy|Modern Slavery Act Transparency Statement|Sitemap|About US| Contact US: help@patsnap.com