CN110335243B - 一种基于纹理对比的轮胎x光病疵检测方法 - Google Patents
一种基于纹理对比的轮胎x光病疵检测方法 Download PDFInfo
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- CN110335243B CN110335243B CN201910414699.9A CN201910414699A CN110335243B CN 110335243 B CN110335243 B CN 110335243B CN 201910414699 A CN201910414699 A CN 201910414699A CN 110335243 B CN110335243 B CN 110335243B
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- 230000007547 defect Effects 0.000 title claims abstract description 41
- 238000001514 detection method Methods 0.000 title claims abstract description 10
- 238000000034 method Methods 0.000 claims abstract description 7
- 238000003708 edge detection Methods 0.000 claims abstract description 6
- 238000007781 pre-processing Methods 0.000 claims description 5
- 238000004364 calculation method Methods 0.000 abstract description 2
- 238000012372 quality testing Methods 0.000 abstract description 2
- 238000007689 inspection Methods 0.000 description 5
- 230000001629 suppression Effects 0.000 description 4
- 230000002950 deficient Effects 0.000 description 3
- 238000012544 monitoring process Methods 0.000 description 3
- 229910000831 Steel Inorganic materials 0.000 description 2
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- 201000010099 disease Diseases 0.000 description 2
- 208000037265 diseases, disorders, signs and symptoms Diseases 0.000 description 2
- 210000003754 fetus Anatomy 0.000 description 2
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N23/00—Investigating or analysing materials by the use of wave or particle radiation, e.g. X-rays or neutrons, not covered by groups G01N3/00 – G01N17/00, G01N21/00 or G01N22/00
- G01N23/02—Investigating or analysing materials by the use of wave or particle radiation, e.g. X-rays or neutrons, not covered by groups G01N3/00 – G01N17/00, G01N21/00 or G01N22/00 by transmitting the radiation through the material
- G01N23/04—Investigating or analysing materials by the use of wave or particle radiation, e.g. X-rays or neutrons, not covered by groups G01N3/00 – G01N17/00, G01N21/00 or G01N22/00 by transmitting the radiation through the material and forming images of the material
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- 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
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T7/00—Image analysis
- G06T7/10—Segmentation; Edge detection
- G06T7/13—Edge detection
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T7/00—Image analysis
- G06T7/40—Analysis of texture
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- 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
- G06T2207/10116—X-ray image
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CN110335243B true CN110335243B (zh) | 2021-07-16 |
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Families Citing this family (1)
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CN110827272B (zh) * | 2019-11-13 | 2022-09-02 | 中国科学技术大学 | 一种基于图像处理的轮胎x光图像缺陷检测方法 |
Citations (5)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN105335692A (zh) * | 2014-08-15 | 2016-02-17 | 软控股份有限公司 | 一种轮胎x光图像检测识别方法及*** |
CN105869135A (zh) * | 2015-01-19 | 2016-08-17 | 青岛软控机电工程有限公司 | 轮胎缺陷的检测方法和装置 |
CN107316300A (zh) * | 2017-07-17 | 2017-11-03 | 杭州盈格信息技术有限公司 | 一种基于深度卷积神经网络的轮胎x光病疵检测方法 |
CN108564563A (zh) * | 2018-03-07 | 2018-09-21 | 浙江大学 | 一种基于Faster R-CNN的轮胎X光病疵检测方法 |
CN109523518A (zh) * | 2018-10-24 | 2019-03-26 | 浙江工业大学 | 一种轮胎x光病疵检测方法 |
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2019
- 2019-05-17 CN CN201910414699.9A patent/CN110335243B/zh active Active
Patent Citations (5)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN105335692A (zh) * | 2014-08-15 | 2016-02-17 | 软控股份有限公司 | 一种轮胎x光图像检测识别方法及*** |
CN105869135A (zh) * | 2015-01-19 | 2016-08-17 | 青岛软控机电工程有限公司 | 轮胎缺陷的检测方法和装置 |
CN107316300A (zh) * | 2017-07-17 | 2017-11-03 | 杭州盈格信息技术有限公司 | 一种基于深度卷积神经网络的轮胎x光病疵检测方法 |
CN108564563A (zh) * | 2018-03-07 | 2018-09-21 | 浙江大学 | 一种基于Faster R-CNN的轮胎X光病疵检测方法 |
CN109523518A (zh) * | 2018-10-24 | 2019-03-26 | 浙江工业大学 | 一种轮胎x光病疵检测方法 |
Non-Patent Citations (7)
Title |
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Defect Detection in Tire X-Ray Images Using Weighted Texture Dissimilarity;Qiang Guo等;《Hindawi》;20161231;第1-13页 * |
Detection of Impurity and Bubble Defects in Tire X-Ray Image Based on Improved Extremum Filter and Locally Adaptive-threshold Binaryzation;Xiunan Zheng等;《2018 International Conference on Security, Pattern Analysis, and Cybernetics (SPAC)》;20181231;第1-10页 * |
Tire X-ray Image Impurity Detection Based on Multiple Kernel Learning;Shuai Zhao等;《SpringerLink》;20180510;第346-355页 * |
全钢子午线轮胎缺陷识别***的研制;朱越等;《光电工程》;20090531;第36卷(第5期);第129-133页 * |
基于穿线法的轮胎帘线弯曲缺陷检测;郑修楠等;《济南大学学报(自然科学版)》;20180731;第32卷(第4期);第286-290页 * |
基于穿线法的轮胎帘线断裂缺陷检测;张潘杰等;《济南大学学报(自然科学版)》;20180331;第32卷(第2期);第102-106页 * |
基于穿线法的轮胎胎侧帘线稀疏缺陷的检测;陈仁龙等;《济南大学学报(自然科学版)》;20180930;第32卷(第5期);第417-421页 * |
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Effective date of registration: 20211208 Address after: 310000 room 604-605, building 16, No. 57, Science Park, Baiyang street, Hangzhou Economic and Technological Development Zone, Zhejiang Province Patentee after: HANGZHOU YINGGE INFORMATION TECHNOLOGY CO.,LTD. Address before: 310018 room 9, room 1213-1218, building 17, No. 57, kejiyuan Road, Baiyang street, Hangzhou Economic and Technological Development Zone, Zhejiang Province Patentee before: Hangzhou Data Point Gold Technology Co.,Ltd. |
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Denomination of invention: A tire X-ray defect detection method based on texture comparison Granted publication date: 20210716 Pledgee: Bank of Hangzhou Limited by Share Ltd. science and Technology Branch Pledgor: HANGZHOU YINGGE INFORMATION TECHNOLOGY CO.,LTD. Registration number: Y2024980007889 |
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