Image segmentation method based on immunity clone selection clustering

A technology of immune cloning and image segmentation, which is applied in the field of image processing, can solve the problems that cannot be widely used, and achieve the effect of reasonable image segmentation results, good convergence performance, and reduced sensitivity

Inactive Publication Date: 2008-09-24
XIDIAN UNIV
View PDF0 Cites 37 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0006] Due to the shortcomings of the above-mentioned FCM clustering segmentation method, it cannot be widely used. Therefore, it is an urgent task for scientific and technical personnel in the technical field to study an effective 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 more

Image

Smart Image Click on the blue labels to locate them in the text.
Viewing Examples
Smart Image
  • Image segmentation method based on immunity clone selection clustering
  • Image segmentation method based on immunity clone selection clustering
  • Image segmentation method based on immunity clone selection clustering

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0049] refer to figure 1 , it is the realization flowchart of the present invention, can find out that its concrete realization process is as follows from the figure:

[0050] 1. Initialize the population

[0051] First determine the number of clusters C, the fuzzy coefficient M, the population size S, the clone size L, and the mutation probability P m , shutdown conditions and weight coefficients α, β and balance factor δ; in the gray space of pixels, the initial population G is randomly generated according to the number of clusters C and the population size S k For each individual of , let k=1, k is the evolution algebra;

[0052] The number of clusters C needs to be determined according to the specific processed image, and the number of cluster targets will be different for different images. The blur coefficient M can take different values, and it is taken as 2 here. The group size S is the specific number of individuals contained in the population, and its value is 8. ...

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 an image segmentation method based on an immune clonal selection cluster, and relates to the technical field of an image processing. The purpose of the invention is to solve the disadvantages that the robustness is lower due to sensitivity of a FCM cluster segmentation method to an initial clustering center and the noise; and spatial relationship between pixels of the image is not considered by the FCM cluster segmentation method. An implementation procedure of the method is as follows: an initial population is created at random according to a setup parameter; adaptation degree of each individual in the present population is calculated to judge whether a halt condition is met; a transitional population is created by a recurrence formula of the FCM; the adaptation degree of each individual in the transitional population is calculated; based on the adaptation degree, a cloning operation is made to the transitional population; a mutating operation is made to the individual in the cloned population; after the mutating operation, a roulette wheel selection is carried on to get a new population to carry out the second step; finally, an optimum individual is selected; and the image of a segmentation result corresponding to the optimum individual is output. The image segmentation method based on the immune clonal selection cluster can be used for the cluster segmentation of a pixel level of the image.

Description

technical field [0001] The invention belongs to the technical field of image processing, and relates to the application of the technology in the field of image segmentation, in particular to an image segmentation method based on Immune Clone Selection and ICS Clustering, i.e. ICSC. The method can be used in the technical field of image segmentation. Background technique [0002] Image segmentation is an important step in image processing. The task of image segmentation is to divide the input image into some independent regions, so that the same region has the same attributes, and different regions have different attributes. For the problem of image segmentation, researchers have proposed many methods, but in view of the characteristics of many types of images, large amount of data, and many changes, so far there is no image segmentation method suitable for all situations. As a means of image segmentation, data clustering has been widely used. [0003] Clustering is an imp...

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 Applications(China)
IPC IPC(8): G06T5/00G06N3/12
Inventor 焦李成王爽梁建华侯彪刘芳公茂果夏玉
Owner XIDIAN 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