Software image defect detection of full-fashioned textures in textile industry

The purpose of the research is to detect defects in textile industry using computer vision and fuzzy logic techniques. The paper presents various practices used for edge detection, including a fuzzy logic applied. By testing, a fuzzy logic method has been chosen to obtain a respectable result. The a...

Full description

Saved in:
Bibliographic Details
Main Authors: Zatonskiy, Andrey, Varlamova, Svetlana, Beknazarova, Saida, Gorbunova, Tatiana, Alutin, Petr, Belozerov, Oleg, Bazhenov, Ruslan
Format: Conference Proceeding
Language:English
Subjects:
Algorithms
Color
Computer vision
Defects
Edge detection
Fabrics
Fuzzy logic
Textile industry
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
cited_by
cites
container_end_page
container_issue 1
container_start_page
container_title
container_volume 3021
creator Zatonskiy, Andrey
Varlamova, Svetlana
Beknazarova, Saida
Gorbunova, Tatiana
Alutin, Petr
Belozerov, Oleg
Bazhenov, Ruslan
description The purpose of the research is to detect defects in textile industry using computer vision and fuzzy logic techniques. The paper presents various practices used for edge detection, including a fuzzy logic applied. By testing, a fuzzy logic method has been chosen to obtain a respectable result. The algorithm that is observed in the paper is improved by dividing the processing into two phases: a fast one, which allows us to assume that there is a defect, and a searching one, which allows a defect to be highlighted in color. The advanced algorithm was tested on several types of fabrics. An average background arrangement is obtained for them. That allows separating fabric texture and color from potential defects. The tests were also performed on fabrics (cloths) with different brightness, number and type of defects. We obtained the percentage ratios of the defect detection quality and so we suggested the ways to develop the system.
doi_str_mv 10.1063/5.0192867
format conference_proceeding
fullrecord <record><control><sourceid>proquest_scita</sourceid><recordid>TN_cdi_proquest_journals_3015031920</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><sourcerecordid>3015031920</sourcerecordid><originalsourceid>FETCH-LOGICAL-p133t-a3e4761064ec2ef90809cd09bc3fec071132bff84514bfb37549eb4ac5bfd5b33</originalsourceid><addsrcrecordid>eNotUE1LxDAQDaLgunrwHxS8CdVJJ2mboyx-waIHFbyFpJ1ol9quSYruvzfr7unNwJt5H4ydc7jiUOK1vAKuirqsDtiMS8nzquTlIZsBKJEXAt-P2UkIK4BCVVU9Y08vo4s_xlPWfZkPylpy1MQEMUE3DtnoMjf1fe5M-Ew7tVmk3zh5Clk3_M9dn46HdgrRb07ZkTN9oLM9ztnb3e3r4iFfPt8_Lm6W-ZojxtwgiWQMSkFNQU5BDappQdkGkzxUnGNhnauF5MI6i5UUiqwwjbSulRZxzi52f9d-_J4oRL0aJz8kSY3AJWAqARLrcscKTRfNNo5e-5TTbzQHve1LS73vC_8APTpdnQ</addsrcrecordid><sourcetype>Aggregation Database</sourcetype><iscdi>true</iscdi><recordtype>conference_proceeding</recordtype><pqid>3015031920</pqid></control><display><type>conference_proceeding</type><title>Software image defect detection of full-fashioned textures in textile industry</title><source>American Institute of Physics:Jisc Collections:Transitional Journals Agreement 2021-23 (Reading list)</source><creator>Zatonskiy, Andrey ; Varlamova, Svetlana ; Beknazarova, Saida ; Gorbunova, Tatiana ; Alutin, Petr ; Belozerov, Oleg ; Bazhenov, Ruslan</creator><contributor>Kovalev, Igor ; Voroshilova, Anna</contributor><creatorcontrib>Zatonskiy, Andrey ; Varlamova, Svetlana ; Beknazarova, Saida ; Gorbunova, Tatiana ; Alutin, Petr ; Belozerov, Oleg ; Bazhenov, Ruslan ; Kovalev, Igor ; Voroshilova, Anna</creatorcontrib><description>The purpose of the research is to detect defects in textile industry using computer vision and fuzzy logic techniques. The paper presents various practices used for edge detection, including a fuzzy logic applied. By testing, a fuzzy logic method has been chosen to obtain a respectable result. The algorithm that is observed in the paper is improved by dividing the processing into two phases: a fast one, which allows us to assume that there is a defect, and a searching one, which allows a defect to be highlighted in color. The advanced algorithm was tested on several types of fabrics. An average background arrangement is obtained for them. That allows separating fabric texture and color from potential defects. The tests were also performed on fabrics (cloths) with different brightness, number and type of defects. We obtained the percentage ratios of the defect detection quality and so we suggested the ways to develop the system.