Method for identifying flaw of textile based on Gabor filter and RBF support vector machine

A support vector machine and recognition method technology, applied in the field of automatic detection of textile quality defects, can solve problems such as inconsistent standards, low efficiency, high rate of missed detection and false detection, and achieve the effect of low loss

Active Publication Date: 2018-05-29
DONGHUA UNIV
View PDF7 Cites 9 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

Traditional detection is based on manual naked eye detection, which is inefficient, inconsistent in standards, and has a high rate of missed and false detections

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 identifying flaw of textile based on Gabor filter and RBF support vector machine
  • Method for identifying flaw of textile based on Gabor filter and RBF support vector machine
  • Method for identifying flaw of textile based on Gabor filter and RBF support vector machine

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0049] 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.

[0050] Such as figure 1 As shown, a kind of textile defect recognition method based on Gabor filter and RBF support vector machine of the present invention comprises the following steps:

[0051]Step 1, collect textile images through YB cloth inspection machine. The image acquisition system of the cloth inspection machine adopts the method of line scanning. The initial image size is large and needs to be reduced to an approp...

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 method for identifying a flaw of a textile based on a Gabor filter and an RBF support vector machine. The method comprises: collecting a textile image and carrying out pretreatment; generating a Gabor filter group and filtering the textile image; carrying out preferential fusion on a filter image group; carrying out binaryzation processing on the fused image to display aflaw region; generating a feature vector for the flaw region; and classifying the feature vector by using a pre-trained RBF kernel function support vector machine classifier. According to the invention, the image is analyzed by using the Gabor filter and texture information of each scale and each angle is covered; and the flaw type is analyzed by using the RB support vector machine. The method has the positive significance in improving the production quality of the textile.

Description

technical field [0001] The invention relates to the technical field of automatic detection of textile quality defects, in particular to a textile defect recognition method based on a Gabor filter and a support vector machine. Background technique [0002] With the upgrading of domestic consumption, people have higher and higher requirements for clothing, which also puts forward higher requirements for the quality inspection of textile enterprises. Traditional detection is based on manual naked eye detection, which has low efficiency, inconsistent standards, and a high rate of missed and false detections. With the development of machine vision technology, this problem can be effectively alleviated. The application of machine vision technology can bring effective help to enterprises to improve quality management. Unified inspection standards and efficient inspection speed help enterprises to improve product quality more effectively, while liberating productivity and reducing ...

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): G06K9/46G06K9/62G06K9/40
CPCG06V10/446G06V10/30G06F18/2411
Inventor 郝阳石红瑞
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
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