CN107437248B - A kind of method of smart fields detection textile product quality - Google Patents
A kind of method of smart fields detection textile product quality Download PDFInfo
- Publication number
- CN107437248B CN107437248B CN201710658567.1A CN201710658567A CN107437248B CN 107437248 B CN107437248 B CN 107437248B CN 201710658567 A CN201710658567 A CN 201710658567A CN 107437248 B CN107437248 B CN 107437248B
- Authority
- CN
- China
- Prior art keywords
- image
- equipment
- pixel
- filtering
- pattern
- 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.)
- Active
Links
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
- G06T7/0006—Industrial image inspection using a design-rule based approach
-
- 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
Landscapes
- Engineering & Computer Science (AREA)
- Quality & Reliability (AREA)
- Computer Vision & Pattern Recognition (AREA)
- Physics & Mathematics (AREA)
- General Physics & Mathematics (AREA)
- Theoretical Computer Science (AREA)
- Image Analysis (AREA)
- Image Processing (AREA)
Abstract
The present invention relates to a kind of method of smart fields detection textile product quality, this method includes：1) a kind of quilt cover pattern smart fields detection platform is provided；And 2) run the detection platform and detected.Detection platform includes MMC storage cards, quilt cover identification equipment, pattern recognition device and pattern match equipment, the quilt cover identification equipment is used to identify whether pending object is quilt cover, the pattern recognition device is connected with the quilt cover identification equipment, for when pending object is quilt cover, identify the live pattern on quilt cover, the pattern match equipment is connected with the pattern recognition device, for by the live pattern compared with preset reference pattern；Wherein, the MMC storage cards are used to prestore preset reference pattern.
Description
Technical field
The present invention relates to quilt cover field, more particularly to a kind of method of smart fields detection textile product quality.
Background technology
Quilt cover is in guard bed and edge of bed and the cover done, be cleaned also for convenient.The selection of quilt cover should basis
The change in season and change.As spring and summer may be selected pure and fresh, the fresh and alive atmosphere of color creation of jump, winter can select warm tones,
Set off warm visual effect by contrast.It is advisable by subfamily summer with 3 jin or so, spring and autumn 4-5 jin or so, winter 6-8 jin or so, together
When will be depending on personal habits and local climate.
But in the prior art, it is housed in manufacturing process and the situation that pattern is misprinted often occurs, if is generalized to market
On, the credit worthiness of producer will be adversely affected, in the prior art and in the absence of such quilt cover pattern detection mechanism.
The content of the invention
In order to solve the above problems, the invention provides a kind of method of smart fields detection textile product quality, use
Quilt cover identification equipment is used to identify whether pending object is quilt cover, using pattern recognition device and the quilt cover identification equipment
Connection, for when pending object is quilt cover, identifying the live pattern on quilt cover, the pattern match equipment and the figure
Case identification equipment connects, for the live pattern compared with preset reference pattern, to be malfunctioned so as to prepare detection
Version quilt cover.
According to an aspect of the present invention, there is provided a kind of method of smart fields detection textile product quality, this method bag
Include：
1) a kind of quilt cover pattern smart fields detection platform is provided, including MMC storage cards, quilt cover identification equipment, pattern are known
Other equipment and pattern match equipment, the quilt cover identification equipment are used to identify whether pending object is quilt cover, the pattern
Identification equipment is connected with the quilt cover identification equipment, for when pending object is quilt cover, identifying the scene photo on quilt cover
Case, the pattern match equipment are connected with the pattern recognition device, for the live pattern to be entered with preset reference pattern
Row compares；
Wherein, the MMC storage cards are used to prestore preset reference pattern；And
2) detection platform is run to be detected.
More specifically, in the quilt cover pattern smart fields detection platform, in addition to：Point array camera, for treating
The object of processing is shot, to obtain and export real-time target image.
More specifically, in the quilt cover pattern smart fields detection platform, in addition to：Region division equipment, for connecing
Real-time target image is received, real-time target image is divided into multiple fringe regions, includes an edge in each fringe region
Curve, boundary curve are made up of the black level pixel that multiple pixel values are 0.
