CN106970090A - Embryo cloth defective vision detection device and method - Google Patents
Embryo cloth defective vision detection device and method Download PDFInfo
- Publication number
- CN106970090A CN106970090A CN201710287368.4A CN201710287368A CN106970090A CN 106970090 A CN106970090 A CN 106970090A CN 201710287368 A CN201710287368 A CN 201710287368A CN 106970090 A CN106970090 A CN 106970090A
- Authority
- CN
- China
- Prior art keywords
- defect
- embryo cloth
- detection
- size
- detection device
- 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.)
- Pending
Links
- 238000001514 detection method Methods 0.000 title claims abstract description 75
- 239000004744 fabric Substances 0.000 title claims abstract description 68
- 210000001161 mammalian embryo Anatomy 0.000 title claims abstract description 40
- 230000002950 deficient Effects 0.000 title claims abstract description 36
- 230000004438 eyesight Effects 0.000 title claims abstract description 33
- 238000000034 method Methods 0.000 title description 6
- 230000007547 defect Effects 0.000 claims abstract description 51
- 230000007246 mechanism Effects 0.000 claims abstract description 20
- 238000007689 inspection Methods 0.000 claims abstract description 13
- 238000005562 fading Methods 0.000 claims description 3
- 238000002347 injection Methods 0.000 claims description 3
- 239000007924 injection Substances 0.000 claims description 3
- 239000007921 spray Substances 0.000 claims description 2
- 239000004753 textile Substances 0.000 abstract description 10
- 238000004519 manufacturing process Methods 0.000 abstract description 4
- 238000009941 weaving Methods 0.000 abstract description 4
- 230000007812 deficiency Effects 0.000 abstract description 3
- 238000012372 quality testing Methods 0.000 abstract description 3
- 238000004804 winding Methods 0.000 description 17
- 238000007641 inkjet printing Methods 0.000 description 4
- 238000007639 printing Methods 0.000 description 4
- 208000028804 PERCHING syndrome Diseases 0.000 description 3
- 238000005516 engineering process Methods 0.000 description 3
- 238000012545 processing Methods 0.000 description 3
- 238000006243 chemical reaction Methods 0.000 description 2
- 238000000605 extraction Methods 0.000 description 2
- 238000003384 imaging method Methods 0.000 description 2
- 230000000007 visual effect Effects 0.000 description 2
- 239000008358 core component Substances 0.000 description 1
- 238000011161 development Methods 0.000 description 1
- 238000010586 diagram Methods 0.000 description 1
- 238000011156 evaluation Methods 0.000 description 1
- 238000009940 knitting Methods 0.000 description 1
- 230000035515 penetration Effects 0.000 description 1
- 238000012797 qualification Methods 0.000 description 1
- 230000009967 tasteless effect Effects 0.000 description 1
- 230000009466 transformation Effects 0.000 description 1
Classifications
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N21/00—Investigating or analysing materials by the use of optical means, i.e. using sub-millimetre waves, infrared, visible or ultraviolet light
- G01N21/84—Systems specially adapted for particular applications
- G01N21/88—Investigating the presence of flaws or contamination
- G01N21/95—Investigating the presence of flaws or contamination characterised by the material or shape of the object to be examined
Landscapes
- Physics & Mathematics (AREA)
- Health & Medical Sciences (AREA)
- Life Sciences & Earth Sciences (AREA)
- Chemical & Material Sciences (AREA)
- Analytical Chemistry (AREA)
- Biochemistry (AREA)
- General Health & Medical Sciences (AREA)
- General Physics & Mathematics (AREA)
- Immunology (AREA)
- Pathology (AREA)
- Treatment Of Fiber Materials (AREA)
- Ink Jet (AREA)
Abstract
For the deficiency of existing detection technique, with reference to all kinds of weaving mill's demands, the invention provides a kind of embryo cloth defective vision detection device, it at least includes vision-based detection platform and ink-jet marking mechanism, and a kind of embryo cloth Inspection Algorithm progress defects detection identification based on multithreading has been used in combination by vision-based detection platform and has been marked by ink-jet marking mechanism.It can realize embryo cloth defects detection automatically and preserve defective data in the local database, its detection speed and recall rate are far above artificial detection, so as to increase the production efficiency of textile mills, hand labor intensity is greatly reduced, labour expenses of the textile mills in terms of quality testing are reduced.
