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

Method for detecting color difference degree of colored textile fabrics

A color difference and detection method technology, applied in the field of image processing, can solve problems such as large amount of calculation, difficulty in solving model coefficients, inconvenient parameter adjustment, etc. Effect

Inactive Publication Date: 2020-01-17
WUHAN TEXTILE UNIV
View PDF10 Cites 9 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

The geometric method is a texture feature analysis method based on the texture primitive theory. The more influential algorithm is the checkerboard feature method, but its application and development are extremely limited.
The model method is to estimate and calculate the model parameters from the realization of the texture image, and at the same time use the parameters as the characteristics, or use a certain classification strategy to segment the image, the solution of the model coefficients is difficult and the amount of calculation is large, and the parameter adjustment is inconvenient

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
  • Method for detecting color difference degree of colored textile fabrics
  • Method for detecting color difference degree of colored textile fabrics
  • Method for detecting color difference degree of colored textile fabrics

Examples

Experimental program
Comparison scheme
Effect test

Embodiment

[0046] The present invention comprises the following steps:

[0047] Step 1: Obtain the image of the dyed fabric;

[0048] Step 2: convert the color-dyed fabric image from RGB color space to HSV color space and Lab color space respectively;

[0049] Step 3: Extract global color features and local texture descriptors of the mixed color space; including the following sub-steps:

[0050] Step 3.1: The global color feature extraction adopts the color aggregation vector method, which can not only effectively represent the color information, but also contain the spatial information of the color distribution. The color aggregation vector of the image is expressed as follows:

[0051] f=1 ,β 1 ),(α 2 ,β 2 ),…(α i ,β i )> Formula 3.1

[0052] In the formula, α i is the aggregation number of the i-th cluster, β i is the non-aggregate number of the i-th cluster, (α i ,β i ) is the ith aggregation vector pair;

[0053] Calculate the color aggregation vector f of the H componen...

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 belongs to the technical field of image processing, and relates to a colored textile fabric color difference degree detection method which is widely applied to the fields of artificial intelligence, color analysis, pattern recognition, intelligent detection and the like. According to the method, color space conversion is firstly carried out on an image, then global color features andlocal texture descriptors are extracted from HSV and Lab color spaces respectively, and finally corresponding features are fused to obtain mixed color space color representation features. According to the method, the defect that colors are described in a single color space is overcome, the color depicting capacity of the mixed color space is improved, the color difference degree is accurately detected, and the method has universality for different colored spun fabrics.

Description

technical field [0001] The invention relates to a method for detecting color difference of colored textiles, which belongs to the technical field of image processing. The established color characterization feature of mixed color space can effectively represent the color of colored textiles and further detect the color difference. Background technique [0002] Color-spun fabrics are made of two or more different dyed fibers mixed and spun through a specific process, which has a special color rendering effect. By adjusting the ratio of dyed fibers and the production process, color-spun fabrics with rich color levels can be obtained. In the production process of color-spun fabrics, it is difficult for enterprises to detect the target color, so scientific color characterization is needed to accurately detect the color difference between different colored fabrics. [0003] The commonly used color spaces have limitations in the representation of complex color models, and cannot ac...

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): G06T7/90G06T7/45G06T7/44G06K9/62G06K9/46
CPCG06T7/90G06T7/44G06T7/45G06V10/56G06V10/467G06F18/23
Inventor 袁理刘沐黎
Owner WUHAN TEXTILE 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
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