CN114757900A - 基于人工智能的纺织品缺陷类型识别方法 - Google Patents
基于人工智能的纺织品缺陷类型识别方法 Download PDFInfo
- Publication number
- CN114757900A CN114757900A CN202210346780.XA CN202210346780A CN114757900A CN 114757900 A CN114757900 A CN 114757900A CN 202210346780 A CN202210346780 A CN 202210346780A CN 114757900 A CN114757900 A CN 114757900A
- Authority
- CN
- China
- Prior art keywords
- defect
- textile
- cluster
- area
- clustering
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Granted
Links
- 230000007547 defect Effects 0.000 title claims abstract description 210
- 239000004753 textile Substances 0.000 title claims abstract description 111
- 238000000034 method Methods 0.000 title claims abstract description 48
- 238000013473 artificial intelligence Methods 0.000 title claims abstract description 24
- 238000005520 cutting process Methods 0.000 claims abstract description 6
- 239000013598 vector Substances 0.000 claims description 18
- 238000012549 training Methods 0.000 claims description 17
- 238000000605 extraction Methods 0.000 claims description 10
- 238000001914 filtration Methods 0.000 claims description 10
- 230000008569 process Effects 0.000 claims description 7
- 238000002372 labelling Methods 0.000 claims description 6
- 238000012216 screening Methods 0.000 claims description 2
- 238000001514 detection method Methods 0.000 description 20
- 230000002950 deficient Effects 0.000 description 6
- 238000009826 distribution Methods 0.000 description 5
- 238000012545 processing Methods 0.000 description 4
- 230000009286 beneficial effect Effects 0.000 description 3
- 230000002159 abnormal effect Effects 0.000 description 2
- 238000004458 analytical method Methods 0.000 description 2
- 235000012343 cottonseed oil Nutrition 0.000 description 2
- 108700041286 delta Proteins 0.000 description 2
- 239000000284 extract Substances 0.000 description 2
- 238000010008 shearing Methods 0.000 description 2
- 238000012360 testing method Methods 0.000 description 2
- 241000221931 Hypomyces rosellus Species 0.000 description 1
- 230000003796 beauty Effects 0.000 description 1
- 238000012512 characterization method Methods 0.000 description 1
- 238000010276 construction Methods 0.000 description 1
- 230000000694 effects Effects 0.000 description 1
- 238000005516 engineering process Methods 0.000 description 1
- 239000004744 fabric Substances 0.000 description 1
- 238000009776 industrial production Methods 0.000 description 1
- 230000007257 malfunction Effects 0.000 description 1
- 238000004519 manufacturing process Methods 0.000 description 1
- 238000002156 mixing Methods 0.000 description 1
- 238000012986 modification Methods 0.000 description 1
- 230000004048 modification Effects 0.000 description 1
- 238000003062 neural network model Methods 0.000 description 1
- 230000008439 repair process Effects 0.000 description 1
Images
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T7/00—Image analysis
