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

Automatic partitioning method for optimizing image initial partitioning boundary

A technology of initial segmentation and automatic segmentation, applied in the field of image processing

Inactive Publication Date: 2008-07-30
INST OF AUTOMATION CHINESE ACAD OF SCI
View PDF0 Cites 12 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

Although watershed methods have been successfully used in image classification, they require user interaction or accurate prior knowledge about the image structure

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
  • Automatic partitioning method for optimizing image initial partitioning boundary
  • Automatic partitioning method for optimizing image initial partitioning boundary
  • Automatic partitioning method for optimizing image initial partitioning boundary

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0033] The present invention will be described in detail below in conjunction with accompanying drawing, and segmentation optimization method of the present invention mainly comprises the following steps:

[0034] (1) Detect the boundary points in the initial segmentation results and mark them according to the initial segmentation results. All the boundary points in the first region are marked as Arabic numerals "1", and the boundary points in the second region are marked as "2". and so on;

[0035] (2) Calculate the nearest neighbor function value between all points in a certain neighborhood of each marked boundary point;

[0036] (3) Calculate the membership function value of the current boundary point according to the neighbor function value, that is, the possibility measure that the current boundary point belongs to a certain area;

[0037] (4) Reclassify the boundary points according to the membership function value to obtain the optimal segmentation boundary.

[0038] ...

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 processing technology, in particular to an automatic optimization method of initially segmented boundary based on neighbor function criterion. The method comprises the following steps: initially segmented boundary points are detected, and are marked with Arabic numerals according to an initially segmented area; neighbor function values within a neighborhood are calculated for each boundary point; membership function values of the current boundary point are calculated according to the neighbor function values; the boundary points are reclassified according to the membership function values to get an optimized segmented boundary; the steps above are repeated to ensure the segmented boundaries of the entire image to be optimized. The method provided by the invention imitates some functions of human eyes during image processing, and can optimize inaccurately segmented boundaries automatically. In addition, the invention eliminates the influence of image noise, local bulk effect, overlapping intensity and non-uniformity of intensity, and well complements prior segmentation algorithm. The invention has important application values in the fields of medical image segmentation, remote sensing image segmentation, target identification and so on.

Description

technical field [0001] The invention relates to image processing technology, in particular to an automatic optimization algorithm of an initial segmentation boundary based on a neighbor function criterion. Background technique [0002] The so-called image segmentation refers to distinguishing different regions with special meaning in the image, these regions do not cross each other, and each region satisfies the consistency of a specific region. From the perspective of processing objects, segmentation is to determine the location of the target of interest in the image matrix. Obviously, only by using this method to extract the "target object of interest" from the complex scene, it is possible to further quantitatively analyze or identify each sub-region, and then understand the image. The features available for image segmentation include image grayscale, color, texture, local statistical features or spectral features, etc. The difference of these features can be used to dis...

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): G06T5/00
Inventor 田捷陈健
Owner INST OF AUTOMATION CHINESE ACAD OF SCI
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

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