Printed fabric surface defect detection method based on image processing

A defect detection and image processing technology, applied in image data processing, image enhancement, image analysis, etc., can solve problems such as low accuracy, inconsistent detection standards, etc., to improve production efficiency, reduce waste, and reduce secondary processing. effect of probability

Pending Publication Date: 2021-01-29
XI'AN POLYTECHNIC UNIVERSITY +1
View PDF8 Cites 7 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0003] The purpose of the present invention is to provide a method for detecting surface defects of printed fabrics based on image processing, which solves the problems of non-uniform detection standards and low accuracy in existing defect detection methods

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
  • Printed fabric surface defect detection method based on image processing
  • Printed fabric surface defect detection method based on image processing
  • Printed fabric surface defect detection method based on image processing

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0038] The present invention will be described in detail below in conjunction with the accompanying drawings and specific embodiments.

[0039] A method for detecting surface defects of printed fabrics based on image processing of the present invention is specifically implemented according to the following steps:

[0040] Step 1, collecting the template image and collecting the cloth image to be detected;

[0041] Step 2, perform the same preprocessing on the template image and the cloth image to be detected, including grayscale, brightness adjustment, image blurring, and detexturing;

[0042] The grayscale is specifically:

[0043] (1) calculate template image and the component of each pixel point RGB of cloth image to be detected by OpenCV function;

[0044] (2) Calculate the weighted gray value: 0.3×B+0.59×G+0.11×R;

[0045] (3) Assign the weighted gray value calculated in (2) to each corresponding pixel in (1);

[0046] The expression for adjusting brightness is:

[0...

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 a printed fabric surface defect detection method based on image processing, and the method comprises the steps: collecting a template image and a to-be-detected cloth image, carrying out the same preprocessing of the images, calculating the SURF features of the images, and determining feature points; taking the to-be-detected cloth image as a template image, taking the template image as a reference image, carrying out bidirectional feature point matching, obtaining registered feature point information, carrying out affine transformation, image registration and image difference, and extracting a difference region in the image to obtain a difference image; and performing threshold segmentation, opening operation and connected domain marking operation on the differential image to obtain an image marked with defects. The detection method provided by the invention solves the problems of non-uniform detection standards and low accuracy in the existing defect detectionmethod.

Description

technical field [0001] The invention belongs to the technical field of digital printing, and in particular relates to a method for detecting surface defects of printed fabrics based on image processing. Background technique [0002] During the production process of printed cloth, due to faults such as nozzle blockage, nozzle ink leakage, cloth wrinkles, and motor step deviation, the printed pattern will have dot and strip defects. In the process of batch printing, if the failure is not detected and eliminated in time, a large number of defective products will be produced, resulting in unnecessary waste of resources. At present, although each machine has a corresponding inspector, the labor cost is high, the inspection standard is not uniform, and due to long hours of work, human eyes will be fatigued, and the actual inspection effect is not good. Due to the limitations of human physiological factors, it is impossible to accurately and objectively detect the accuracy of the ...

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): G06T7/00G06T7/33G06T3/00
CPCG06T7/001G06T7/337G06T3/0075G06T2207/30124
Inventor 张团善马超华
Owner XI'AN POLYTECHNIC UNIVERSITY
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