</description><identifier>ISSN: 0094-243X</identifier><identifier>EISSN: 1551-7616</identifier><identifier>DOI: 10.1063/5.0192867</identifier><identifier>CODEN: APCPCS</identifier><language>eng</language><publisher>Melville: American Institute of Physics</publisher><subject>Algorithms ; Color ; Computer vision ; Defects ; Edge detection ; Fabrics ; Fuzzy logic ; Textile industry</subject><ispartof>AIP conference proceedings, 2024, Vol.3021 (1)</ispartof><rights>Author(s)</rights><rights>2024 Author(s). Published by AIP Publishing.</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><link.rule.ids>309,310,314,780,784,789,790,23929,23930,25139,27923,27924</link.rule.ids></links><search><contributor>Kovalev, Igor</contributor><contributor>Voroshilova, Anna</contributor><creatorcontrib>Zatonskiy, Andrey</creatorcontrib><creatorcontrib>Varlamova, Svetlana</creatorcontrib><creatorcontrib>Beknazarova, Saida</creatorcontrib><creatorcontrib>Gorbunova, Tatiana</creatorcontrib><creatorcontrib>Alutin, Petr</creatorcontrib><creatorcontrib>Belozerov, Oleg</creatorcontrib><creatorcontrib>Bazhenov, Ruslan</creatorcontrib><title>Software image defect detection of full-fashioned textures in textile industry</title><title>AIP conference proceedings</title><description>The purpose of the research is to detect defects in textile industry using computer vision and fuzzy logic techniques. The paper presents various practices used for edge detection, including a fuzzy logic applied. By testing, a fuzzy logic method has been chosen to obtain a respectable result. The algorithm that is observed in the paper is improved by dividing the processing into two phases: a fast one, which allows us to assume that there is a defect, and a searching one, which allows a defect to be highlighted in color. The advanced algorithm was tested on several types of fabrics. An average background arrangement is obtained for them. That allows separating fabric texture and color from potential defects. The tests were also performed on fabrics (cloths) with different brightness, number and type of defects. We obtained the percentage ratios of the defect detection quality and so we suggested the ways to develop the system.</description><subject>Algorithms</subject><subject>Color</subject><subject>Computer vision</subject><subject>Defects</subject><subject>Edge detection</subject><subject>Fabrics</subject><subject>Fuzzy logic</subject><subject>Textile industry</subject><issn>0094-243X</issn><issn>1551-7616</issn><fulltext>true</fulltext><rsrctype>conference_proceeding</rsrctype><creationdate>2024</creationdate><recordtype>conference_proceeding</recordtype><recordid>eNotUE1LxDAQDaLgunrwHxS8CdVJJ2mboyx-waIHFbyFpJ1ol9quSYruvzfr7unNwJt5H4ydc7jiUOK1vAKuirqsDtiMS8nzquTlIZsBKJEXAt-P2UkIK4BCVVU9Y08vo4s_xlPWfZkPylpy1MQEMUE3DtnoMjf1fe5M-Ew7tVmk3zh5Clk3_M9dn46HdgrRb07ZkTN9oLM9ztnb3e3r4iFfPt8_Lm6W-ZojxtwgiWQMSkFNQU5BDappQdkGkzxUnGNhnauF5MI6i5UUiqwwjbSulRZxzi52f9d-_J4oRL0aJz8kSY3AJWAqARLrcscKTRfNNo5e-5TTbzQHve1LS73vC_8APTpdnQ</recordid><startdate>20240329</startdate><enddate>20240329</enddate><creator>Zatonskiy, Andrey</creator><creator>Varlamova, Svetlana</creator><creator>Beknazarova, Saida</creator><creator>Gorbunova, Tatiana</creator><creator>Alutin, Petr</creator><creator>Belozerov, Oleg</creator><creator>Bazhenov, Ruslan</creator><general>American Institute of Physics</general><scope>8FD</scope><scope>H8D</scope><scope>L7M</scope></search><sort><creationdate>20240329</creationdate><title>Software image defect detection of full-fashioned textures in textile industry</title><author>Zatonskiy, Andrey ; Varlamova, Svetlana ; Beknazarova, Saida ; Gorbunova, Tatiana ; Alutin, Petr ; Belozerov, Oleg ; Bazhenov, Ruslan</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-p133t-a3e4761064ec2ef90809cd09bc3fec071132bff84514bfb37549eb4ac5bfd5b33</frbrgroupid><rsrctype>conference_proceedings</rsrctype><prefilter>conference_proceedings</prefilter><language>eng</language><creationdate>2024</creationdate><topic>Algorithms</topic><topic>Color</topic><topic>Computer vision</topic><topic>Defects</topic><topic>Edge detection</topic><topic>Fabrics</topic><topic>Fuzzy logic</topic><topic>Textile industry</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Zatonskiy, Andrey</creatorcontrib><creatorcontrib>Varlamova, Svetlana</creatorcontrib><creatorcontrib>Beknazarova, Saida</creatorcontrib><creatorcontrib>Gorbunova, Tatiana</creatorcontrib><creatorcontrib>Alutin, Petr</creatorcontrib><creatorcontrib>Belozerov, Oleg</creatorcontrib><creatorcontrib>Bazhenov, Ruslan</creatorcontrib><collection>Technology Research Database</collection><collection>Aerospace Database</collection><collection>Advanced Technologies Database with Aerospace</collection></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Zatonskiy, Andrey</au><au>Varlamova, Svetlana</au><au>Beknazarova, Saida</au><au>Gorbunova, Tatiana</au><au>Alutin, Petr</au><au>Belozerov, Oleg</au><au>Bazhenov, Ruslan</au><au>Kovalev, Igor</au><au>Voroshilova, Anna</au><format>book</format><genre>proceeding</genre><ristype>CONF</ristype><atitle>Software image defect detection of full-fashioned textures in textile industry</atitle><btitle>AIP conference proceedings</btitle><date>2024-03-29</date><risdate>2024</risdate><volume>3021</volume><issue>1</issue><issn>0094-243X</issn><eissn>1551-7616</eissn><coden>APCPCS</coden><abstract>The purpose of the research is to detect defects in textile industry using computer vision and fuzzy logic techniques. The paper presents various practices used for edge detection, including a fuzzy logic applied. By testing, a fuzzy logic method has been chosen to obtain a respectable result. The algorithm that is observed in the paper is improved by dividing the processing into two phases: a fast one, which allows us to assume that there is a defect, and a searching one, which allows a defect to be highlighted in color. The advanced algorithm was tested on several types of fabrics. An average background arrangement is obtained for them. That allows separating fabric texture and color from potential defects. The tests were also performed on fabrics (cloths) with different brightness, number and type of defects. We obtained the percentage ratios of the defect detection quality and so we suggested the ways to develop the system.</abstract><cop>Melville</cop><pub>American Institute of Physics</pub><doi>10.1063/5.0192867</doi><tpages>6</tpages></addata></record>
fulltext fulltext
identifier ISSN: 0094-243X
ispartof AIP conference proceedings, 2024, Vol.3021 (1)
issn 0094-243X
1551-7616
language eng
recordid cdi_proquest_journals_3015031920
source American Institute of Physics:Jisc Collections:Transitional Journals Agreement 2021-23 (Reading list)
subjects Algorithms
Color
Computer vision
Defects
Edge detection
Fabrics
Fuzzy logic
Textile industry
title Software image defect detection of full-fashioned textures in textile industry
url http://sfxeu10.hosted.exlibrisgroup.com/loughborough?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2025-01-13T04%3A13%3A21IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-proquest_scita&rft_val_fmt=info:ofi/fmt:kev:mtx:book&rft.genre=proceeding&rft.atitle=Software%20image%20defect%20detection%20of%20full-fashioned%20textures%20in%20textile%20industry&rft.btitle=AIP%20conference%20proceedings&rft.au=Zatonskiy,%20Andrey&rft.date=2024-03-29&rft.volume=3021&rft.issue=1&rft.issn=0094-243X&rft.eissn=1551-7616&rft.coden=APCPCS&rft_id=info:doi/10.1063/5.0192867&rft_dat=%3Cproquest_scita%3E3015031920%3C/proquest_scita%3E%3Cgrp_id%3Ecdi_FETCH-LOGICAL-p133t-a3e4761064ec2ef90809cd09bc3fec071132bff84514bfb37549eb4ac5bfd5b33%3C/grp_id%3E%3Coa%3E%3C/oa%3E%3Curl%3E%3C/url%3E&rft_id=info:oai/&rft_pqid=3015031920&rft_id=info:pmid/&rfr_iscdi=true