Eureka AIR delivers breakthrough ideas for toughest innovation challenges, trusted by R&D personnel around the world.

Fabric flaw detection method based on wavelet transformation and genetic algorithm

A genetic algorithm and defect detection technology, applied in computing, image data processing, instruments, etc., can solve the problems of image quality easily affected by industrial environment, fast cloth movement, large cloth size, etc., to achieve fast calculation speed, segmentation Fast, accurate segmentation effects

Inactive Publication Date: 2016-09-07
DONGHUA UNIV
View PDF4 Cites 14 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

However, due to the fast movement of the cloth and the large size of the cloth during the detection process, the image quality is easily affected by the industrial environment. Correctly extracting the defective area is called the key and difficult point in the cloth detection

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
  • Fabric flaw detection method based on wavelet transformation and genetic algorithm
  • Fabric flaw detection method based on wavelet transformation and genetic algorithm
  • Fabric flaw detection method based on wavelet transformation and genetic algorithm

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0033] Below in conjunction with specific embodiment, further illustrate the present invention. It should be understood that these examples are only used to illustrate the present invention and are not intended to limit the scope of the present invention. In addition, it should be understood that after reading the teachings of the present invention, those skilled in the art can make various changes or modifications to the present invention, and these equivalent forms also fall within the scope defined by the appended claims of the present application.

[0034] Embodiments of the present invention relate to a fabric defect detection method based on wavelet transform and genetic algorithm, such as figure 1 shown, including the following steps:

[0035] (1) Preprocessing the collected images with defects;

[0036] (2) Use wavelet decomposition on the preprocessed image to obtain multi-scale sub-images;

[0037] (3) Fusion the sub-images to obtain the optimal defect edge inform...

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 a fabric flaw detection method based on wavelet transformation and a genetic algorithm. The method comprises the following steps: preprocessing acquired images with flaws; obtaining multi-dimensional sub-images by performing wavelet decomposition on the preprocessed images; obtaining optimal flaw edge information by performing fusion on the sub-images; calculating a threshold for the sub-images by use of the genetic algorithm, and performing threshold segmentation on the fused images by use of the threshold; and performing morphological processing on the images after threshold segmentation. According to the invention, the cloth flaw segmentation effect after processing is accurate, the segmentation speed is fast, and original forms of the flaws are well reserved.

Description

technical field [0001] The invention relates to the technical field of fabric flaw detection, in particular to a fabric flaw detection method based on wavelet transform and genetic algorithm. Background technique [0002] Fabric defect detection is an indispensable link in the fabric production process, and the manual detection method has been widely used in textile enterprises for a long time. This traditional cloth inspection method is inefficient, the labor intensity of workers is high, and the detection accuracy cannot be guaranteed. It can be seen that the traditional manual inspection method has been difficult to meet the modern management requirements of enterprises. Therefore, the development of a fabric automatic detection equipment has important economic significance for the quality control of textile enterprises and the saving of labor costs. [0003] At present, there are relatively few automatic fabric defect detection systems facing the market, and only a few...

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): G06T7/00G06T5/40G06T5/50
CPCG06T7/0004G06T5/40G06T5/50G06T2207/20032G06T2207/20221G06T2207/30124
Inventor 周武能李倩倩
Owner DONGHUA 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
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