An Unsupervised Color Image Segmentation Method Based on Watershed Transform

A watershed transform and color image technology, applied in the field of image processing, can solve the problems of unsupervised image segmentation and difficulty in applying color image segmentation

Inactive Publication Date: 2017-03-22
LANZHOU JIAOTONG UNIV
View PDF6 Cites 0 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

However, this method does not achieve unsupervised segmentation of images, where the determination of parameters is a problem; secondly, this method is only suitable for grayscale image segmentation, and it is difficult to apply to color image segmentation

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
  • An Unsupervised Color Image Segmentation Method Based on Watershed Transform
  • An Unsupervised Color Image Segmentation Method Based on Watershed Transform
  • An Unsupervised Color Image Segmentation Method Based on Watershed Transform

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0033] The present invention will be further described below in conjunction with the accompanying drawings and embodiments, and the present invention includes but not limited to the following embodiments.

[0034] figure 1 It is a schematic block diagram of the flow process of the present invention's implementation steps. Aiming at the color image segmentation problem, a kind of non-parameter color image segmentation method based on watershed transform designed by the present invention is specifically described as follows:

[0035] (1) Initialization: Input a color image f, the image size is M×N, M and N represent the height and width of f respectively, define the initial variable i=1, and i represents the disc-shaped structural element B i The radius of , l=2 means that the gradient image is initially divided into 2 levels;

[0036] (2) Utilize the vector gradient method to calculate the gradient image g of the color image f,

[0037] (a) Use the Sobel operator to calculate...

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 provides a non-supervision color image segmentation method based on watershed transformation. The non-supervision color image segmentation method sequentially includes the following steps: (1), initializing operation parameters of a given program, and inputting a color image; (2), acquiring the gradient of the color image by a vector gradient calculation method; (3), performing self-adaptive gradient reconstruction on the gradient image according to a morphology reconstruction theory, and establishing structural elements changeable in size to adapt to different gradient values to effectively eliminate image structures with the small gradient values and keep the large gradient values unchanged; (4), performing parameter-free segmentation on the image according to stability of segmentation areas; (5), outputting a segmentation result. The non-supervision color image segmentation method can be applied to color image segmentation, and stable and accurate segmentation results can be acquired without setting of any parameters.

Description

technical field [0001] The invention belongs to the technical field of image processing and relates to morphological watershed theory and color image segmentation. The invention can be applied to the rapid segmentation of color images and lays a foundation for subsequent target classification and recognition. Background technique [0002] Image segmentation is a key step in computer vision and has important applications in image analysis and pattern recognition. At present, scholars have proposed many image segmentation methods, among which, the watershed transform based on mathematical morphology is an effective segmentation tool. The image segmentation results based on the watershed method have closed segmentation regions, however, because a single watershed transformation is often very sensitive to irregular details and noise, it is easy to cause over-segmentation. In response to this problem, scholars have done a lot of research work in recent years and proposed many im...

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): G06T7/155G06T7/90
CPCG06T7/11G06T2207/20152
Inventor 雷涛加小红罗维薇王履程
Owner LANZHOU JIAOTONG 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