- G06T7/0002—Inspection of images, e.g. flaw detection
- G06T7/0004—Industrial image inspection
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F18/00—Pattern recognition
- G06F18/20—Analysing
- G06F18/22—Matching criteria, e.g. proximity measures
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F18/00—Pattern recognition
- G06F18/20—Analysing
- G06F18/23—Clustering techniques
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
- G06N3/00—Computing arrangements based on biological models
- G06N3/02—Neural networks
- G06N3/04—Architecture, e.g. interconnection topology
- G06N3/045—Combinations of networks
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
- G06N3/00—Computing arrangements based on biological models
- G06N3/02—Neural networks
- G06N3/08—Learning methods
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T7/00—Image analysis
- G06T7/10—Segmentation; Edge detection
- G06T7/11—Region-based segmentation
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T7/00—Image analysis
- G06T7/90—Determination of colour characteristics
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T2207/00—Indexing scheme for image analysis or image enhancement
- G06T2207/10—Image acquisition modality
- G06T2207/10024—Color image
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T2207/00—Indexing scheme for image analysis or image enhancement
- G06T2207/20—Special algorithmic details
- G06T2207/20081—Training; Learning
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T2207/00—Indexing scheme for image analysis or image enhancement
- G06T2207/20—Special algorithmic details
- G06T2207/20084—Artificial neural networks [ANN]
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T2207/00—Indexing scheme for image analysis or image enhancement
- G06T2207/30—Subject of image; Context of image processing
- G06T2207/30108—Industrial image inspection
- G06T2207/30124—Fabrics; Textile; Paper
-
- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02P—CLIMATE CHANGE MITIGATION TECHNOLOGIES IN THE PRODUCTION OR PROCESSING OF GOODS
- Y02P90/00—Enabling technologies with a potential contribution to greenhouse gas [GHG] emissions mitigation
- Y02P90/30—Computing systems specially adapted for manufacturing
Landscapes
- Engineering & Computer Science (AREA)
- Theoretical Computer Science (AREA)
- Physics & Mathematics (AREA)
- General Physics & Mathematics (AREA)
- Data Mining & Analysis (AREA)
- Computer Vision & Pattern Recognition (AREA)
- General Engineering & Computer Science (AREA)
- Evolutionary Computation (AREA)
- Artificial Intelligence (AREA)
- Life Sciences & Earth Sciences (AREA)
- Biophysics (AREA)
- General Health & Medical Sciences (AREA)
- Bioinformatics & Computational Biology (AREA)
- Health & Medical Sciences (AREA)
- Biomedical Technology (AREA)
- Bioinformatics & Cheminformatics (AREA)
- Computational Linguistics (AREA)
