CN107843566A - A kind of textile component detection means and method - Google Patents
A kind of textile component detection means and method Download PDFInfo
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- CN107843566A CN107843566A CN201710951431.XA CN201710951431A CN107843566A CN 107843566 A CN107843566 A CN 107843566A CN 201710951431 A CN201710951431 A CN 201710951431A CN 107843566 A CN107843566 A CN 107843566A
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- 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
- G01N21/17—Systems in which incident light is modified in accordance with the properties of the material investigated
- G01N21/25—Colour; Spectral properties, i.e. comparison of effect of material on the light at two or more different wavelengths or wavelength bands
- G01N21/31—Investigating relative effect of material at wavelengths characteristic of specific elements or molecules, e.g. atomic absorption spectrometry
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Abstract
A kind of textile component detection means, detection means include gripper frame, standard white plate, 2 pieces of reflective mirrors, band light source, imaging mirror, optical spectrum imagers and computer.Gripper frame is used to stretch, fixes textile to be detected, the standard white plate rectangular with gripper frame plane is provided with gripper frame side, standard white plate provides standard correction thing for radiant correction.2 pieces of reflective mirrors are then provided with the opposite side of gripper frame, 2 pieces of reflective mirrors are located at the positive and negative of gripper frame respectively, and minute surface and the gripper frame interplanar of 2 pieces of reflective mirrors form acute angle, and 2 angle angles are identical.The unlimited lateral edges of 2 pieces of reflective mirrors are provided with band light source, and shooting image provides stabilized light source.Imaging mirror is arranged on the front of standard white plate with angle of inclination, and the projection of standard white plate is located at imaging mirror centre position, and optical spectrum imagers collect the textile positive and negative image of reflection and the image of standard white plate by imaging mirror.
Description
Technical field
The invention belongs to textile component detection technique field, more particularly to a kind of textile component detection means and side
Method.
Background technology
The detection of textile component is highly important link in textile industry, and at present, fiber qualitative analysis generally may be used
It is divided into physical identification method, chemical discrimination method, system discrimination method and other discrimination methods.So-called physical identification method refers to
Differentiate fiber using the morphological feature of textile fabric, physical property, such as feel ocular estimate, melting point method, optical microscopy, sweep
Retouch electron microscope method, infrared spectrum differential method, density gradient method, chromatography, birefringence method, blackout light method etc..Chemistry mirror
Other method is to differentiate fiber, such as combustion method, thermal analysis system, dissolution method, reagent color developing method using textile fabric chemical property.
System differential method is a kind of comprehensive method, and it is to utilize microscope observation, combustion method, densimetry, melting point method, coloring
Method, chloride nitrogenous detection method and dissolution method carry out integrating discriminating to fiber.Other discrimination methods are to analyze fiber with precision instrument
Internal microstructure so as to infer textile component form method.
Existing these methods analysis process is complicated, wastes time and energy, has certain danger, be unfriendly to environment, and needs
Want experienced staff to operate, be easily affected by human factors.Also some detection methods such as X-ray diffraction method, nuclear-magnetism is common
Though vibration wave spectrometry etc. can the more accurate composition composition that objectively obtain textile there is also operation difficulty is big, cost
The shortcomings of cost is high, time-consuming long.
The content of the invention
The present invention provides a kind of textile component detection means and method, is quickly and easily completed using double-face imaging principle
The detection of textile component.
A kind of textile component detection means, detection means include gripper frame, standard white plate, 2 pieces of reflective mirrors, banding light
Source, imaging mirror, optical spectrum imagers and computer,
Gripper frame is used to stretch, fixes textile to be detected, is provided with gripper frame side rectangular with gripper frame plane
Standard white plate, standard white plate provides standard correction thing for radiant correction,
2 pieces of reflective mirrors are then provided with the opposite side of gripper frame, 2 pieces of reflective mirrors are located at the positive and negative of gripper frame respectively, and 2
The minute surface of block reflective mirror forms acute angle with gripper frame interplanar, and 2 angle angles are identical,
The unlimited lateral edges of 2 pieces of reflective mirrors are provided with band light source, and shooting image provides stabilized light source,
Imaging mirror is arranged on the front of standard white plate with angle of inclination, and the projection of standard white plate is reflective positioned at being imaged
Mirror centre position, optical spectrum imagers collect the textile positive and negative image of reflection and the figure of standard white plate by imaging mirror
Picture.
Band light source is connected with computer, by computer regulated angle and brightness, meanwhile, the image of optical spectrum imagers collection
It is also communicated to computer.