More specifically, in the quilt cover pattern smart fields detection platform, in addition to：Equipment for area detection equipment, it is and described
Region division equipment connects, for for each black level pixel in real-time target image, determining the marginal zone where it
Domain, it is measured to the distance of boundary curve core-wire as boundary curve distance, boundary curve distance to be more than or equal to default
The black level pixel of curve distance replaces with white level pixel, and boundary curve distance is less than to the black level picture of pre-programmed curve distance
Element is left black level pixel.
More specifically, in the quilt cover pattern smart fields detection platform, in addition to：
Image output device, real-time target image of each black level pixel after processed is handled into image as black level
Output；Strengthen equipment step by step, including target just knows unit, contrast processing unit, histogram equalization unit and image smoothing list
Member, the target are just known unit and are used to receive black level processing image, determined based on goal-selling gray threshold scope described black
Whether each pixel in level processing image belongs to object pixel, and the black level is handled into all target pictures in image
Element composition preliminary aim region, the contrast processing unit is just known unit with the target and is connected, for improving the black appliances
The gray value grade of all pixels in preliminary region improves image, the histogram equalization to obtain contrast in flat processing image
Unit is connected with the contrast processing unit, is improved image for receiving the contrast, is strengthened the contrast raising figure
Highlights region as in, while the dark portion region in the contrast raising image is reduced, it is described to obtain targets improvement image
Image smoothing unit is connected with the histogram equalization unit, for receiving the targets improvement image, to the targets improvement
Image carries out picture smooth treatment strengthens image step by step to obtain；
Double-deck filter apparatus, including the sub- equipment of contour detecting, the sub- equipment of pattern analysis, the sub- equipment of the first filtering and the second filter
Marble equipment；The contour detecting equipment, strengthen image step by step for receiving, and strengthen the target in image described in detection step by step
Profile；The pattern analysis equipment is connected with the contour detecting equipment, for receiving the target strengthened step by step in image
Profile, and medium filtering template and filtering wavelet basis are determined based on the objective contour strengthened step by step in image；Described first
Filter sub- equipment to be connected with the pattern analysis equipment, for each contour pixel to forming the objective contour, be based on
The medium filtering template that the pattern analysis equipment determines is true according to the pixel distribution in the medium filtering window centered on it
Fixed different filtering strategies, it is described based on the medium filtering template that the pattern analysis equipment determines according in centered on it
Pixel distribution in value filtering window determines that different filtering strategies include：When the object pixel quantity in medium filtering window is big
During non-targeted pixel quantity in equal to medium filtering window, the average of pixel value of each object pixel is taken as the wheel
The pixel value of wide pixel, when the object pixel quantity in medium filtering window is less than the non-targeted pixel count in medium filtering window
During amount, pixel value of the average as the contour pixel of the pixel value of each non-targeted pixel is taken, the first filtering is set
Standby each non-contour pixel being additionally operable to being not belonging to the objective contour in the image of enhancing step by step, based on the intermediate value
Filtering Template is used as the non-profile according to using the average of the pixel value of all pixels in the medium filtering window centered on it
The pixel value of pixel, and the sub- equipment of first filtering are additionally operable to export the first filtering image；The sub- equipment of second filtering
Equipment sub- with the pattern analysis and the sub- equipment of first filtering are connected respectively, for receiving first filtering image, base
In the filtering wavelet basis that the pattern analysis equipment determines first filtering image is performed the processing of corresponding wavelet filtering with
Export the second filtering image；
Wherein, the pattern recognition device is connected with the described second sub- equipment of filtering, for receiving the second filtering figure
Picture, and the live pattern in second filtering image is identified based on predetermined pattern characteristics of image.
More specifically, in the quilt cover pattern smart fields detection platform：Boundary curve core-wire is that corresponding edge is bent
The line upper curve curve that each central point is formed in the radial direction.
