Supercharge Your Innovation With Domain-Expert AI Agents!

An image matching method based on image global features and local features

A technology of local features and matching methods, applied in the fields of computer vision and image matching, can solve the problems of unacceptable time overhead and space overhead of local features, and achieve the effects of fast processing speed, strong versatility and strong anti-interference ability.

Inactive Publication Date: 2019-03-08
NANJING XUNSIYA INFORMATION TECH
View PDF2 Cites 10 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

Compared with global features, local features have high image matching accuracy, high matching accuracy and strong anti-interference (flip, remake, color change, background interference, etc.), which can basically meet the normal target matching requirements, but when the demand is tens of millions or even hundreds of millions When retrieving images from image databases of the same level, the time and space overhead of local features becomes unacceptable

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
  • An image matching method based on image global features and local features
  • An image matching method based on image global features and local features
  • An image matching method based on image global features and local features

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0032] The technical scheme of the present invention is described in detail below in conjunction with accompanying drawing:

[0033] Those skilled in the art can understand that, unless otherwise defined, all terms (including technical terms and scientific terms) used herein have the same meaning as commonly understood by those of ordinary skill in the art to which this invention belongs. It should also be understood that terms such as those defined in commonly used dictionaries should be understood to have a meaning consistent with the meaning in the context of the prior art, and will not be interpreted in an idealized or overly formal sense unless defined as herein explain.

[0034] The present invention proposes an image classification method based on scale space, which maintains invariance to image scaling, rotation and even affine transformation, and utilizes deep learning to classify images by finding feature points (interestpoints, or corner points) in a picture ) and ...

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 an image matching method based on image global features and local features. According to the method, an image is scaled based on an image scale space; rotation and even affinetransformation keep invariant image local features; a deep learning image classification method is utilized, a local feature compression algorithm and an index algorithm are creatively designed, localfeatures are successfully integrated into a CBIR framework, a fingerprint technology based on image and video content recognition is formed, and the method is applied to image and video matching. Compared with the prior art, the method has the advantages of high anti-interference capability, high universality, high processing speed and high matching accuracy.

Description

technical field [0001] The invention relates to the field of computer vision, in particular to the technical field of image matching. Background technique [0002] Image matching has been a hot and difficult research topic in recent decades. It is to find one or more transformations in the transformation space to make two or more images of the same scene from different times, different sensors or different perspectives It is consistent in space and has been applied in many fields. [0003] Image matching is divided into grayscale-based matching and feature-based matching, but the calculation of matching methods using grayscale information is too large, these methods are rarely used, and the matching based on image features is more and more used in practice. more and more widely. In feature matching, it is divided into global feature matching and local feature matching. Global features mainly extract edge and color information to describe the content of an image, or use a s...

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): G06K9/62G06K9/46
CPCG06V10/462G06V10/44G06V10/751
Inventor 田海陆玉传吴馨吴沁
Owner NANJING XUNSIYA INFORMATION TECH
Features
  • R&D
  • Intellectual Property
  • Life Sciences
  • Materials
  • Tech Scout
Why Patsnap Eureka
  • Unparalleled Data Quality
  • Higher Quality Content
  • 60% Fewer Hallucinations
Social media
Patsnap Eureka Blog
Learn More

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

© 2025 PatSnap. All rights reserved.Legal|Privacy policy|Modern Slavery Act Transparency Statement|Sitemap|About US| Contact US: help@patsnap.com