A kind of textile component recognition methods, using described textile component detection means, it is characterised in that including with
Lower step：
Step 1: establish the standard high-spectral data storehouse of the various types of materials of textile；
Step 2: obtain the tow sides of textile to be measured and the high spectrum image of standard white plate；
Step 3: the high spectrum image is pre-processed；
Step 4: feature extraction is carried out to pretreated high spectrum image；
Step 5: combined standard high-spectral data storehouse, material identification is carried out to the high spectrum image after processing；
Step 6: the recognition result of the high spectrum image with reference to textile tow sides to be measured, statistical analysis weaving to be measured
The proportion of composing of various types of materials in product.
The method of the proportion of composing of various types of materials comprises the following steps in statistical analysis textile to be measured in the step 6：
Step I, statistics textile to be measured front high spectrum image all pixels point material identification result, common X is individual,
The pixel number of front high spectrum image corresponding to various materials is recorded, is denoted as x respectively1、x2、x3、…xm, wherein m expressions are just
The material category number of face high spectrum image；
Step II, statistics textile to be measured reverse side high spectrum image all pixels point material identification result, common Y
It is individual, the pixel number of reverse side high spectrum image corresponding to various materials is recorded, is denoted as y respectively1、y2、y3、…yn, wherein n tables
Show the material category number of reverse side high spectrum image；
Step III, proportion of composing corresponding to various types of materials in whole textile to be measured is calculated, be denoted as P respectively1、P2、P3、…
PS,
When the material identification result to front high spectrum image and reverse side high spectrum image includes identical material, by such as
Lower equation calculates,
P1=(x1+y1)/(X+Y), P2=(x2+y2)/(X+Y), P3=(x3+y3)/(X+Y)…PS=xm/ (X+Y) or PS
=yn/ (X+Y), wherein, the greater in s m, n；
When the material identification result to front high spectrum image and reverse side high spectrum image does not include identical material, press
Equation below calculates,
P1=x1/ (X+Y), P2=x2/ (X+Y), P3=x3/(X+Y)…PS=yn/ (X+Y), wherein, s m, n phases are in addition
With.
The preprocess method of the step 3 includes：Radiant correction, image rectification, noise reduction process and reflectivity conversion.
The feature extracting method of the step 4 includes：Spectral slope, absorb position, absorption area, spectrum integral, spectrum
Inverse, spectral slope, envelope removal, PCA, minimal noise separation MNF, successive projection algorithm, wavelet transformation,
One kind in adaptive band selection, singular value decomposition or noise adaptation principal component analysis.
Material identification method in the step 5 includes：The matching process of spectrum, SVMs, neutral net, shellfish
One kind in this grader of leaf or Spectral matching method.
The matching process of the spectrum includes spectral modeling matching, Spectral Characteristic fitting and binary coding matching.
The present invention obtains the high spectrum image of the positive and negative of textile to be measured, realizes and treat by double-face imaging device
The material identification of textile is surveyed, avoids to pollution caused by environment in traditional chemical discrimination process and operating personnel's person is pacified
Full threat, the unreliability in physics discrimination process is reduced, simplified the complicated procedures in system discrimination process, reduced
The cost differentiated using precision instrument, the influence of textile surface coating and final finishing to material identification is avoided, and it is whole
Individual process can save in the form of a file it is convenient follow-up consult, have the advantages that reliably, stably, it is accurate.It is this non-
Contact, more meet society instantly without destruction, the double-face imaging device of friendly, quick, reliable textile and material identification method
The needs of development.
Brief description of the drawings
Detailed description below, above-mentioned and other mesh of exemplary embodiment of the invention are read by reference to accompanying drawing
, feature and advantage will become prone to understand.In the accompanying drawings, if showing the present invention's by way of example, and not by way of limitation
Dry embodiment, wherein：
Fig. 1 is the detection means principle schematic of the present invention.
Fig. 2 is the schematic diagram of gripper frame in Fig. 1 of the present invention.
Wherein, 1- gripper frames, 2- standard white plates, 3- reflective mirrors, 4- band light sources, 5- imaging mirrors, 6- light spectrum image-formings
Instrument, 7- computers.