More specifically, in the quilt cover pattern smart fields detection platform, in addition to：Luminance sensor, it is arranged on a little
The side of array camera, for detecting the real-time luminosity of simultaneously output dot matrix video camera surrounding environment.
More specifically, in the quilt cover pattern smart fields detection platform, in addition to：Flash unit, with the brightness
Sensor connects, and is arranged on the side of an array camera, is determined for receiving the real-time luminosity, and based on the real-time luminosity
Whether start the flash operation of its own and provide floor light with the shooting for described array camera.
Brief description of the drawings
Embodiment of the present invention is described below with reference to accompanying drawing, wherein：
Fig. 1 is the block diagram of the quilt cover pattern smart fields detection platform according to embodiment of the present invention.
Fig. 2 is the enhancing equipment step by step of the quilt cover pattern smart fields detection platform according to embodiment of the present invention
Block diagram.
Reference：1MMC storage cards；2 quilt cover identification equipments；3 pattern recognition devices；4 pattern match equipment；5 increase step by step
Strong equipment；51 targets just know unit；52 contrast processing units；53 histogram equalization units；54 image smoothing units
Embodiment
The embodiment of the quilt cover pattern smart fields detection platform of the present invention is carried out specifically below with reference to accompanying drawings
It is bright.
Double increasing quilt cover size is as follows：Sheet：240*270CM quilt cover 220*240CM pillowcases 74*48CM (internal diameter) (two
Only) bed necessaries of this size are normally only used on 1.8*2 rice or more roomy bed because sheet is bigger.
Currently, lack effective quilt cover pattern detection mechanism, lead to not the quilt cover for recognizing wrong version in time, easily by mistake
Version quilt cover is sold in the market.In order to overcome above-mentioned deficiency, the present invention has built a kind of smart fields detection textile product quality
Method, this method includes：1) a kind of quilt cover pattern smart fields detection platform is provided；And 2) run the detection platform and enter
Row detection.
Fig. 1 is the block diagram of quilt cover pattern smart fields detection platform according to embodiment of the present invention, institute
Stating platform includes MMC storage cards, quilt cover identification equipment, pattern recognition device and pattern match equipment, the quilt cover identification equipment
For identifying whether pending object is quilt cover, the pattern recognition device is connected with the quilt cover identification equipment, for
When pending object is quilt cover, the live pattern on quilt cover, the pattern match equipment and the pattern recognition device are identified
Connection, for by the live pattern compared with preset reference pattern；
Wherein, the MMC storage cards are used to prestore preset reference pattern.
Then, continue to carry out further the concrete structure of the quilt cover pattern smart fields detection platform of the present invention
It is bright.
In the quilt cover pattern smart fields detection platform, in addition to：
Point array camera, for being shot to pending object, to obtain and export real-time target image.
In the quilt cover pattern smart fields detection platform, in addition to：
Region division equipment, for receiving real-time target image, real-time target image is divided into multiple fringe regions, often
Include a boundary curve in one fringe region, boundary curve is made up of the black level pixel that multiple pixel values are 0.
In the quilt cover pattern smart fields detection platform, in addition to：
Equipment for area detection equipment, it is connected with the region division equipment, for black for each in real-time target image
Level pixel, the fringe region where it is determined, measures it to the distance of boundary curve core-wire using as boundary curve distance,
The black level pixel that boundary curve distance is more than or equal to pre-programmed curve distance replaces with white level pixel, by boundary curve distance
Black level pixel less than pre-programmed curve distance is left black level pixel.
