Eureka AIR delivers breakthrough ideas for toughest innovation challenges, trusted by R&D personnel around the world.

Image retrieval method and system based on global and local feature rearrangement

A technology of local features and global features, applied in the fields of image retrieval and information technology, can solve the problems of low average retrieval accuracy, unlearnability, and inability to express the spatial position information of vehicle components, and achieve the effect of improving the rearrangement effect.

Active Publication Date: 2022-05-31
CHINA NAT ELECTRONICS IMP & EXP CORP
View PDF0 Cites 0 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0002] In image retrieval methods such as vehicle image retrieval methods, they can be roughly divided into two categories: one is based on global features, using the residual network to map vehicle images into feature vectors, and using the cosine similarity of feature vectors to complete image retrieval sorting. The method only expresses the content of the image, but cannot express the spatial position information of the vehicle parts, resulting in low average retrieval accuracy
The other is based on traditional local features, mapping vehicle images to key point descriptors, and calculating the number of matching points based on feature matching to complete image retrieval and ranking. The image retrieval task failed to complete a good expression, resulting in a relatively low average retrieval accuracy

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
  • Image retrieval method and system based on global and local feature rearrangement
  • Image retrieval method and system based on global and local feature rearrangement
  • Image retrieval method and system based on global and local feature rearrangement

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0031] The present invention will be described in further detail below through specific embodiments and accompanying drawings.

[0032] An image retrieval method based on global and local feature rearrangement according to an embodiment of the present invention, used for vehicle image retrieval, includes the following steps:

[0033] (1) Data preparation: Based on the license plate recognition system, the vehicle pictures captured by different cameras are sorted out under each license plate number, and then the vehicle image data set is divided into training set, verification set and retrieval test set according to the ratio of 8:1:1 , randomly select a batch of pictures from each license plate number in the retrieval test set as the query image, and the rest of the pictures are used as the image database.

[0034] (2) Build a distributed deep learning vehicle image retrieval environment based on Pytorch.

[0035] (3) Data preprocessing: normalize the vehicle image data set i...

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 an image retrieval method and system based on global and local feature rearrangement. The method includes: extracting the global features and local features of the image to be queried and the images in the image database; calculating the similarity between the image to be queried and the images in the image database according to the global features, and sorting the images in the image database according to the similarity , take the topN image of the sorting result as the query result of the global feature; use the local feature to calculate the matching degree between the image to be queried and the topN image, rearrange the topN image according to the number of matching points, and obtain an accurate image retrieval and sorting result. The present invention first uses the similarity of the global features to perform image retrieval and sorting, and then rearranges the TopN results based on the feature matching points of the local features, further improving the retrieval accuracy, and is especially suitable for the key points of the suspect vehicle in the public security arrest or traffic accident Troubleshoot.

Description

technical field [0001] The invention belongs to the technical fields of information technology and image retrieval, in particular to an image retrieval method and system based on global and local feature rearrangement, and is especially suitable for retrieval of images such as vehicle images. Background technique [0002] In image retrieval methods such as vehicle image retrieval methods, they are roughly divided into two categories: one is based on global features, uses residual network to map vehicle images into feature vectors, and uses the cosine similarity of feature vectors to complete image retrieval sorting. The method only expresses the content of the image, but cannot express the spatial position information of vehicle components, resulting in low average retrieval accuracy. The other is based on traditional local features, mapping vehicle images as key point descriptors, and calculating the number of matching points based on feature matching to complete image retr...

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): G06F16/583G06F16/535G06F16/538G06V10/80G06V10/77G06V10/25
CPCG06F16/583G06F16/535G06F16/538G06V10/25G06F18/213G06F18/253Y02D10/00
Inventor 张招亮刘后标廖欢汪洋旭唐文杰
Owner CHINA NAT ELECTRONICS IMP & EXP CORP
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
Eureka Blog
Learn More
PatSnap group products