Embodiment
As shown in figure 1, the dimensional structure diagram of the present invention.It is used to textile material composition the invention provides one kind know
Other double-face imaging device, including for accommodating the gripper frame 1 of textile to be measured, the side of gripper frame 1 is provided with standard white plate
2, the standard white plate 2 is vertically fixedly connected with gripper frame 1, the opposite side of gripper frame 1 is provided with two reflective mirrors 3, two reflective
Mirror 3 is located at the both sides of gripper frame 1 respectively, and the two reflective mirrors 3 are intersecting and equal with the angle of gripper frame 1, intersects the intersection at end
With another side superimposed of gripper frame 1, open end is respectively provided with band light source 4, to pass through the two energy of reflective mirror 3 from a certain angle
It is enough to obtain the tow sides image of textile to be measured simultaneously, imaging mirror 5 is provided with the front of standard white plate 2, imaging is anti-
Light, 5 central face standard white plate 2, so that optical spectrum imagers 6 can be obtained from a certain angle by imaging mirror 5 simultaneously
The tow sides of textile to be measured and the high spectrum image of standard white plate, optical spectrum imagers 6 upload obtained high spectrum image
Processed to computer 7.
Textile material identification side based on the described double-face imaging device for being used for textile material identification in the present invention
Method, comprise the following steps：
Step 1: establish the standard high-spectral data storehouse of the various types of materials of textile；
Step 2: using double-face imaging device, the tow sides of textile to be measured and the high-spectrum of standard white plate are obtained
Picture；
Step 3: high spectrum image is pre-processed；
Step 4: feature extraction is carried out to pretreated high spectrum image；
Step 5: combined standard high-spectral data storehouse, material identification is carried out to the high spectrum image after processing；
Step 6: the recognition result of the high spectrum image with reference to textile tow sides to be measured, statistical analysis weaving to be measured
The proportion of composing of various types of materials in product.
Cover the various types of of in the market appearance in the standard high-spectral data storehouse of the various types of materials of established textile
Textile material, including string, animal origin, mineral fibres, regenerated fiber, synthetic fibers, inorfil are such as：Cotton, fiber crops, fruit
Real fiber, bamboo fibre, wool, the rabbit hair, silk, asbestos, viscose fiber, polyacetates, polyamide fibre, terylene, acrylic fibers, spandex, polyvinyl,
Polypropylene fibre, polyvinyl chloride fibre, glass fibre, metallic fiber etc..
Wherein, the method for the proportion of composing of various types of materials includes following step in statistical analysis textile to be measured in step 6
Suddenly：
Step I, statistics textile to be measured front high spectrum image all pixels point material identification result, common X is individual,
The pixel number of front high spectrum image corresponding to various materials is recorded, is denoted as x respectively1、x2、x3、…xm, wherein m expressions are just
The material category number of face high spectrum image；
Step II, statistics textile to be measured reverse side high spectrum image all pixels point material identification result, common Y
It is individual, the pixel number of reverse side high spectrum image corresponding to various materials is recorded, is denoted as y respectively1、y2、y3、…yn, wherein n tables
Show the material category number of reverse side high spectrum image；
Step III, proportion of composing corresponding to various types of materials in whole textile to be measured is calculated, be denoted as P respectively1、P2、P3、…
PS,
When the material identification result to front high spectrum image and reverse side high spectrum image includes identical material, by such as
Lower equation calculates,
P1=(x1+y1)/(X+Y), P2=(x2+y2)/(X+Y), P3=(x3+y3)/(X+Y)…PS=xm/ (X+Y) or PS
=yn/ (X+Y), wherein, the greater in s m, n；
When the material identification result to front high spectrum image and reverse side high spectrum image does not include identical material, press
Equation below calculates,
P1=x1/ (X+Y), P2=x2/ (X+Y), P3=x3/(X+Y)…PS=yn/ (X+Y), wherein, s m, n phases are in addition
With.
Wherein, the preprocess method of step 3 includes：Radiant correction, image rectification, noise reduction process and reflectivity conversion.Step
Rapid four feature extracting method includes：Spectral slope, absorb position, absorption area, spectrum integral, spectrum inverse, spectral slope,
Envelope removal, PCA, minimal noise separation MNF, successive projection algorithm, wavelet transformation, adaptive band selection,
One kind in singular value decomposition and noise adaptation principal component analysis.Material identification method in step 5 includes：The match party of spectrum
One kind in method, SVMs, neutral net, Bayes classifier and Spectral matching method.The matching process of spectrum includes
Spectral modeling matching, Spectral Characteristic fitting and binary coding matching.
What deserves to be explained is although foregoing teachings describe the essence of the invention by reference to some embodiments
God and principle, it should be appreciated that, the present invention is not limited to disclosed embodiment, the also unawareness of the division to each side
The feature that taste in these aspects can not combine, and this division is merely to the convenience of statement.It is contemplated that cover appended power
Included various modifications and equivalent arrangements in the spirit and scope that profit requires.
