Multi-scale multi-level image segmentation method based on minimum spanning tree
An image segmentation, multi-level technology, applied in image analysis, image data processing, instruments, etc., can solve the problem of blurred and inaccurate boundaries
Inactive Publication Date: 2011-06-15
WUHAN UNIV
View PDF3 Cites 25 Cited by
- Summary
- Abstract
- Description
- Claims
- Application Information
AI Technical Summary
Problems solved by technology
Aiming at the problem of multi-scale and multi-level image segmentation and description, in order to avoid the problem of blurred and inaccurate boundaries in multi-scale space, and to describe the adjacency relationship between objects and the relationship between the upper and lower layers, the present invention provides a method based on minimum generation Tree-based multi-scale and multi-level image segmentation method
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 moreImage
Smart Image Click on the blue labels to locate them in the text.
Smart ImageViewing Examples
Examples
Experimental program
Comparison scheme
Effect test
Embodiment Construction
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
Login to View More
Abstract
The invention provides a multi-scale multi-level image segmentation method based on a minimum spanning tree. Multi-scale multi-level image segmentation is expressed and realized by a graph model. The segmentation method is suitable for initial segmentation results obtained by various images and various rules to effectively combine over-segmented regions in high level segmentation, so an over-segmentation phenomenon is avoided; moreover, multi-scale segmentation results on different levels provides characteristic description information on different levels for analysis of target structural components; and the method is very important for target recognition.
Description
Multi-scale and multi-level image segmentation method based on minimum spanning tree technical field The method belongs to the technical field of image processing and recognition, and in particular relates to a new multi-level and multi-scale pyramid image segmentation method based on minimum spanning tree optimization theory and graph model characteristics. Background technique High-spatial-resolution remote sensing images provide us with high-precision spatial geometric information, rich texture information, and multi-spectral information of the ground landscape, making traditional pixel-based remote sensing image classification methods inapplicable. Therefore, high-resolution remote sensing image processing Challenged with the detail provided by imagery. For this reason, Baatz and Schape pointed out in [1] in 1999 that important semantic interpretation needs to be represented by meaningful objects and the relationship between objects in images rather than by pixels. Th...
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
Login to View More
IPC IPC(8): G06K9/34G06T7/00
Inventor 崔卫红潘斌
Owner WUHAN 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 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