A false matching removal method based on superpixel motion statistics

A super-pixel, mismatching technology, applied in computing, image analysis, image data processing and other directions, can solve problems such as inaccuracy and statistical errors, achieve strong robustness, accurate screening results, and solve the problem of false matching elimination.

Active Publication Date: 2019-06-28
TIANJIN UNIV
View PDF6 Cites 7 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0004] However, studies have shown that although the matrix grid is simple, it often contains different texture components. Therefore, i

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 false matching removal method based on superpixel motion statistics
  • A false matching removal method based on superpixel motion statistics
  • A false matching removal method based on superpixel motion statistics

Examples

Experimental program
Comparison scheme
Effect test

Embodiment 1

[0041] An embodiment of the present invention provides a method for removing false matches based on superpixel motion statistics, which mainly consists of four parts: initial matching of features, superpixel segmentation of images, establishment of superpixel statistical models, and retention of correct matches .

[0042] The embodiment of the present invention adopts the region division method of superpixel segmentation, assigns the initial feature matching to different superpixels, converts the smoothness constraints of local matching into consistency statistics of superpixel motion, and establishes a statistical model of superpixel motion. The automatic selection of registration feature points of non-rigid deformed images is realized through this statistical model. Such as figure 1 As shown, the specific steps and principles are as follows:

[0043] 101: Perform feature extraction, description and matching on two images to be matched;

[0044] This step 101 is specifical...

Embodiment 2

[0070] The scheme in embodiment 1 is described in further detail below in conjunction with specific examples, see the following description for details:

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 false matching removal method based on superpixel motion statistics. The method comprises the following steps: carrying out feature extraction, description and matching on two images to be matched; Segmenting the to-be-matched images I1 and I2 by using an improved superpixel segmentation algorithm to obtain two superpixel mark graphs; And establishing a superpixel motionstatistical model based on the superpixel marker map, and realizing automatic screening of registration feature points of the non-rigid deformation image through the model. According to the method, asuper-pixel segmentation strategy is adopted to replace simple rectangular grid division, super-pixel blocks obtained through segmentation are tightly connected in space, colors and textures in singlesuper-pixel blocks are kept consistent, a segmentation result better follows the moving edge of an object, and therefore it is guaranteed that feature points in super-pixels have the same or consistent moving tendency.

Description

technical field [0001] The invention relates to the field of computer image matching, in particular to a method for removing false matching based on superpixel motion statistics, which can be used to remove false feature matching of non-rigid deformed images. Background technique [0002] The fundamental purpose of the feature point registration method is to establish the matching correspondence between two or more image feature point sets. Due to the influence of lighting conditions, noise, geometric transformation, space warping, etc., it is very challenging to achieve completely accurate feature matching. At present, the feature operators used for image registration mainly include SIFT operator (scale invariant feature transformation), SURF operator (accelerated robust feature), and ORB operator [1] Wait. Using the above method can achieve relatively accurate feature registration, but when non-rigid deformation or large-scale displacement occurs between images, it is ea...

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): G06T7/33G06T7/11G06K9/62
Inventor 何凯王阳刘志国马红悦
Owner TIANJIN UNIV
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