Claims (8)
- A kind of 1. textile component detection means, it is characterised in that detection means include gripper frame, standard white plate, 2 pieces it is reflective Mirror, band light source, imaging mirror, optical spectrum imagers and computer,Gripper frame is used to stretch, fixes textile to be detected, and the mark rectangular with gripper frame plane is provided with gripper frame side Quasi- blank, standard white plate provide standard correction thing for radiant correction,2 pieces of reflective mirrors are then provided with the opposite side of gripper frame, 2 pieces of reflective mirrors are located at the positive and negative of gripper frame respectively, and 2 pieces anti- The minute surface of light microscopic forms acute angle with gripper frame interplanar, and 2 angle angles are identical,The unlimited lateral edges of 2 pieces of reflective mirrors are provided with band light source, and shooting image provides stabilized light source,Imaging mirror is arranged on the front of standard white plate with angle of inclination, and the projection of standard white plate is located in imaging mirror Between position, optical spectrum imagers collect the textile positive and negative image of reflection and the image of standard white plate by imaging mirror.
- 2. textile component detection means as claimed in claim 1, it is characterised in that band light source is connected with computer, by counting Calculation machine adjusts angle and brightness, meanwhile, the image of optical spectrum imagers collection is also communicated to computer.
- 3. a kind of textile component recognition methods, using textile component detection means as claimed in claim 1, its feature exists In comprising the following steps：Step 1: establish the standard high-spectral data storehouse of the various types of materials of textile；Step 2: obtain the tow sides of textile to be measured and the high spectrum image of standard white plate；Step 3: the high spectrum image is pre-processed；Step 4: feature extraction is carried out to pretreated high spectrum image；Step 5: combined standard high-spectral data storehouse, material identification is carried out to the high spectrum image after processing；Step 6: the recognition result of the high spectrum image with reference to textile tow sides to be measured, in statistical analysis textile to be measured The proportion of composing of various types of materials.
- 4. detection method according to claim 3, it is characterised in that in the step 6 in statistical analysis textile to be measured The method of the proportion of composing of various types of materials comprises the following steps：Step I, statistics textile to be measured front high spectrum image all pixels point material identification result, common X, record The pixel number of front high spectrum image corresponding to various materials, is denoted as x respectively1、x2、x3、…xm, wherein m expressions front height The material category number of spectrum picture；Step II, statistics textile to be measured reverse side high spectrum image all pixels point material identification result, common Y, remember The pixel number of reverse side high spectrum image corresponding to various materials is recorded, is denoted as y respectively1、y2、y3、…yn, wherein n expression reverse side The material category number of high spectrum image；Step III, proportion of composing corresponding to various types of materials in whole textile to be measured is calculated, be denoted as P respectively1、P2、P3、…PS,When the material identification result to front high spectrum image and reverse side high spectrum image includes identical material, by such as lower section Journey calculates,P1=(x1+y1)/(X+Y), P2=(x2+y2)/(X+Y), P3=(x3+y3)/(X+Y)…PS=xm/ (X+Y) or PS=yn/ (X+Y), wherein, the greater in s m, n；When the material identification result to front high spectrum image and reverse side high spectrum image does not include identical material, by as follows Equation calculates,P1=x1/ (X+Y), P2=x2/ (X+Y), P3=x3/(X+Y)…PS=yn/ (X+Y), wherein, s m, n sums.
- 5. detection method according to claim 3, it is characterised in that the preprocess method of the step 3 includes：Radiation Correction, image rectification, noise reduction process and reflectivity conversion.
- 6. detection method according to claim 3, it is characterised in that the feature extracting method of the step 4 includes：Light Compose slope, absorb position, absorption area, spectrum integral, spectrum inverse, spectral slope, envelope removal, PCA, Minimal noise separation MNF, successive projection algorithm, wavelet transformation, adaptive band selection, singular value decomposition or noise adaptation it is main into One kind in point-score.
- 7. detection method according to claim 3, it is characterised in that the material identification method in the step 5 includes： One kind in the matching process of spectrum, SVMs, neutral net, Bayes classifier or Spectral matching method.
- 8. detection method according to claim 6, it is characterised in that the matching process of the spectrum includes spectral modeling Match somebody with somebody, Spectral Characteristic fitting and binary coding match.
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| CN117784721A (en) * | 2023-11-14 | 2024-03-29 | 东莞德芳油墨科技有限公司 | Intelligent control system for producing water-based environment-friendly ink |
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Application publication date: 20180327 |