Gray scale space division method of image preprocessing based on mean value filtering

A technology of image preprocessing and mean filtering, applied in the field of image processing, can solve problems such as increasing the complexity of solving problems, and achieve good segmentation effect and clear edge effect

Inactive Publication Date: 2016-01-06
CHENGDU RONGCHUANG ZHIGU SCI & TECH
View PDF4 Cites 10 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

People hope to introduce some artificial knowledge-oriented and artificial intelligence methods to correct some errors in segmentation, which is a promising method, but this increases the complexity of the problem

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
  • Gray scale space division method of image preprocessing based on mean value filtering
  • Gray scale space division method of image preprocessing based on mean value filtering
  • Gray scale space division method of image preprocessing based on mean value filtering

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0031] All features disclosed in this specification, or steps in all methods or processes disclosed, may be combined in any manner, except for mutually exclusive features and / or steps.

[0032] The information in an image includes three parts: target object, background and noise. Image binarization is an image processing method to obtain the target object in the image. After binarization, all pixels in the image will be will change to white or black. When the image contains only two parts of information, the foreground and the background, the pixel value of the foreground can be set to 1, and the pixel value of the background can be set to 0, so that the image is binarized. There are many methods of binarization, generally divided into global threshold method and local threshold method

[0033] The global threshold method refers to a method that uses only one global threshold T in the binarization process. It compares the gray value of each pixel of the image with T, if it i...

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

Disclosed is a gray scale space division method of image preprocessing based on mean value filtering. The method comprises the following steps: according to importance of RGB three components and other indexes, performing weight average operation on the three components by means of different weights; histogram correction is firstly carried out by use of histogram equalization, a histogram of an original image is corrected to be uniformly distributed by use of a gray scale conversion function, then the histogram correction is carried out; carrying out the mean value filtering on the image by use of a global threshold method in which only one global threshold T is used in a binary process, the gray scale value of each pixel of the image is compared to T, if the value is greater than T, the value is taken as a foreground color, and otherwise, the value is taken as a background value; taking center points P with maximum quantities of corresponding pixels in L gray scale grade scopes as initial mean values; and during i-th iteration, investigating each pixel, calculating the spacing between each pixel and the mean value of each gray scale grade, endowing each pixel with a mean value to a closest cluster, for j=1, 2, ...1, calculating a new cluster center, updating a cluster mean value, and investigating all the pixels one by one.

Description

technical field [0001] The invention relates to the technical field of image processing, and provides a method for dividing gray space of image preprocessing based on mean filtering. Background technique [0002] Image segmentation is the technology and process of dividing an image into several specific regions with unique properties and proposing objects of interest. It is a key step from image processing to image analysis. The existing image segmentation methods are mainly divided into the following categories: threshold-based segmentation methods, region-based segmentation methods, edge-based segmentation methods, and segmentation methods based on specific theories. Since 1998, researchers have continuously improved the original image segmentation methods and applied some new theories and methods from other disciplines to image segmentation, and proposed many new segmentation methods. The objects extracted after image segmentation can be used in image semantic recogniti...

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): G06T7/00
CPCG06T2207/10024G06T2207/20182
Inventor 张岱齐弘文
Owner CHENGDU RONGCHUANG ZHIGU SCI & TECH
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