WO2019132792A1 - A method for detecting weft and warp regions in woven fabrics - Google Patents
A method for detecting weft and warp regions in woven fabrics Download PDFInfo
- Publication number
- WO2019132792A1 WO2019132792A1 PCT/TR2017/050729 TR2017050729W WO2019132792A1 WO 2019132792 A1 WO2019132792 A1 WO 2019132792A1 TR 2017050729 W TR2017050729 W TR 2017050729W WO 2019132792 A1 WO2019132792 A1 WO 2019132792A1
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- WIPO (PCT)
- Prior art keywords
- analysis window
- weaving
- regions
- binary
- warp
- Prior art date
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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
- G01N21/89—Investigating the presence of flaws or contamination in moving material, e.g. running paper or textiles
- G01N21/892—Investigating the presence of flaws or contamination in moving material, e.g. running paper or textiles characterised by the flaw, defect or object feature examined
- G01N21/898—Irregularities in textured or patterned surfaces, e.g. textiles, wood
- G01N21/8983—Irregularities in textured or patterned surfaces, e.g. textiles, wood for testing textile webs, i.e. woven material
-
- D—TEXTILES; PAPER
- D06—TREATMENT OF TEXTILES OR THE LIKE; LAUNDERING; FLEXIBLE MATERIALS NOT OTHERWISE PROVIDED FOR
- D06H—MARKING, INSPECTING, SEAMING OR SEVERING TEXTILE MATERIALS
- D06H3/00—Inspecting textile materials
- D06H3/08—Inspecting textile materials by photo-electric or television means
-
- 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
- G01N21/8851—Scan or image signal processing specially adapted therefor, e.g. for scan signal adjustment, for detecting different kinds of defects, for compensating for structures, markings, edges
-
- 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
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T7/00—Image analysis
- G06T7/40—Analysis of texture
- G06T7/41—Analysis of texture based on statistical description of texture
- G06T7/42—Analysis of texture based on statistical description of texture using transform domain methods
-
- 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
- G01N21/8851—Scan or image signal processing specially adapted therefor, e.g. for scan signal adjustment, for detecting different kinds of defects, for compensating for structures, markings, edges
- G01N2021/8887—Scan or image signal processing specially adapted therefor, e.g. for scan signal adjustment, for detecting different kinds of defects, for compensating for structures, markings, edges based on image processing techniques
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N33/00—Investigating or analysing materials by specific methods not covered by groups G01N1/00 - G01N31/00
- G01N33/36—Textiles
- G01N33/367—Fabric or woven textiles
-
- 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
- G06T2207/20021—Dividing image into blocks, subimages or windows
-
- 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
- G06T2207/20048—Transform domain processing
- G06T2207/20056—Discrete and fast Fourier transform, [DFT, FFT]
-
- 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
Definitions
- the present invention relates to a method suitable for detecting weft and warp regions in woven fabrics.
- the analysis of woven fabric provides important data for research and development activities in fabric and weaving field in textile sector. Furthermore, it is desired to be benefited from fabric analyses for fabric quality controls. Weaving analysis and color report are among important data in fabric analyses.
- the weaving density in weaving analyses of the previous art can be detected by using various image processing methods. In the methods of the previous art, the intersection regions of the weft yam and warp yarn forming weaving regions are determined. By means of determining weaving regions, the weaving density can be calculated and weaving yam can be counted.
- Publication no CN103364397A discloses an apparatus and a method for measuring weaving density in a fabric.
- the objective of the present invention is to provide a method suitable for detecting weft and warp regions in woven fabrics.
- Figure 1- The view of an exemplary weft yarn, exemplary warp yam, exemplary weaving region, exemplary weft region, exemplary warp region in an exemplary woven fabric
- Figure 2 The view of four corner points selected in the digital view shown schematically for determining an analysis window that will determine the limits of weaving region in an exemplary embodiment of the invention.
- Figure 3- The view of selection of analysis window formed by the corners of four comer points selected in an exemplary embodiment of the invention.
- Figure 4- The view of analysis window in frequency definition domain in an exemplary embodiment of the invention.
- Figure 5- The view of double analyses window in black- white in an exemplary embodiment of the invention.
- Figure 6- The view of weaving yams in one direction provided in double analysis window in an exemplary embodiment of the invention.
- Figure 7 The view of weaving yams in another direction provided in double analysis window in an exemplary embodiment of the invention.
- Figure 8 The view of orientations of each weaving regions depending on double analysis window in an exemplary embodiment of the invention.