Description
Technical field
The invention belongs to textile technology field, and in particular to one kind knitting embryo cloth visual detection equipment and method.
Background technology
In textile industry, there is flaw in cloth, then price will reduce 45%-65%, and fabric defects has a strong impact on weaving row
Industry income.Therefore, Fabric Defect detection is one of major tasks of textile mills.For a long time, cloth detection is general by people
Work is completed.Artificial detection speed is general per minute at 15-20 meters.Artificial detection relies on the experience and qualification of perching personnel,
Evaluation criterion is unstable inconsistent, thus often produces flase drop and missing inspection, and skilled perching personnel can only also have found about 70%
Fault.In addition, cloth defects detection is a heavy tasteless manual labor for workman, and greatly perching is injured
The eyesight of workman.The use of automatic piece goods detecting system is that production efficiency improves in textile mills, saves human cost, industrial transformation upgrading
The only way which must be passed.
In automatic Check cloth machine field, Domestic and abroad disparity is huge, is especially embodied in accuracy of detection and speed.This present situation with
The present situation of machine vision technique has certain relation, i.e. software development kit or platform all to be controlled by external several companies,
Domestic no or rare perfect high performance image processing software bag and development platform.In hardware aspect, the current country is just
Gradually pursuing, the hardware performance of fewer companies has reached international standards, but core component is also the absence of independence.It is based on
This present situation, the data that domestic automatic Check Bu Ji producers can find is considerably less, there is be discussed in detail less.Both at home and abroad can
Automatic Check cloth machine can be provided by finding relevant manufacturers, but its technology maturity is not enough, and price height enterprise, stability difference turns into automatic
The huge obstacle of Check cloth machine penetrations and promotions.
The content of the invention
For the deficiency of existing detection technique, with reference to all kinds of weaving mill's demands, regarded the invention provides a kind of embryo cloth defect
Feel detection device, embryo cloth defects detection can be realized automatically and is preserved defective data in the local database, its detection speed
With recall rate far above artificial detection, so as to increase the production efficiency of textile mills, hand labor intensity is greatly reduced, is reduced
Labour expenses of the textile mills in terms of quality testing.Present invention also offers a kind of embryo cloth quality inspection based on multithreading simultaneously
Method of determining and calculating framework so that the real-time of algorithm is guaranteed.
A kind of embryo cloth defective vision detection device, including vision-based detection platform, industrial computer and display, telltale, spray
Black marking mechanism, operating desk, many side rollers, cloth, edge aligning mechanism, winding cloth, light source bracket, unreel cloth, unreel
Roller, integral support.
The vision-based detection platform, which includes many line scan cameras, can cover the line style direct projection bar light of whole detection wide cut.
The ink-jet marking mechanism is that magnetic valve is at intervals of 100-150 millimeters into nozzle array by plurality of electromagnetic valve group.
After vision-based detection platform is handled image, the position where flaw point is obtained, flaw defect position is transmitted
To the control system of ink-jet marking mechanism, defective locations are marked for control system control ink-jet marking mechanism
The embryo cloth defective vision detection device has two kinds of mode of operations, and pattern one is shutdown mode, that is, detects defect
Shut down at once afterwards, notify staff to come to handle, shutdown mode comprises the following steps：
Step one：Feeding is initialized, guides the leftover of bolt of cloth successively to pass through punishment in advance side roller II (12), punishment in advance exhibition by staff
The cloth of side roller I (11) and winding side roller (14), manually about 1.5 meters of length of winding, forms winding cloth (13)
Step 2：Start detecting system.
Step 3：Single frames input picture is obtained, is schemed by a kind of embryo cloth Inspection Algorithm framework based on multithreading
As processing.
Step 4：Judge to whether there is defect in single frames input picture, if defect is present, defective data is saved in
Local data base, sends defect alarm command to control system, performs step 5.If there is no defect, then step 6 is performed.