- Evolutionary Biology (AREA)
- Molecular Biology (AREA)
- Computing Systems (AREA)
- Mathematical Physics (AREA)
- Software Systems (AREA)
- Quality & Reliability (AREA)
- Investigating Materials By The Use Of Optical Means Adapted For Particular Applications (AREA)
- Image Analysis (AREA)
Abstract
Description
Claims (8)
Priority Applications (1)
Application Number | Priority Date | Filing Date | Title |
---|---|---|---|
CN202210346780.XA CN114757900B (zh) | 2022-03-31 | 2022-03-31 | 基于人工智能的纺织品缺陷类型识别方法 |
Applications Claiming Priority (1)
Application Number | Priority Date | Filing Date | Title |
---|---|---|---|
CN202210346780.XA CN114757900B (zh) | 2022-03-31 | 2022-03-31 | 基于人工智能的纺织品缺陷类型识别方法 |
Publications (2)
Publication Number | Publication Date |
---|---|
CN114757900A true CN114757900A (zh) | 2022-07-15 |
CN114757900B CN114757900B (zh) | 2023-04-07 |
Family
ID=82330073
Family Applications (1)
Application Number | Title | Priority Date | Filing Date |
---|---|---|---|
CN202210346780.XA Active CN114757900B (zh) | 2022-03-31 | 2022-03-31 | 基于人工智能的纺织品缺陷类型识别方法 |
Country Status (1)
Country | Link |
---|---|
CN (1) | CN114757900B (zh) |
Cited By (10)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN114998342A (zh) * | 2022-08-04 | 2022-09-02 | 海门市刘氏铸造有限公司 | 基于镀锌板面图案识别的镀锌工艺控制方法及装置 |
CN115018828A (zh) * | 2022-08-03 | 2022-09-06 | 深圳市尹泰明电子有限公司 | 一种电子元器件的缺陷检测方法 |
CN115082482A (zh) * | 2022-08-23 | 2022-09-20 | 山东优奭趸泵业科技有限公司 | 一种金属表面缺陷检测方法 |
CN115205296A (zh) * | 2022-09-16 | 2022-10-18 | 海安玻克超硬材料有限公司 | 一种光伏磨轮磨料层生产缺陷识别方法 |
CN115294140A (zh) * | 2022-10-09 | 2022-11-04 | 南通永卓金属制品有限公司 | 一种五金零件缺陷检测方法及*** |
CN115311278A (zh) * | 2022-10-11 | 2022-11-08 | 南通欧惠纺织科技有限公司 | 一种对于纱线检测的纱线分割方法 |
CN116309493A (zh) * | 2023-03-24 | 2023-06-23 | 南通飞隼信息科技有限公司 | 一种用于纺织产品疵点检测的方法及*** |
CN116401570A (zh) * | 2023-05-26 | 2023-07-07 | 佛山市力天包装印刷有限公司 | 一种印刷质量监测大数据智能处理*** |
CN116894840A (zh) * | 2023-09-08 | 2023-10-17 | 南通世纪纺织有限公司 | 纺纱打样机产品质量检测方法及*** |
CN117152148A (zh) * | 2023-10-31 | 2023-12-01 | 南通杰元纺织品有限公司 | 一种纺织物毛斑缺陷检测方法 |
Citations (12)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
EP0563897A1 (en) * | 1992-03-30 | 1993-10-06 | Fuji Photo Film Co., Ltd. | Defect inspection system |
JP2010164487A (ja) * | 2009-01-16 | 2010-07-29 | Tokyo Seimitsu Co Ltd | 欠陥検査装置及び欠陥検査方法 |
US20150098655A1 (en) * | 2013-10-08 | 2015-04-09 | National Tsing Hua University | Method of Defect Image Classification through Integrating Image Analysis and Data Mining |
CN107169956A (zh) * | 2017-04-28 | 2017-09-15 | 西安工程大学 | 基于卷积神经网络的色织物疵点检测方法 |
CN107643295A (zh) * | 2017-08-24 | 2018-01-30 | 中国地质大学(武汉) | 一种基于机器视觉的布匹缺陷在线检测的方法和*** |
CN110222792A (zh) * | 2019-06-20 | 2019-09-10 | 杭州电子科技大学 | 一种基于孪生网络的标签缺陷检测算法 |
CN111553898A (zh) * | 2020-04-27 | 2020-08-18 | 东华大学 | 一种基于卷积神经网络的面料疵点检测方法 |
CN112164033A (zh) * | 2020-09-14 | 2021-01-01 | 华中科技大学 | 一种基于异常特征编辑的对抗网络纹理表面缺陷检测方法 |