- Figure 9 The view of an ellipse having a second moment same as a weaving region in double analysis window and major axis of the ellipse in an exemplary embodiment of the invention.
- Figure 10- The view of an ellipse having second moment same as a weaving region, major axis of ellipse, and angle between major axis of the ellipse and the x axis (the x axis of which is in a Cartesian coordinate system parallel to the horizontal lower edge of the double analysis window) in an exemplary embodiment of the invention.
- Figure 11- The view of weft regions double analysis window in an exemplary embodiment of the invention.
- Figure 12- The view of warp regions double analysis window in an exemplary embodiment of the invention.
- Figure 13- The view of analysis window comprising markers showing weft regions placed in central points of weft regions and markers showing warp regions placed in central points of warp regions in an exemplary embodiment of the invention.
- a digital image (101) of a woven fabric piece is taken.
- the digital image (101) is high resolution.
- Scanners, especially flatbed scanners with line sensor, microscopes that can form digital output, cameras can be shown as examples for devices suitable for taking digital image (101) without limiting the scope of the invention.
- An analysis window (103) determining the limits of the weaving region (105) within the digital image (101).
- analysis window (103) preferably four comer points (102) that will determine the limits of weaving regions (105) (weft region or warp region) are selected in the digital image (101).
- a quadrangle analysis window (103) is formed by the comers of the selected four corner points (102). If the quadrangle the corners of which are formed by the selected four corner points (102) is not a rectangle, the quadrangle is transformed into a rectangle (analysis window (103)) by using a projective transformation method.
- a frequency domain filtering is applied on the analysis window (103), and the analysis window (103) is transformed into a binary (for example black-white) analysis window (104) comprising only weaving regions.
- a binary analysis window (104) comprising only weaving regions.
- FT Fourier Transformation
- FFT Fast Fourier Transform
- the analysis window (103) in the frequency definition domain is filtered with a selected threshold frequency value, and a binary analysis window (104) is obtained wherein the images outside the weaving regions (105) are eliminated.
- the filtered analysis window (103) in the frequency definition domain is transformed into spatial definition domain.
- FT Inverse Fourier Transformation
- IFFT Inverse Fast Fourier Transform
- weaving density can be calculated and weaving yam can be counted from the binary analysis window (104).
- the multiplication of weaving region (105) number extending along the two vertical edges of the binary analysis window (104) gives the number of weaving region (105) comprised by the analysis window (103).
- the weaving density is calculated by dividing the number of weaving region (105) to the area of analysis window (103).
- the sum of weaving region (105) number extending along the two vertical edges of the binary analysis window (104) gives the number of weaving region (106) (the total of weft yarn and warp yam) passing through the analysis window (103). It is then determined whether the weaving regions (105) in the binary analysis window (104) are a weft region (110) or a warp region (111).
- the orientations of each weaving region (105) in the binary analysis window (104) relative to the binary analysis window (104) are determined. In order to determine the orientation of each weaving region (105) relative to the binary analysis window
- each weaving region (105) preferably the perimeter coordinates of each weaving region (105) (relative to the binary analysis window (104)) are determined by a binary region analysis or an edge detection edge detection method.
- the weaving regions (105) (extending along) having the orientation in a selected weft incline range in the binary analysis window (104) are assumed (determined) as weft regions (110).
- the weaving regions (105) (extending along) having the orientation in a selected warp incline range in the binary analysis window (104) are assumed (determined) as warp regions (111).
- a Cartesian coordinate system parallel to the horizontal lower edge of the x-axis binary analysis window (104) is considered.
- the orientation of a weaving region (105) is the angle between the major axis (109) of the ellipse (108) having the same second moment as the weaving region
- the selected weft incline range is 30° - 40°. In one embodiment of the invention, preferably the selected warp incline range is 70° - 80°.
- each weaving region (105) preferably central coordinates of each weaving region (105) are determined.
- preferably central points of each weaving region (105) are superimposed on the analysis window (103) (not binary).
- a marker (112) indicative of the weft region is located at the center points of the detected weft regions (110) to be displayed in the analysis window (103).
- a marker (113) indicative of the warp region is located at the center points of the detected warp regions (111) to be displayed in the analysis window (103).