In the quilt cover pattern smart fields detection platform, in addition to：
Image output device, real-time target image of each black level pixel after processed is handled into image as black level
Output；
As shown in Fig. 2 strengthen equipment step by step, including target just knows unit, contrast processing unit, histogram equalization unit
With image smoothing unit, the target just knows unit and is used to receive black level processing image, based on goal-selling gray threshold model
Enclose and determine whether each pixel in the black level processing image belongs to object pixel, the black level is handled in image
All object pixels composition preliminary aim region, just knowledge unit is connected the contrast processing unit with the target, is used for
The gray value grade for improving all pixels in preliminary region in the black level processing image improves image, institute to obtain contrast
State histogram equalization unit to be connected with the contrast processing unit, image is improved for receiving the contrast, described in enhancing
Contrast improves the highlights region in image, while reduces the dark portion region in the contrast raising image, to obtain target
Strengthen image, described image smooth unit is connected with the histogram equalization unit, right for receiving the targets improvement image
The targets improvement image carries out picture smooth treatment strengthens image step by step to obtain；
Double-deck filter apparatus, including the sub- equipment of contour detecting, the sub- equipment of pattern analysis, the sub- equipment of the first filtering and the second filter
Marble equipment；The contour detecting equipment, strengthen image step by step for receiving, and strengthen the target in image described in detection step by step
Profile；The pattern analysis equipment is connected with the contour detecting equipment, for receiving the target strengthened step by step in image
Profile, and medium filtering template and filtering wavelet basis are determined based on the objective contour strengthened step by step in image；Described first
Filter sub- equipment to be connected with the pattern analysis equipment, for each contour pixel to forming the objective contour, be based on
The medium filtering template that the pattern analysis equipment determines is true according to the pixel distribution in the medium filtering window centered on it
Fixed different filtering strategies, it is described based on the medium filtering template that the pattern analysis equipment determines according in centered on it
Pixel distribution in value filtering window determines that different filtering strategies include：When the object pixel quantity in medium filtering window is big
During non-targeted pixel quantity in equal to medium filtering window, the average of pixel value of each object pixel is taken as the wheel
The pixel value of wide pixel, when the object pixel quantity in medium filtering window is less than the non-targeted pixel count in medium filtering window
During amount, pixel value of the average as the contour pixel of the pixel value of each non-targeted pixel is taken, the first filtering is set
Standby each non-contour pixel being additionally operable to being not belonging to the objective contour in the image of enhancing step by step, based on the intermediate value
Filtering Template is used as the non-profile according to using the average of the pixel value of all pixels in the medium filtering window centered on it
The pixel value of pixel, and the sub- equipment of first filtering are additionally operable to export the first filtering image；The sub- equipment of second filtering
Equipment sub- with the pattern analysis and the sub- equipment of first filtering are connected respectively, for receiving first filtering image, base
In the filtering wavelet basis that the pattern analysis equipment determines first filtering image is performed the processing of corresponding wavelet filtering with
Export the second filtering image；
Wherein, the pattern recognition device is connected with the described second sub- equipment of filtering, for receiving the second filtering figure
Picture, and the live pattern in second filtering image is identified based on predetermined pattern characteristics of image.
In the quilt cover pattern smart fields detection platform：
Boundary curve core-wire is by the corresponding edge curve upper curve curve that each central point forms in the radial direction.
In the quilt cover pattern smart fields detection platform, in addition to：
Luminance sensor, the side of an array camera is arranged on, for detecting and output dot matrix video camera surrounding environment
Real-time luminosity.
In the quilt cover pattern smart fields detection platform, in addition to：
Flash unit, it is connected with the luminance sensor, is arranged on the side of an array camera, it is described real-time for receiving
Brightness, and determine whether that the flash operation for starting its own thinks that the shooting of described array camera carries based on the real-time luminosity
For floor light.
It can also divide in addition, target just knows unit, contrast processing unit, histogram equalization unit and image smoothing unit
Do not realized using different CPLD chips.
In addition, small echo (Wavelet) this term, as its name suggests, " small echo " is exactly small waveform.So-called " small " refers to him
With Decay Rate；And be referred to as " ripple " and then refer to its fluctuation, the concussion form of its amplitude alternate positive and negative.Become with Fourier
Commutation ratio, wavelet transformation are the localization analyses of time (space) frequency, he by flexible shift operations to signal (function) by
Step carries out multi-scale refinement, is finally reached high frequency treatment time subdivision, and frequency is segmented at low frequency, can adapt to time frequency signal analysis automatically
Requirement, so as to focus on any details of signal, solve Fourier conversion difficult problem, turn into after Fourier become
Important breakthrough since changing in scientific method.Someone calls wavelet transformation " school microscop ".