CN112630222A (zh) * | 2020-11-24 | 2021-04-09 | 河海大学常州校区 | 一种基于机器视觉的手机盖板玻璃缺陷检测方法 |
CN113112483A (zh) * | 2021-04-16 | 2021-07-13 | 合肥科大智能机器人技术有限公司 | 一种基于相似度度量的刚性接触网缺陷检测方法及*** |
CN113554080A (zh) * | 2021-07-15 | 2021-10-26 | 长沙长泰机器人有限公司 | 一种基于机器视觉的无纺布瑕疵检测分类方法及*** |
CN114170208A (zh) * | 2021-12-14 | 2022-03-11 | 武汉福旺家包装有限公司 | 一种基于人工智能的纸制品缺陷检测方法 |
-
2022
- 2022-03-31 CN CN202210346780.XA patent/CN114757900B/zh active Active
Patent Citations (12)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
EP0563897A1 (en) * | 1992-03-30 | 1993-10-06 | Fuji Photo Film Co., Ltd. | Defect inspection system |
JP2010164487A (ja) * | 2009-01-16 | 2010-07-29 | Tokyo Seimitsu Co Ltd | 欠陥検査装置及び欠陥検査方法 |
US20150098655A1 (en) * | 2013-10-08 | 2015-04-09 | National Tsing Hua University | Method of Defect Image Classification through Integrating Image Analysis and Data Mining |
CN107169956A (zh) * | 2017-04-28 | 2017-09-15 | 西安工程大学 | 基于卷积神经网络的色织物疵点检测方法 |
CN107643295A (zh) * | 2017-08-24 | 2018-01-30 | 中国地质大学(武汉) | 一种基于机器视觉的布匹缺陷在线检测的方法和*** |
CN110222792A (zh) * | 2019-06-20 | 2019-09-10 | 杭州电子科技大学 | 一种基于孪生网络的标签缺陷检测算法 |
CN111553898A (zh) * | 2020-04-27 | 2020-08-18 | 东华大学 | 一种基于卷积神经网络的面料疵点检测方法 |
CN112164033A (zh) * | 2020-09-14 | 2021-01-01 | 华中科技大学 | 一种基于异常特征编辑的对抗网络纹理表面缺陷检测方法 |
CN112630222A (zh) * | 2020-11-24 | 2021-04-09 | 河海大学常州校区 | 一种基于机器视觉的手机盖板玻璃缺陷检测方法 |
CN113112483A (zh) * | 2021-04-16 | 2021-07-13 | 合肥科大智能机器人技术有限公司 | 一种基于相似度度量的刚性接触网缺陷检测方法及*** |
CN113554080A (zh) * | 2021-07-15 | 2021-10-26 | 长沙长泰机器人有限公司 | 一种基于机器视觉的无纺布瑕疵检测分类方法及*** |
CN114170208A (zh) * | 2021-12-14 | 2022-03-11 | 武汉福旺家包装有限公司 | 一种基于人工智能的纸制品缺陷检测方法 |
Non-Patent Citations (2)
Title |
---|
SOO CHANGKIM ET AL.: "Texture classification and segmentation using wavelet packet frame and Gaussian mixture model", 《PATTERN RECOGNITION》 * |
刘万春等: "基于聚类分析和支持向量机的布匹瑕疵分类方法", 《北京理工大学学报》 * |
Cited By (15)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN115018828A (zh) * | 2022-08-03 | 2022-09-06 | 深圳市尹泰明电子有限公司 | 一种电子元器件的缺陷检测方法 |
CN114998342A (zh) * | 2022-08-04 | 2022-09-02 | 海门市刘氏铸造有限公司 | 基于镀锌板面图案识别的镀锌工艺控制方法及装置 |
CN115082482B (zh) * | 2022-08-23 | 2022-11-22 | 山东优奭趸泵业科技有限公司 | 一种金属表面缺陷检测方法 |
CN115082482A (zh) * | 2022-08-23 | 2022-09-20 | 山东优奭趸泵业科技有限公司 | 一种金属表面缺陷检测方法 |
CN115205296A (zh) * | 2022-09-16 | 2022-10-18 | 海安玻克超硬材料有限公司 | 一种光伏磨轮磨料层生产缺陷识别方法 |
CN115294140A (zh) * | 2022-10-09 | 2022-11-04 | 南通永卓金属制品有限公司 | 一种五金零件缺陷检测方法及*** |
CN115311278A (zh) * | 2022-10-11 | 2022-11-08 | 南通欧惠纺织科技有限公司 | 一种对于纱线检测的纱线分割方法 |
CN115311278B (zh) * | 2022-10-11 | 2023-12-22 | 南通欧惠纺织科技有限公司 | 一种对于纱线检测的纱线分割方法 |
CN116309493A (zh) * | 2023-03-24 | 2023-06-23 | 南通飞隼信息科技有限公司 | 一种用于纺织产品疵点检测的方法及*** |
CN116401570A (zh) * | 2023-05-26 | 2023-07-07 | 佛山市力天包装印刷有限公司 | 一种印刷质量监测大数据智能处理*** |
CN116401570B (zh) * | 2023-05-26 | 2023-08-11 | 佛山市力天包装印刷有限公司 | 一种印刷质量监测大数据智能处理*** |
CN116894840A (zh) * | 2023-09-08 | 2023-10-17 | 南通世纪纺织有限公司 | 纺纱打样机产品质量检测方法及*** |