Abstract
The present invention relates to a method for detecting weft and warp regions in woven fabrics comprising the steps of taking a digital image (101)of a woven fabric piece; selecting an analysis window (103) from the digital image (101); transforming the analysis window (103) to a binary analysis window (104) comprising only weaving regions (105) by applying filtering in a frequency definition domain to the analysis window (103); determining the orientations of each weaving region (105) in the binary analysis window (104) relative to the binary analysis window (104); detecting the weaving regions (105) having the orientation in a selected weft incline range in the binary analysis window (104) as weft regions (110); detecting the weaving regions (105) having the orientation in a selected warp incline range in the binary analysis window (104) as warp regions (111).
Description
A METHOD FOR DETECTING WEFT AND WARP REGIONS IN
WOVEN FABRICS
Field of the Invention
The present invention relates to a method suitable for detecting weft and warp regions in woven fabrics.
Background of the Art
The analysis of woven fabric provides important data for research and development activities in fabric and weaving field in textile sector. Furthermore, it is desired to be benefited from fabric analyses for fabric quality controls. Weaving analysis and color report are among important data in fabric analyses. The weaving density in weaving analyses of the previous art can be detected by using various image processing methods. In the methods of the previous art, the intersection regions of the weft yam and warp yarn forming weaving regions are determined. By means of determining weaving regions, the weaving density can be calculated and weaving yam can be counted.
Publication no CN103364397A discloses an apparatus and a method for measuring weaving density in a fabric.
In the previous technique, it is not possible to determine which of the weaving regions (intersecting regions of the weft yam and the warp yarn) located in the woven fabric is the warp region (weft yam on top) or the warp region (warp yarn on top). Therefore, even though weaving density and weaving yarn count are included in the fabric analysis; since weft regions and warp regions are not detected, said fabric analyses are insufficient in detecting fabric production.
Weft regions and warp regions in woven fabrics are detected in the method of the present invention. Therefore, the errors that can occur in production (for example a weft region and warp region breaking or being damaged) can be detected.
Summary of the Invention
The objective of the present invention is to provide a method suitable for detecting weft and warp regions in woven fabrics.
Detailed Description of the Invention
An exemplary embodiment of the method for detecting weft and warp regions in woven fabrics developed to fulfill the objective of the present invention is illustrated in the accompanying figures in order to better understand the invention. The details of the invention should be evaluated considering the whole specification, in these drawings
Figure 1- The view of an exemplary weft yarn, exemplary warp yam, exemplary weaving region, exemplary weft region, exemplary warp region in an exemplary woven fabric
Figure 2 - The view of four corner points selected in the digital view shown schematically for determining an analysis window that will determine the limits of weaving region in an exemplary embodiment of the invention.
Figure 3- The view of selection of analysis window formed by the corners of four comer points selected in an exemplary embodiment of the invention.
Figure 4- The view of analysis window in frequency definition domain in an exemplary embodiment of the invention.
Figure 5- The view of double analyses window in black- white in an exemplary embodiment of the invention.
Figure 6- The view of weaving yams in one direction provided in double analysis window in an exemplary embodiment of the invention.
Figure 7- The view of weaving yams in another direction provided in double analysis window in an exemplary embodiment of the invention. Figure 8- The view of orientations of each weaving regions depending on double analysis window in an exemplary embodiment of the invention. Figure 9- The view of an ellipse having a second moment same as a weaving region in double analysis window and major axis of the ellipse in an exemplary embodiment of the invention.
Figure 10- The view of an ellipse having second moment same as a weaving region, major axis of ellipse, and angle between major axis of the ellipse and the x axis (the x axis of which is in a Cartesian coordinate system parallel to the horizontal lower edge of the double analysis window) in an exemplary embodiment of the invention.
Figure 11- The view of weft regions double analysis window in an exemplary embodiment of the invention.
Figure 12- The view of warp regions double analysis window in an exemplary embodiment of the invention.
Figure 13- The view of analysis window comprising markers showing weft regions placed in central points of weft regions and markers showing warp regions placed in central points of warp regions in an exemplary embodiment of the invention.
The components shown in the figures are each given reference numbers as follows:
S_l. Exemplary woven fabric
S_2. Exemplary warp yarn
S_3. Exemplary weft yarn
S_4. Exemplary weaving region
S_5. Exemplary warp region
S_6. Exemplary weft region
101. Digital image
102. Comer point
103. Analysis window
104. Double analysis window
105. Weaving region
106. Weaving yarn
107. The line showing the orientation of weaving region according to analysis window
108. Ellipse having second moment same as the weaving region
109. Ellipse major axis
110. Weft region
111. Warp region
112. Marker showing the weft region
113. Marker showing the warp region
Q. The angle between the major axis of the ellipse having the second moment same as the weaving region and the x axis
In the method of the present invention, a digital image (101) of a woven fabric piece is taken. Preferably the digital image (101) is high resolution. Scanners, especially flatbed scanners with line sensor, microscopes that can form digital output, cameras can be shown as examples for devices suitable for taking digital image (101) without limiting the scope of the invention.