Step 5：Control system receives defect alarm command, shuts down at once, is alarmed by warning lamp (9), notifies live work
Come to handle as personnel.
Step 6：If detection is not completed also, perform step 3 and start next circulation.If detection is completed, printing detection
Report.
The embryo cloth defective vision detection device mode of operation two is automatic marking mode, is comprised the following steps：
Step one：Feeding is initialized, guides the leftover of bolt of cloth successively to pass through punishment in advance side roller II (12), punishment in advance exhibition by staff
The cloth of side roller I (11) and winding side roller (14), manually about 1.5 meters of length of winding, forms winding cloth (13)
Step 2：Start detecting system.
Step 3：Single frames input picture is obtained, is schemed by a kind of embryo cloth Inspection Algorithm framework based on multithreading
As processing.
Step 4：Judge to whether there is defect in single frames input picture, if defect is present, defective data is saved in
Local data base, sends defective locations data to control system, performs step 5.If there is no defect, then step 6 is performed.
Step 5：Control system control ink jet printing mechanism (3) injection can fading ink defective locations are marked.
Step 6：If detection is not completed also, perform step 3 and start next circulation.If detection is completed, printing detection
Report.
A kind of embryo cloth Inspection Algorithm framework based on multithreading, comprises the following steps：
Step one：Input picture is obtained.Camera input image I is obtained from imaging systeminput, input image size for (m ×
1024)×(n×1024)
Step 2：Image block.Input picture is divided into m1×n1Individual unit_size × unit_size cell picture
Wherein 0≤i≤m1,0≤j≤n1。
Step 3：Newly-built size is m1×n1Thread queue Ti,j, to cell pictureCarry out block texture special
Levy extraction.Obtain block texture feature vectorWherein 0≤i≤m1,0≤j≤
n1。
Step 4：It is rightFurther subdivision, is divided into size for patch_size × patch_size, overlay region
Domain is the fritter that size is over_size
Wherein
Step 5：WithTexture boot vector is tieed up, each is calculated
Grain distribution, obtains shortage probability distributed image defect_priori,j。
Step 6：To defect_priori,jCarry out binary conversion treatment and obtain defect_segprior i,j, extract shortage probability
Pixel more than 75%, such as following formula：
According to defect_segprior I, jThe defect area size defect_area being partitioned intoi,jWith defect number defect_
counti,jJudgeIn whether there is defect, and defect information write into Databasce is preserved.If meeting following
Condition, then it is assumed thatMiddle existing defects, such as following formula：
Wherein Tr is the defect threshold value that user sets.
Step 7：Discharge thread queuing memory Ti,j。
Brief description of the drawings
Fig. 1 is the integrally-built front view of embryo cloth defective vision detection device
Fig. 2 is the integrally-built rear view of embryo cloth defective vision detection device
The partial view of Fig. 3 embryo cloth defective vision detection device vision-based detection platforms and ink jet printing mechanism
Fig. 4 is the system flow chart under shutdown mode
Fig. 5 is the system flow chart under automatic marking mode
Fig. 6 is a kind of embryo cloth Inspection Algorithm block flow diagram based on multithreading
Label declaration：
1. vision-based detection platform, 2. industrial computers and display, 3. ink jet printing mechanism, 4. operating desks, 5. winding sides
Roller, 6. punishment in advance cloth, 7. edge aligning mechanisms, 8. winding cloth, 9. telltales, 10. light source brackets, 11. punishment in advance side roller I,
12. punishment in advance side roller II, 13. winding cloth, 14. winding cloth side rollers, 15. integral supports, 16. encoders, 17. regard
Feel hardware platform magnification region, 18. cloth to be checked, 19. light sources, 20. industrial cameras, the 21. industrial camera visuals field, 22. ink nozzles.