CN116894840B (zh) * | 2023-09-08 | 2023-11-17 | 南通世纪纺织有限公司 | 纺纱打样机产品质量检测方法及*** |
CN117152148A (zh) * | 2023-10-31 | 2023-12-01 | 南通杰元纺织品有限公司 | 一种纺织物毛斑缺陷检测方法 |
CN117152148B (zh) * | 2023-10-31 | 2023-12-29 | 南通杰元纺织品有限公司 | 一种纺织物毛斑缺陷检测方法 |
Also Published As
Publication number | Publication date |
---|---|
CN114757900B (zh) | 2023-04-07 |
Similar Documents
Publication | Publication Date | Title |
---|---|---|
CN114757900B (zh) | 基于人工智能的纺织品缺陷类型识别方法 | |
CN113989279B (zh) | 基于人工智能及图像处理的塑料薄膜质量检测方法 | |
CN114549522B (zh) | 基于目标检测的纺织品质量检测方法 | |
CN109934802B (zh) | 一种基于傅里叶变换和图像形态学的布匹疵点检测方法 | |
CN108562589B (zh) | 一种对磁路材料表面缺陷进行检测的方法 | |
CN114419025A (zh) | 一种基于图像处理的纤维板质量评估方法 | |
CN116205919B (zh) | 基于人工智能的五金零件生产质量检测方法及*** | |
CN108181316B (zh) | 一种基于机器视觉的竹条缺陷检测方法 | |
CN115082683A (zh) | 一种基于图像处理的注塑缺陷检测方法 | |
CN107220649A (zh) | 一种素色布匹缺陷检测和分类方法 | |
CN111507426B (zh) | 基于视觉融合特征的无参考图像质量分级评价方法及装置 | |
CN113935666B (zh) | 基于图像处理的建筑装饰墙面砖异常评估方法 | |
CN114627125B (zh) | 一种基于光学手段的不锈钢压片机表面质量评估方法 | |
CN106557740B (zh) | 一种遥感图像中油库目标的识别方法 | |
CN114723704A (zh) | 一种基于图像处理的纺织品质量评估方法 | |
CN114820625B (zh) | 一种汽车顶块缺陷检测方法 | |
CN113706490B (zh) | 一种晶片缺陷检测方法 | |
CN113221881B (zh) | 一种多层级的智能手机屏幕缺陷检测方法 | |
CN115294116A (zh) | 基于人工智能的纺织材料染色质量评估方法、装置及*** | |
CN115294377A (zh) | 一种道路裂缝的识别***及方法 | |
CN113516619A (zh) | 一种基于图像处理技术的产品表面瑕疵识别方法 | |
CN112435235A (zh) | 一种基于图像分析的籽棉含杂率检测方法 | |
CN116152242A (zh) | 一种篮球用天然皮革缺陷可视化检测*** | |
CN117036314A (zh) | 一种高密度柔性ic基板氧化区域检测方法 | |
CN114937042B (zh) | 基于机器视觉的塑料制品质量评估方法 |
Legal Events
Date | Code | Title | Description |
---|---|---|---|
PB01 | Publication | ||
PB01 | Publication | ||
SE01 | Entry into force of request for substantive examination | ||
SE01 | Entry into force of request for substantive examination | ||
TA01 | Transfer of patent application right |
Effective date of registration: 20230322 Address after: Building 1, Warp Knitting Industrial Town, Yangxunqiao Town, Keqiao District, Shaoxing City, Zhejiang Province, 312030 Applicant after: SHAOXING KEQIAO QINUO HOME TEXTILE ARTICLES CO.,LTD. Address before: 226200 Binhai Industrial Park, Qidong City, Nantong City, Jiangsu Province (in Baiyue new material technology Qidong Co., Ltd.) Applicant before: Qidong xinpenglai Textile Technology Co.,Ltd. |
|
TA01 | Transfer of patent application right | ||
GR01 | Patent grant | ||
GR01 | Patent grant | ||
PE01 | Entry into force of the registration of the contract for pledge of patent right |
Denomination of invention: A Method for Identifying Textile Defect Types Based on Artificial Intelligence Effective date of registration: 20230531 Granted publication date: 20230407 Pledgee: Zhejiang Shaoxing Ruifeng Rural Commercial Bank Co.,Ltd. Yangxunqiao sub branch Pledgor: SHAOXING KEQIAO QINUO HOME TEXTILE ARTICLES CO.,LTD. Registration number: Y2023980042340 |
|
PE01 | Entry into force of the registration of the contract for pledge of patent right |