The application of wavelet analysis is that the theoretical research with wavelet analysis is bound tightly together ground.He believes in science and technology
Breath industrial field achieves the achievement to attract people's attention.Electronic information technology is a field important in six big new and high technologies, he
Importance be image and signal transacting.Now, signal transacting has become the pith of contemporary science and technology work, letter
Number processing purpose be exactly：Accurately analysis, diagnosis, coding compression and quantify, it is quick transmit or storage, accurately reconstruct (or
Recover).From the point of view of mathematically angle, signal can uniformly regard that (image can be regarded as two to signal transacting as with image procossing
Dimensional signal), in many applications of many analyses, signal processing problems can be attributed in wavelet analysis.For its property
It is to stablize constant signal with the time, the ideal tools of processing are still Fourier analysis.But in actual applications exhausted big
Majority signal is non-stable, and the instrument especially suitable for unstable signal is exactly wavelet analysis.
Using the quilt cover pattern smart fields detection platform of the present invention, it is stranded for quilt cover pattern Site Detection in the prior art
Difficult technical problem, first, completes the Site Detection to quilt cover target, secondly, is set by introducing various effective IMAQs
Standby and image processing equipment carries out the comparison of live pattern and preset reference pattern to pending quilt cover, so as to accurate true
Recognize wrong version quilt cover.
It is understood that although the present invention is disclosed as above with preferred embodiment, but above-described embodiment and it is not used to
Limit the present invention.For any those skilled in the art, without departing from the scope of the technical proposal of the invention,
Many possible changes and modifications are all made to technical solution of the present invention using the technology contents of the disclosure above, or are revised as
With the equivalent embodiment of change.Therefore, every content without departing from technical solution of the present invention, the technical spirit pair according to the present invention
Any simple modifications, equivalents, and modifications made for any of the above embodiments, still fall within the scope of technical solution of the present invention protection
It is interior.
Claims (1)
1. a kind of method of smart fields detection textile product quality, this method include：
1) a kind of quilt cover pattern smart fields detection platform is provided；And
2) detection platform is run to be detected；
The quilt cover pattern smart fields detection platform includes：
MMC storage cards, quilt cover identification equipment, pattern recognition device and pattern match equipment, the quilt cover identification equipment are used to know
Whether not pending object is quilt cover, and the pattern recognition device is connected with the quilt cover identification equipment, for pending
Object when being quilt cover, identify the live pattern on quilt cover, the pattern match equipment is connected with the pattern recognition device, use
In by the live pattern compared with preset reference pattern；
Wherein, the MMC storage cards are used to prestore preset reference pattern；
Point array camera, for being shot to pending object, to obtain and export real-time target image；
Region division equipment, for receiving real-time target image, real-time target image is divided into multiple fringe regions, each
Include a boundary curve in fringe region, boundary curve is made up of the black level pixel that multiple pixel values are 0；
Equipment for area detection equipment, it is connected with the region division equipment, for for each black level in real-time target image
Pixel, the fringe region where it is determined, it is measured to the distance of boundary curve core-wire using as boundary curve distance, by side
The black level pixel that edge curve distance is more than or equal to pre-programmed curve distance replaces with white level pixel, and boundary curve distance is less than
The black level pixel of pre-programmed curve distance is left black level pixel；
Characterized in that, the detection platform also includes：
Image output device, it is defeated to handle image using real-time target image of each black level pixel after processed as black level
Go out；
Strengthen equipment step by step, including target just knows unit, contrast processing unit, histogram equalization unit and image smoothing list