Embodiment
Below in conjunction with the drawings and specific embodiments, the present invention is described in further detail：
For the deficiency of existing detection technique, with reference to all kinds of weaving mill's demands, regarded the invention provides a kind of embryo cloth defect
Feel detection device, embryo cloth defects detection can be realized automatically and is preserved defective data in the local database, its detection speed
With recall rate far above artificial detection, so as to increase the production efficiency of textile mills, hand labor intensity is greatly reduced, is reduced
Labour expenses of the textile mills in terms of quality testing.Present invention also offers a kind of embryo cloth quality inspection based on multithreading simultaneously
Method of determining and calculating framework so that the real-time of algorithm is guaranteed.Scheme highest detection speed reaches 6.5 meter per seconds, maximum detection wide cut
For 2 meters.
The vision-based detection platform, which includes 4 line scan cameras, can cover the line style direct projection bar light of whole detection wide cut.
The ink-jet marking mechanism is to constitute nozzle array by multiple valves, and nozzle pitch is 120 millimeters.
After vision-based detection platform (1) is handled image, the position where flaw point is obtained, flaw defect position is passed
The control system of ink-jet marking mechanism (3) is passed, defective locations are marked for control system control ink-jet marking mechanism.
The embryo cloth defective vision detection device has two kinds of mode of operations, and pattern one is shutdown mode, is illustrated in figure 4 mould
The flow chart of formula one, that is, detect after defect and shut down at once, notifies staff to come to handle, shutdown mode comprises the following steps：
Step one：Feeding is initialized, guides the leftover of bolt of cloth successively to pass through punishment in advance side roller II (12), punishment in advance exhibition by staff
The cloth of side roller I (11) and winding side roller (14), manually about 1.5 meters of length of winding, forms winding cloth (13)
Step 2：Start detecting system.
Step 3：IMAQ is carried out by encoder triggering camera, single frames input picture is obtained afterwards, by one kind based on many
The embryo cloth Inspection Algorithm framework of thread carries out image procossing.
Step 4：Judge to whether there is defect in single frames input picture, if defect is present, defective data is saved in
Local data base, sends defect alarm command to control system, performs step 5.If there is no defect, then step 6 is performed.
Step 5：Control system receives defect alarm command, shuts down at once, is alarmed by warning lamp (9), notifies live work
Come to handle as personnel.
Step 6：If detection is not completed also, perform step 3 and start next circulation.If detection is completed, printing detection
Report.
The embryo cloth defective vision detection device mode of operation two is automatic marking mode, is illustrated in figure 5 pattern second-rate
Cheng Tu, comprises the following steps：
Step one：Feeding is initialized, guides the leftover of bolt of cloth successively to pass through punishment in advance side roller II (12), punishment in advance exhibition by staff
The cloth of side roller I (11) and winding side roller (14), manually about 1.5 meters of length of winding, forms winding cloth (13)
Step 2：Start detecting system.
Step 3：Single frames input picture is obtained, is schemed by a kind of embryo cloth Inspection Algorithm framework based on multithreading
As processing.
Step 4：Judge to whether there is defect in single frames input picture, if defect is present, defective data is saved in
Local data base, sends defective locations data to control system, performs step 5.If there is no defect, then step 6 is performed.
Step 5：Control system control ink jet printing mechanism (3) injection can fading ink defective locations are marked.
Step 6：If detection is not completed also, perform step 3 and start next circulation.If detection is completed, printing detection
Report.
A kind of embryo cloth Inspection Algorithm framework based on multithreading, is illustrated in figure 6 algorithm flow chart, including following step
Suddenly：
Step one：Input picture is obtained.Camera input image I is obtained from imaging systeminput, input image size for (m ×
1024) × (n × 1024), wherein m=4, n=1.
Step 2：Image block.Input picture is divided into m1×n1Individual unit_size × unit_size cell picture
Wherein 0≤i≤m1,0≤j≤n1。m1=16, n1=4, unit_size=256
Step 3：Newly-built size is m1×n1Thread queue Ti,j, to cell pictureCarry out block texture special
Levy extraction.Obtain block texture feature vectorWherein 0≤i≤m1,0≤j≤
n1。
Step 4：It is rightFurther subdivision, is divided into size for patch_size × patch_size, overlay region
Domain is the fritter that size is over_sizeWherein patch_size=16, over_size=8
Wherein 0≤u≤30,0≤v≤30
Step 5：WithTexture boot vector is tieed up, each is calculated
Grain distribution, obtains shortage probability distributed image defect_priori,j。
Step 6：To defect_priori,jCarry out binary conversion treatment and obtain defect_segprior i,j, extract shortage probability
Pixel more than 75%, such as following formula：
Wherein, unitsize=256
According to defect_segprior i,jThe defect area size defect_area being partitioned intoi,jWith defect number defect_
counti,jJudgeIn whether there is defect, and defect information write into Databasce is preserved.If meeting following
Condition, then it is assumed thatMiddle existing defects, such as following formula：
Wherein Tr is the defect threshold value that user sets.
Tr=25 in this example, corresponds to actual flaw size for 0.5mm × 0.5mm
Step 7：Discharge thread queuing memory Ti,j。
Claims (5)
1. a kind of embryo cloth defective vision detection device, including vision-based detection platform and ink-jet marking mechanism, it is characterised in that
The vision-based detection platform includes many line scan cameras, and the ink-jet marking mechanism includes the spray that plurality of electromagnetic valve is controlled
Mouth array and control system,
The vision-based detection platform scanner simultaneously obtains the image of the embryo cloth and the flaw point of the embryo cloth is obtained after being handled
The position at place, and the position where flaw point is passed to the control system of ink-jet marking mechanism, control system control ink-jet
The position is marked marking mechanism.
2. embryo cloth defective vision detection device as claimed in claim 1, the embryo cloth defective vision detection device has two kinds of works
Operation mode, mode of operation one is shutdown mode, and mode of operation two is automatic marking mode.
3. embryo cloth defective vision detection device as claimed in claim 2, wherein the shutdown mode comprises the following steps：
Step one：Initialize feeding；
Step 2：Start the embryo cloth defective vision detection device；
Step 3：Single frames input picture is obtained, image procossing is carried out by the embryo cloth Inspection Algorithm based on multithreading；
Step 4：Judge to whether there is defect in single frames input picture, if defect is present, defective data is saved in locally
Database, sends defect alarm command to control system, performs step 5, if there is no defect, then perform step 6；
Step 5：Control system receives defect alarm command, shuts down at once, is alarmed by warning lamp, notifies field personnel
Come to handle；
Step 6：If detection is not completed also, step 3 is performed, if detection is completed, examining report is printed.
4. embryo cloth defective vision detection device as claimed in claim 2, wherein automatic marking mode comprises the following steps：
Step one：Initialize feeding；
Step 2：Start the embryo cloth defective vision detection device；
Step 3：Single frames input picture is obtained, image procossing is carried out by the embryo cloth Inspection Algorithm based on multithreading；
Step 4：Judge to whether there is defect in single frames input picture, if defect is present, defective data is saved in locally
Database, sends defective locations data to control system, performs step 5, if there is no defect, then perform step 6；
Step 5：The injection of control system control ink-jet marking mechanism can fading ink defective locations are marked；
Step 6：If detection is not completed also, step 3 is performed, if detection is completed, examining report is printed.
5. the embryo cloth defective vision detection device as described in claim 3 or 4, wherein the embryo cloth quality based on multithreading
Detection algorithm, comprises the following steps：
Step one：Input picture is obtained, and input picture I is obtained from the vision-based detection platforminput, input image size for (m ×
1024)×(n×1024)；
Step 2：Image block, is divided into m by input picture1×n1Individual, size is
Unit_size × unit_size cell pictureWherein 0≤i≤m1,0≤j≤n1,Unit_size=256 or 128；
Step 3：Newly-built size is m1×n1Thread queue Ti,j, to cell pictureBlock textural characteristics are carried out to carry
Take, obtain block texture feature vector
Step 4：It is rightFurther subdivision, is divided into that size is patch_size × patch_size and overlapping region is
Size is over_size fritter
Wherein
Step 5：WithFor dimension texture boot vector, each is calculatedTexture
Distribution, obtains shortage probability distributed image defect_priori,j；
Step 6：According to defect_priori,jJudgeIn whether there is defect, by defect information write into Databasce
Preserved；
Step 7：Discharge thread queuing memory Ti,j。
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201710287368.4A CN106970090A (en) | 2017-04-27 | 2017-04-27 | Embryo cloth defective vision detection device and method |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201710287368.4A CN106970090A (en) | 2017-04-27 | 2017-04-27 | Embryo cloth defective vision detection device and method |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN106970090A true CN106970090A (en) | 2017-07-21 |
Family
ID=59332832
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201710287368.4A Pending CN106970090A (en) | 2017-04-27 | 2017-04-27 | Embryo cloth defective vision detection device and method |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN106970090A (en) |
Cited By (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN107703152A (en) * | 2017-10-27 | 2018-02-16 | 深圳精创视觉科技有限公司 | The automatic indication device of optical film shortcoming |
| CN109145985A (en) * | 2018-08-21 | 2019-01-04 | 佛山职业技术学院 | A kind of detection and classification method of Fabric Defects Inspection |
| CN109283193A (en) * | 2018-10-22 | 2019-01-29 | 上海易清智觉自动化科技有限公司 | Cotton tyre cord flaw on-line checking and identity device |
| CN110702691A (en) * | 2019-10-29 | 2020-01-17 | 无锡精质智能装备有限公司 | Fabric quality detection system |
| CN110793973A (en) * | 2019-11-12 | 2020-02-14 | 广东骉马机器人科技有限公司 | Leather surface defect detecting system |
| CN114397308A (en) * | 2022-03-25 | 2022-04-26 | 江苏贝尔特福新材料有限公司 | Detection equipment for automatically identifying fabric flaws and use method |
Citations (8)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102169093A (en) * | 2010-12-20 | 2011-08-31 | 湖南大学 | Multi-station machine vision imaging detection method and system based on graphics processor |
| CN102323272A (en) * | 2011-08-10 | 2012-01-18 | 合肥望远电子科技有限公司 | Filter paper defect detecting system and detection method thereof based on machine vision technique |
| CN202175829U (en) * | 2010-12-27 | 2012-03-28 | 中国船舶重工集团公司第七一五研究所 | On-line real-time detection system for gray fabric flaw based on machine vision |
| CN202330297U (en) * | 2011-11-28 | 2012-07-11 | 陕西长岭纺织机电科技有限公司 | Device for automatically detecting texture defects |
| CN103344648A (en) * | 2013-07-10 | 2013-10-09 | 鞍钢股份有限公司 | Steel plate surface quality detection method and system based on GPU |
| CN104458766A (en) * | 2014-12-31 | 2015-03-25 | 江南大学 | Cloth surface blemish detection method based on structure texture method |
| CN105044126A (en) * | 2015-07-22 | 2015-11-11 | 瑞安市质量技术监督检测院 | Visual detection system for large-width continuous surface defects |
| CN205317684U (en) * | 2015-12-22 | 2016-06-15 | 无锡市同威软件有限公司 | Flaw detecting system dyes cloth based on image |
-
2017
- 2017-04-27 CN CN201710287368.4A patent/CN106970090A/en active Pending
Patent Citations (8)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102169093A (en) * | 2010-12-20 | 2011-08-31 | 湖南大学 | Multi-station machine vision imaging detection method and system based on graphics processor |
| CN202175829U (en) * | 2010-12-27 | 2012-03-28 | 中国船舶重工集团公司第七一五研究所 | On-line real-time detection system for gray fabric flaw based on machine vision |
| CN102323272A (en) * | 2011-08-10 | 2012-01-18 | 合肥望远电子科技有限公司 | Filter paper defect detecting system and detection method thereof based on machine vision technique |
| CN202330297U (en) * | 2011-11-28 | 2012-07-11 | 陕西长岭纺织机电科技有限公司 | Device for automatically detecting texture defects |
| CN103344648A (en) * | 2013-07-10 | 2013-10-09 | 鞍钢股份有限公司 | Steel plate surface quality detection method and system based on GPU |
| CN104458766A (en) * | 2014-12-31 | 2015-03-25 | 江南大学 | Cloth surface blemish detection method based on structure texture method |
| CN105044126A (en) * | 2015-07-22 | 2015-11-11 | 瑞安市质量技术监督检测院 | Visual detection system for large-width continuous surface defects |
| CN205317684U (en) * | 2015-12-22 | 2016-06-15 | 无锡市同威软件有限公司 | Flaw detecting system dyes cloth based on image |
Cited By (8)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN107703152A (en) * | 2017-10-27 | 2018-02-16 | 深圳精创视觉科技有限公司 | The automatic indication device of optical film shortcoming |
| CN109145985A (en) * | 2018-08-21 | 2019-01-04 | 佛山职业技术学院 | A kind of detection and classification method of Fabric Defects Inspection |
| CN109283193A (en) * | 2018-10-22 | 2019-01-29 | 上海易清智觉自动化科技有限公司 | Cotton tyre cord flaw on-line checking and identity device |
| CN109283193B (en) * | 2018-10-22 | 2024-04-26 | 上海易清智觉自动化科技有限公司 | Tire cord flaw on-line detection and identification device |
| CN110702691A (en) * | 2019-10-29 | 2020-01-17 | 无锡精质智能装备有限公司 | Fabric quality detection system |
| CN110793973A (en) * | 2019-11-12 | 2020-02-14 | 广东骉马机器人科技有限公司 | Leather surface defect detecting system |
| CN114397308A (en) * | 2022-03-25 | 2022-04-26 | 江苏贝尔特福新材料有限公司 | Detection equipment for automatically identifying fabric flaws and use method |
| CN114397308B (en) * | 2022-03-25 | 2022-07-01 | 江苏贝尔特福新材料有限公司 | Detection equipment for automatically identifying fabric flaws and use method |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN106970090A (en) | Embryo cloth defective vision detection device and method | |
| US10942133B2 (en) | Method and system for automatically detecting fabric defect, and computer readable storage medium | |
| CN206945566U (en) | Embryo cloth defective vision detection device | |
| CN108162600A (en) | The method and test pattern of failure print nozzles in detection and compensation ink-jet printer | |
| CN101158650A (en) | On-line detecting method of machine vision system for printed calico flaw | |
| CN110154190A (en) | A kind of household plate production line and detection method with online vision-based detection function | |
| DE102018211922A1 (en) | Automated image sensor calibration | |
| CN102262093A (en) | Machine vision-based on-line detection method for printing machine | |
| CN101445977A (en) | Method and device for the automated identification of bobbin tubes | |
| TR201810709T4 (en) | Device for inspection of printing products. | |
| WO1992008967A1 (en) | Methods and apparatus for fabric inspection | |
| CN109664611B (en) | Printing machine | |
| CN114486903B (en) | Gray-scale self-adaptive coiled material detection system, device and algorithm | |
| CN105301008A (en) | Tipping paper quality test warning system and on-line quality test method | |
| CN107155094A (en) | Using the vision inspections method of multiple video cameras | |
| KR20230137584A (en) | Vision inspection system for defect detection of fabric | |
| EP3699578A1 (en) | System for improved fabric inspection | |
| CN110443803A (en) | A kind of printed matter picture quality detection method and device | |
| CN102529340B (en) | Printed full-sheet ink quantity automatic detection system based on machine vision and printed full-sheet ink quantity detection method | |
| CN117079297A (en) | Relay protection fixed value checking method, system, equipment and medium | |
| CN210604354U (en) | Cloth pattern and character online acquisition device | |
| DE112020006158T5 (en) | Image good/bad learning device, image good/bad determining device and image reading device | |
| CN210775274U (en) | System for automatically detecting and eliminating defects of pipe-making printing | |
| CN209102635U (en) | A kind of cloth inspecting machine with fabric defects instruction function | |
| US20220261975A1 (en) | Inspection method and apparatus |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| RJ01 | Rejection of invention patent application after publication | ||
| RJ01 | Rejection of invention patent application after publication |
Application publication date: 20170721 |