An analysis window (103) determining the limits of the weaving region (105) within the digital image (101). For the selection of analysis window (103), preferably four comer points (102) that will determine the limits of weaving regions (105) (weft region or warp region) are selected in the digital image (101). A quadrangle analysis window (103) is formed by the comers of the selected four
corner points (102). If the quadrangle the corners of which are formed by the selected four corner points (102) is not a rectangle, the quadrangle is transformed into a rectangle (analysis window (103)) by using a projective transformation method.
A frequency domain filtering is applied on the analysis window (103), and the analysis window (103) is transformed into a binary (for example black-white) analysis window (104) comprising only weaving regions. For the transformation of analysis window (103) from spatial definition domain to frequency definition domain, preferably Fourier Transformation (FT), especially Fast Fourier Transform (FFT) is used. The analysis window (103) in the frequency definition domain is filtered with a selected threshold frequency value, and a binary analysis window (104) is obtained wherein the images outside the weaving regions (105) are eliminated. Then, the filtered analysis window (103) in the frequency definition domain is transformed into spatial definition domain. For the transformation of analysis window (103) from frequency definition domain to spatial definition domain, preferably Inverse Fourier Transformation (FT), especially Inverse Fast Fourier Transform (IFFT) is used. As a result, a binary analysis window (104) is obtained wherein the images outside the weaving regions (105) are eliminated.
Preferably weaving density can be calculated and weaving yam can be counted from the binary analysis window (104). The multiplication of weaving region (105) number extending along the two vertical edges of the binary analysis window (104) gives the number of weaving region (105) comprised by the analysis window (103). The weaving density is calculated by dividing the number of weaving region (105) to the area of analysis window (103). The sum of weaving region (105) number extending along the two vertical edges of the binary analysis window (104) gives the number of weaving region (106) (the total of weft yarn and warp yam) passing through the analysis window (103).
It is then determined whether the weaving regions (105) in the binary analysis window (104) are a weft region (110) or a warp region (111). The orientations of each weaving region (105) in the binary analysis window (104) relative to the binary analysis window (104) are determined. In order to determine the orientation of each weaving region (105) relative to the binary analysis window
(104), preferably the perimeter coordinates of each weaving region (105) (relative to the binary analysis window (104)) are determined by a binary region analysis or an edge detection edge detection method.
The weaving regions (105) (extending along) having the orientation in a selected weft incline range in the binary analysis window (104) are assumed (determined) as weft regions (110). The weaving regions (105) (extending along) having the orientation in a selected warp incline range in the binary analysis window (104) are assumed (determined) as warp regions (111).
In one embodiment of the invention, a Cartesian coordinate system parallel to the horizontal lower edge of the x-axis binary analysis window (104) is considered. The orientation of a weaving region (105) is the angle between the major axis (109) of the ellipse (108) having the same second moment as the weaving region
(105) and the x axis ( Q ). In one embodiment of the invention, preferably the selected weft incline range is 30° - 40°. In one embodiment of the invention, preferably the selected warp incline range is 70° - 80°.
In one embodiment of the invention, preferably central coordinates of each weaving region (105) are determined. In this embodiment of the invention, preferably central points of each weaving region (105) are superimposed on the analysis window (103) (not binary). A marker (112) indicative of the weft region is located at the center points of the detected weft regions (110) to be displayed in the analysis window (103). A marker (113) indicative of the warp region is located at the center points of the detected warp regions (111) to be displayed in the analysis window (103). Thus, each weft region (110) and warp region (111)
which are comprised by the woven fabric in the image located in the analysis window (104) is shown to the user.
Claims
1. A method for detecting weft and warp regions in woven fabrics comprising the steps of taking a digital image (lOl)of a woven fabric piece;
selecting an analysis window (103) from the digital image (101);
transforming the analysis window (103) to a binary analysis window (104) comprising only weaving regions (105) by applying filtering in a frequency definition domain to the analysis window (103);
determining the orientations of each weaving region (105) in the binary analysis window (104) relative to the binary analysis window (104);
detecting the weaving regions (105) having the orientation in a selected weft incline range in the binary analysis window (104) as weft regions (110);
detecting the weaving regions (105) having the orientation in a selected warp incline range in the binary analysis window (104) as warp regions (111)
2. A method according to claim 1, comprising the step of selecting an analysis window (103) from the digital image (101) which comprises the sub steps of selecting four corner points (102) in the digital image (101);
selecting a quadrangle as analysis window (103) the corners of which are formed by the selected four corner points (102)
3. A method according to claim 2, comprising the step of transforming the quadrangle into a rectangle by using a projective transformation method if the quadrangle the corners of which are formed by the selected four comer points (102) is not a rectangle.