Member, the target are just known unit and are used to receive black level processing image, determined based on goal-selling gray threshold scope described black
Whether each pixel in level processing image belongs to object pixel, and the black level is handled into all target pictures in image
Element composition preliminary aim region, the contrast processing unit is just known unit with the target and is connected, for improving the black appliances
The gray value grade of all pixels in preliminary region improves image, the histogram equalization to obtain contrast in flat processing image
Unit is connected with the contrast processing unit, is improved image for receiving the contrast, is strengthened the contrast raising figure
Highlights region as in, while the dark portion region in the contrast raising image is reduced, it is described to obtain targets improvement image
Image smoothing unit is connected with the histogram equalization unit, for receiving the targets improvement image, to the targets improvement
Image carries out picture smooth treatment strengthens image step by step to obtain；
Double-deck filter apparatus, including the sub- equipment of contour detecting, the sub- equipment of pattern analysis, the sub- equipment of the first filtering and the second filtering
Equipment；The contour detecting equipment, strengthen image step by step for receiving, and strengthen the target wheel in image described in detection step by step
It is wide；The pattern analysis equipment is connected with the contour detecting equipment, for receiving the target wheel strengthened step by step in image
Exterior feature, and medium filtering template and filtering wavelet basis are determined based on the objective contour strengthened step by step in image；First filter
Marble equipment is connected with the pattern analysis equipment, for each contour pixel to forming the objective contour, based on institute
The medium filtering template for stating the determination of pattern analysis equipment determines according to the pixel distribution in the medium filtering window centered on it
Different filtering strategies, the medium filtering template determined based on the pattern analysis equipment is according to the intermediate value centered on it
Pixel distribution in filter window determines that different filtering strategies include：When the object pixel quantity in medium filtering window is more than
During equal to non-targeted pixel quantity in medium filtering window, the average of pixel value of each object pixel is taken as the profile
The pixel value of pixel, when the object pixel quantity in medium filtering window is less than the non-targeted pixel quantity in medium filtering window
When, take pixel value of the average as the contour pixel of the pixel value of each non-targeted pixel, the sub- equipment of first filtering
Each non-contour pixel to being not belonging to the objective contour in the image of enhancing step by step is additionally operable to, is filtered based on the intermediate value
Ripple template is used as the non-wire-frame image according to using the average of the pixel value of all pixels in the medium filtering window centered on it
The pixel value of element, and the sub- equipment of first filtering are additionally operable to export the first filtering image；The sub- equipment point of second filtering
Equipment not sub- with the pattern analysis and the sub- equipment of first filtering are connected, and for receiving first filtering image, are based on
The filtering wavelet basis that the pattern analysis equipment determines performs corresponding wavelet filtering to first filtering image and handled with defeated
Go out the second filtering image；
Wherein, the pattern recognition device is connected with the described second sub- equipment of filtering, for receiving second filtering image, and
Live pattern in second filtering image is identified based on predetermined pattern characteristics of image.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201710658567.1A CN107437248B (en) | 2017-08-04 | 2017-08-04 | A kind of method of smart fields detection textile product quality |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201710658567.1A CN107437248B (en) | 2017-08-04 | 2017-08-04 | A kind of method of smart fields detection textile product quality |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN107437248A CN107437248A (en) | 2017-12-05 |
| CN107437248B true CN107437248B (en) | 2018-04-10 |
Family
ID=60459870
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201710658567.1A Active CN107437248B (en) | 2017-08-04 | 2017-08-04 | A kind of method of smart fields detection textile product quality |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN107437248B (en) |
