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

A post-validation method for matching pairs of local feature points

A technology of local features and verification methods, applied in computer parts, special data processing applications, instruments, etc., can solve problems such as weakened discrimination ability and reduced matching accuracy, and achieves improved accuracy, high accuracy, and good robustness. sexual effect

Active Publication Date: 2020-02-07
HANGZHOU DIANZI UNIV
View PDF4 Cites 0 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0005] Aiming at the problem of reduced matching accuracy caused by the weakening of distinguishing ability after local features are quantized into visual words, the method of the present invention proposes to use the attribute change consistency between local feature point matching pairs and a voting method to confirm the correct match right

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 post-validation method for matching pairs of local feature points
  • A post-validation method for matching pairs of local feature points
  • A post-validation method for matching pairs of local feature points

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0042] The present invention will be described in detail below in conjunction with the accompanying drawings. It should be noted that the described embodiments are only for understanding of the present invention, and do not limit it in any way.

[0043] The concrete steps of the inventive method are:

[0044] Step (1) Obtain the matching pair of local feature points in the two images according to the visual vocabulary corresponding to the local feature points; there are currently many methods for extracting the local feature points, and the method of the present invention adopts the currently widely used scale-invariant descriptor ( SIFT), which is robust to rotation and scale transformation. After the SIFT descriptor is extracted, the image is represented as a set of local feature points {S i},S i is a local feature point descriptor in the image, which has the following related attributes in the image: feature vector (F i ), the main direction (θ i ), scale (σ i ), and s...

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 post-verification method for matching pairs of local feature points. The present invention first extracts local feature points in the image, and obtains candidate local feature point matching pairs through visual vocabulary; then, extracts attribute change values: main direction change value and orientation change value for the candidate local feature point matching pairs; The attribute change value and threshold value of , verify whether the two matching pairs are consistent; finally, the voting method is used to confirm whether the candidate local feature point matching pair is a correct matching pair according to the number of positive votes. This post-verification method can adapt to the effects of image cropping, rotation, scaling and other transformations, and can be used in applications such as image retrieval and classification based on visual vocabulary to improve the accuracy of retrieval and recognition. The invention has a very good verification effect for the feature point matching pairs in those non-perspective transformed images, and can greatly improve the accuracy and recall rate of copy retrieval in the application of image copy retrieval based on visual vocabulary.

Description

technical field [0001] The invention belongs to the field of computer image processing and image retrieval, and relates to a post-verification method for matching pairs of local feature points in two images. Background technique [0002] With the extensive research and application of local feature points in images, image analysis, recognition and retrieval based on local feature points has become an important way in the current image processing field. Referring to the bag-of-words model in document processing, an image can be represented as a collection of local features, thereby eliminating some redundant information in the image. In recent years, researchers have quantified the descriptors of local feature points into visual words, thus proposing the Bag of visual words model. This model has become an important method of image recognition and retrieval. The combination of visual vocabulary bag-of-words model and inverted index is currently the most effective content-base...

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): G06K9/62G06F16/583
CPCG06F16/583G06V10/757
Inventor 姚金良
Owner HANGZHOU DIANZI 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