4. A method according to any one of the preceding claims, comprising the step of transforming the analysis window (103) to a binary analysis window (104) comprising only weaving regions (105) by applying filtering in a frequency definition domain to the analysis window (103) which comprises the sub steps
of transforming the analysis window (103) from spatial definition domain to frequency definition domain by means of a Fast Fourier Transformation (FFT);
obtaining a binary analysis window (104) wherein the images outside the weaving regions (105) are eliminated by filtering the analysis window (103) in the frequency definition domain with a selected threshold frequency value; transforming the filtered analysis window (103) in the frequency definition domain to spatial definition domain by means of an Inverse Fast Fourier Transformation (IFFT).
5. A method according to any one of the preceding claims comprising the step of determining the orientations of each weaving region (105) in the binary analysis window (104) relative to the binary analysis window (104) which comprises the sub step of determining perimeter coordinates of each weaving region (105) relative to analysis window (104) with a binary regional analysis or an edge detection method.
6. A method according to any one of the claims 1 to 5 comprising the step of determining orientations of each weaving region (105) in the binary analysis window (104) relative to the binary analysis window which comprises the sub step of determining the angle (Q) between the major axis (109) of an ellipse (108) having the same second moment as a weaving region (105) and the x axis in a Cartesian coordinate system the x axis of which is parallel to the horizontal lower edge of a binary analysis window (104).
7. A method according to any one of the preceding claims which comprises 30° to 40° of weft inline range.
8. A method according to any one of the preceding claims which comprises 70° to 80° of warp inline range.
9. A method according to any one of the preceding claims comprising the steps of determining the central coordinates of each weaving region (105), placing a marker (112) indicative of the weft region at the center points of the detected weft regions (110) to be displayed in the analysis window (103); placing a marker (113) indicative of the warp region at the center points of the detected warp regions (111) to be displayed in the analysis window (103).
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| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| PCT/TR2017/050729 WO2019132792A1 (en) | 2017-12-29 | 2017-12-29 | A method for detecting weft and warp regions in woven fabrics |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| PCT/TR2017/050729 WO2019132792A1 (en) | 2017-12-29 | 2017-12-29 | A method for detecting weft and warp regions in woven fabrics |
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| WO2019132792A1 true WO2019132792A1 (en) | 2019-07-04 |
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Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN110390675A (en) * | 2019-07-26 | 2019-10-29 | 常州弘仁智能科技有限公司 | A kind of fabric weft inclination detection method based on image analysing computer |
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| CN102288607A (en) * | 2011-06-20 | 2011-12-21 | 江南大学 | Woven fabric count detector based on digital microscope |
| CN103163139A (en) * | 2011-12-14 | 2013-06-19 | 江南大学 | Testing method for yarn uniformity in a woven fabric based on wavelet transform |
| CN103163138A (en) * | 2011-12-14 | 2013-06-19 | 江南大学 | Testing method for yarn uniformity in a woven fabric based on fast Fourier Transform |
| CN103364397B (en) * | 2012-03-31 | 2015-10-28 | 佛山市南海天富科技有限公司 | A kind of fabric weft density measurement method and device |
-
2017
- 2017-12-29 WO PCT/TR2017/050729 patent/WO2019132792A1/en active Application Filing
Patent Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102288607A (en) * | 2011-06-20 | 2011-12-21 | 江南大学 | Woven fabric count detector based on digital microscope |
| CN103163139A (en) * | 2011-12-14 | 2013-06-19 | 江南大学 | Testing method for yarn uniformity in a woven fabric based on wavelet transform |
| CN103163138A (en) * | 2011-12-14 | 2013-06-19 | 江南大学 | Testing method for yarn uniformity in a woven fabric based on fast Fourier Transform |
| CN103364397B (en) * | 2012-03-31 | 2015-10-28 | 佛山市南海天富科技有限公司 | A kind of fabric weft density measurement method and device |
Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN110390675A (en) * | 2019-07-26 | 2019-10-29 | 常州弘仁智能科技有限公司 | A kind of fabric weft inclination detection method based on image analysing computer |
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