Families Citing this family (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN110522349B (en) * | 2018-05-27 | 2021-11-05 | 扬州市旅游日用品制造总厂 | Fixed desktop maintenance method based on gray level measurement |
Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN103018254A (en) * | 2012-12-04 | 2013-04-03 | 东南大学 | Automatic detection device based on image identification technology |
| CN103604809A (en) * | 2013-10-22 | 2014-02-26 | 江南大学 | Pattern cloth flaw online visual inspection method |
| CN104568952A (en) * | 2015-01-15 | 2015-04-29 | 无锡北斗星通信息科技有限公司 | Intelligent fabric weave pattern detection system |
| CN104616003A (en) * | 2015-03-06 | 2015-05-13 | 侯苏 | System for identifying type of foreign matters on power line |
| CN106650721A (en) * | 2016-12-28 | 2017-05-10 | 吴晓军 | Industrial character identification method based on convolution neural network |
-
2017
- 2017-08-04 CN CN201710658567.1A patent/CN107437248B/en active Active
Patent Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN103018254A (en) * | 2012-12-04 | 2013-04-03 | 东南大学 | Automatic detection device based on image identification technology |
| CN103604809A (en) * | 2013-10-22 | 2014-02-26 | 江南大学 | Pattern cloth flaw online visual inspection method |
| CN104568952A (en) * | 2015-01-15 | 2015-04-29 | 无锡北斗星通信息科技有限公司 | Intelligent fabric weave pattern detection system |
| CN104616003A (en) * | 2015-03-06 | 2015-05-13 | 侯苏 | System for identifying type of foreign matters on power line |
| CN106650721A (en) * | 2016-12-28 | 2017-05-10 | 吴晓军 | Industrial character identification method based on convolution neural network |
Non-Patent Citations (1)
| Title |
|---|
| 蜡染跟踪印花图像处理算法的研究;唐雪莲;《中国优秀硕士学位论文全文数据库 信息科技辑》;20131215;第2013年卷(第S2期);第8页、第12页、第25页、第29-30页、第35页 * |
Also Published As
| Publication number | Publication date |
|---|---|
| CN107437248A (en) | 2017-12-05 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN110008968B (en) | Automatic triggering method for robot settlement based on image vision | |
| CN104867159B (en) | A kind of digital camera sensor dust detection and stage division and device | |
| CN106446952B (en) | A kind of musical score image recognition methods and device | |
| CN109409355B (en) | Novel transformer nameplate identification method and device | |
| CN107767359A (en) | Textile product smart fields detection platform | |
| CN104021207A (en) | Food information providing method based on image | |
| CN108108767A (en) | A kind of cereal recognition methods, device and computer storage media | |
| CN111611907B (en) | Image-enhanced infrared target detection method | |
| CN110728201B (en) | Image processing method and device for fingerprint identification | |
| WO2020038312A1 (en) | Multi-channel tongue body edge detection device and method, and storage medium | |
| CN104484650B (en) | The method and apparatus of sketch recognition of face | |
| CN109558908A (en) | A kind of determination method of given area optimal edge | |
| CN111242888A (en) | Image processing method and system based on machine vision | |
| CN110223344A (en) | A kind of infrared small target detection method based on morphology and vision noticing mechanism | |
| CN1042981C (en) | Reader for symbolic information | |
| CN107437248B (en) | A kind of method of smart fields detection textile product quality | |
| CN107491714B (en) | Intelligent robot and target object identification method and device thereof | |
| CN113436162A (en) | Method and device for identifying weld defects on surface of hydraulic oil pipeline of underwater robot | |
| CN117197064A (en) | Automatic non-contact eye red degree analysis method | |
| CN112651962A (en) | AI intelligent diagnosis system platform | |
| CN111353324A (en) | Method for reading two-dimensional code of dot matrix in glass | |
| CN104778432A (en) | Image recognition method | |
| CN112070771B (en) | Adaptive threshold segmentation method and device based on HS channel and storage medium | |
| CN106797420A (en) | Treatment represents the data of image | |
| CN114022856A (en) | Unstructured road travelable area identification method, electronic device and medium |
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 | ||
| CB03 | Change of inventor or designer information |
Inventor after: Hu Xia Inventor before: Chen Si |
|
| CB03 | Change of inventor or designer information | ||
| TA01 | Transfer of patent application right |
Effective date of registration: 20180309 Address after: 233500 West Zhuang, Li Qian building, Chengguan Town, Mengcheng County, Anhui Province, No. 70 Applicant after: Hu Xia Address before: No. 189, Zhu Zhen Road, Dong Zhu Town, Suzhou hi tech Zone, Jiangsu Province Applicant before: Chen Si |
|
| TA01 | Transfer of patent application right | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant |