CN102235972A - Spectral method of color measurement - Google Patents
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Abstract
The invention relates to a spectral method of color measurement, characterized by that: according to reflectance spectrums of a standard board and a comparative substance, establishing a color parameter database, carrying out data fusion between the collected color feature parameters of the substance to be measured and the color parameter database, and carrying out pattern recognition. According to the invention, a rapid, simple and objective measurement of the color of the substance is provided, the impacts of artificial factors, change of time and space and other uncertainties in the traditional subjective visual method on the accuracy of the measurement are avoided, so that the justice and fairness of the measure result is guaranteed.
Description
Technical field
The present invention relates to a kind of spectrum method for measuring color, this method can be used for materials such as the seed, blade to plant and carries out Non-Destructive Testing.
Background technology
How accurately, evaluation is deposited in materials such as together seed, blade objectively, perhaps is deposited in the industrial goods of shape in small, broken bits together, people pursue the problem that solves, and have also obtained certain achievement.Be that example describes below with tealeaves.
Tealeaves has been subjected to common people's welcome as traditional natural drink always.Along with the growth of tealeaves consumption, it is more and more important that the evaluation of tea leaf quality becomes.But the tealeaves color mainly still adopts subjective visual method to evaluate, and visual method is subjected to the influence of uncertain factors such as human factor and time, space change and causes error easily, is difficult to make objective evaluation.
The coloured color difference meter of the main method method, Computer Recognition Technology and the spectrum picture technology that are used for tealeaves color objective detection in the laboratory.
Color colour difference meter method is primarily aimed at homogeneous body, and promptly blank, hawk and all kinds of colour tables etc. because its surface color is even, only need to obtain whole colouring information by the color colorimeter measurement than the small size color.Tea Industry circular Vol.17No.2:1 (1995) adopts color colour difference meter method and L
*a
*b
*The chromatic value of color specification system characterizes the tealeaves color, and proofread and correct through standard white plate, and all adopt the standard sources irradiation, so the color characteristic that reflects the sample zonule that can be objective and accurate, and higher repeatability is arranged; But because tealeaves belongs to the heterogeneous body object, the local shade deviation on surface is bigger, and the detection area of this method is less, even adopt multimetering also to be difficult to the description and the evaluation of the overall color and luster of a certain tealeaves.
Computer Recognition Technology promptly adopts the CCD camera to differentiate as detecting element acquisition tealeaves image and by the computer color analysis, is a kind of widely used tealeaves method for measuring color.See agricultural mechanical journal Vol.31No.4:67 (2000) for details, Jiangsu University's journal (natural science edition) Vol.26No.6:461 (2005), this method can directly be obtained the image information of larger area tealeaves, meets the cognition custom of people to the tealeaves color.But adopt certain light source can cause the image of shooting different with tealeaves true colors under the natural light; Under the situation of the correction of not considering CCD camera colo(u)r bias, the color of image of acquisition there are differences with real tealeaves color.Adopt same equipment can distinguish the relative color distortion of tealeaves accurately, but can not true reappearance tealeaves color.In the trading of reality, lack unified standard, can't be used for fair evaluation.
The spectrum picture technology is the fusion of spectral analysis technique and image processing techniques, has both advantages concurrently, is that tealeaves color quick nondestructive detects a new research method.He Yong (spectroscopy and spectral analysis, Vol.28No.11:2527 (2008)), Chen Quansheng (optics journal, Vol.28No.4:669 (2008)) etc. the people adopts this technology that the tealeaves of different stage is distinguished respectively, owing to can accurately obtain spectral information, therefore the accuracy of its differentiation is very high, and can generally be suitable for.But this technology can not directly obtain color parameter, therefore can not describe the tealeaves color intuitively and make evaluation.In addition, owing to will obtain the image information of different wave length, the image data amount is big, and therefore the post-processed complexity is mainly used in the research of laboratory to tealeaves at present, is not suitable for industry Testing requirement fast.
Summary of the invention
In view of the deficiencies in the prior art, the purpose of this invention is to provide a kind of spectrum method for measuring color, this method can accurately obtain color parameter, can form standardized objective evaluation again, what both guaranteed whereby to test in the trading is just, can be fit to the requirement of industrial test again.
Spectrum method for measuring color of the present invention may further comprise the steps:
(1) adopts visible wide spectrum light source with 45 ° of irradiation detection viewing fields, on-gauge plate is placed detection viewing field, and adopt the reflected light of spectrometer (14) acceptance, thereby obtain the on-gauge plate reflectance spectrum from described on-gauge plate;
(2) first sample box that contrasts material will be housed and place described detection viewing field, and adopt visible wide spectrum light source with 45 ° of irradiation detection viewing fields, and adopt the reflected light of spectrometer acceptance, thereby obtain first contrast material reflectance spectrum from described material to be checked;
(3) repeating step (2) repeatedly, first contrast material reflectance spectrum that repeatedly obtains is average and obtain first contrast material average reflection spectrum;
(4) with on-gauge plate reflectance spectrum, first contrast material average reflection spectrum and on-gauge plate spectral reflectance substitution CIE1976L under D65 standard sources, 45 °/0 ° test condition
*a
*b
*In uniform colour space and the colour difference formula, calculate the color characteristic parameter L of first contrast material
*, a
*, b
*
(5) choose many batches of contrast materials, and carry out above-mentioned steps (1), (2), (3) and (4), thereby obtain the color characteristic parameter L of many batches of contrast materials at each batch contrast material
*, a
*, b
*
(6) according to above-mentioned first contrast material and the many batches of color characteristic parameter L that contrast materials
*, a
*, b
*Set up the color parameter database;
(7) choose material to be checked, carry out above-mentioned steps (1), (2), (3) and (4) at this material to be checked, to obtain the color characteristic parameter L of material to be checked
*, a
*, b
*
(8) color characteristic parameter L that will this material to be checked
*, a
*, b
*Carry out data fusion with above-mentioned color parameter database, the row mode of going forward side by side identification.
In spectrum method for measuring color of the present invention, described material to be checked is preferably seed or the blade of plant, for example is tealeaves, tobacco leaf, pipe tobacco, corn seed, soya seeds, rapeseed etc.Obviously, the present invention also goes for the detection of industrial goods such as small size sheet, granular chemical materials.
In the present invention, preferably adopt digital camera to obtain the picture of described material to be checked, and with the color characteristic parameter L of this material to be checked
*, a
*, b
*Storage accordingly.
In the present invention, preferably in the darkroom, carry out above-mentioned steps (1), (2), (5) and (7), to avoid the influence of parasitic light.
In addition, in the present invention, described visible wide spectrum light source preferably adopts the stabilized current supply power supply.
Preferably, before visible wide spectrum light source, add gradual change frosted glass, so that on shadow surface, form uniform light distribution.
Preferably, on the direction parallel with the material surface in the sample box, the center of sample box is the spot radius size of this visible wide spectrum light source on this shadow surface apart with the center of visible wide spectrum light source shadow surface of material surface in sample box, and the center of described visible wide spectrum light source shadow surface overlaps with the center of the probe of described spectrometer.
Preferably, described sample box stepping ground rotation in detection viewing field; More preferably, described sample box is placed on the electric rotary table in the detection viewing field, by the integral time interval greater than spectrometer of each step rotation of computer regulated electric rotary table.
Preferably, adopt the method for classifying modes of BF neural network to set up pattern recognition model.About neural network especially sees also " theory and the method for neural network structure design " by National Defense Industry Press's publication in 2005 about the document of BF neural network, the author who published in 2003 is " based on the Design of Virtual Instrument of LabVIEW " (this book) of Liu Junhua, and the author who published in 2006 is Han Liqun " artificial neural network study course ".
According to the present invention, can measure the overall color of interior material to be checked in a big way fast, compare with the color colour difference meter, can obtain the material color information to be checked of certain area, more accurate than multimetering, and be not subjected to the influence of detecting element self misalignment, really realize the absolute measurement of color; The color parameter of measuring is formed database, and set up recognition mode and avoid artificial judgement difference under the different situations, not only realize objective measurement, and guarantee objective evaluation.Therefore the present invention compares with classic method, has objective, advantage accurately.
Description of drawings
Specifically introduce the present invention with tealeaves as the example of material to be checked with reference to the accompanying drawings.Among the figure:
Fig. 1 is the spectrum method for measuring color hardware synoptic diagram of tealeaves color;
Fig. 2 is the spectrum method for measuring color software module of tealeaves color;
Fig. 3 is the spectrum method for measuring color pattern-recognition flow process of tealeaves color.
Embodiment
Below in conjunction with accompanying drawing, describe in detail according to the embodiment of the present invention.It is pointed out that these accompanying drawings only are schematically, nor necessarily be drawn to scale, do not constitute qualification to protection scope of the present invention.
Light source of the present invention preferably adopts the wide spectrum light source that can send the 380nm-780nm visible spectrum, for example bromine tungsten filament lamp.Be provided with gradual change frosted glass 14 before lamp, this gradual change frosted glass 14 can make it in different local transmitance differences according to the light intensity of light source, to reach through the uniform requirement of the light distribution of outgoing behind the frosted glass.Adopt this light source with 45 ° of irradiation detection viewing fields.This detection viewing field is the surface level at place, tealeaves described later surface.On-gauge plate is placed detection viewing field, and adopt the reflected light of spectrometer acceptance, thereby obtain the on-gauge plate reflectance spectrum from described on-gauge plate.
The sample box 9 that first contrast tealeaves is housed is placed described detection viewing field, adopt above-mentioned light source with 45 ° of irradiation detection viewing fields, and adopt the reflected light of spectrometer acceptance, thereby obtain first contrast material reflectance spectrum from described contrast tealeaves; The rotary sample box also repeatedly repeats this step, and first contrast material reflectance spectrum that repeatedly obtains is on average obtained first contrast material average reflection spectrum.With on-gauge plate reflectance spectrum, first contrast tealeaves average reflection spectrum and on-gauge plate spectral reflectance substitution CIE1976L under D65 standard sources, 45 °/0 ° test condition
*a
*b
*In uniform colour space and the colour difference formula, calculate the color characteristic parameter L of first contrast tealeaves
*, a
*, b
*
Choose many batches of contrast tealeaves, and carry out above-mentioned steps, thereby obtain the color characteristic parameter L of many batches of contrast tealeaves at each batch contrast tealeaves
*, a
*, b
*
Color characteristic parameter L according to above-mentioned first contrast tealeaves and many batches of contrast tealeaves
*, a
*, b
*Set up the color parameter database, compare tealeaves to be checked fully.
When detecting tealeaves, tealeaves to be checked is filled sample box 9, cover after the sample lid 10, be placed on the rotary electric platform 7, connect shake oscillator power supply 17, shake 1 minute, guarantee that the tealeaves sample surfaces is smooth after, take off the sample lid.Open light source subsequently, promptly bromine tungsten filament lamp 13.After the power supply 16 that turns on the light, make bromine tungsten filament lamp 13 preheating numbers minute.Making the light that arrives detection viewing field (test surface is promptly at the surface level at tealeaves sample surfaces place) form diameter is the even light distribution of Φ 40mm.The detection viewing field center is coaxial with the center of detector (being the optical fiber interface 12 of spectrometer), and the spot center that forms at test surface with light source is at a distance of 20mm.Obtain on-gauge plate 6 reflectance spectrum φ 1 (λ) by fiber spectrometer 15.Control translation motorized stage 4 makes sample box place detection viewing field, 7 rotations of control rotary electric platform, be provided with fiber spectrometer this rotary electric platform 7 whenever rotate a circle during in repeatedly sample, obtain tealeaves surface reflectance spectra φ 2 (λ) thus.This sampling number can be determined according to instruction of the present invention and actual conditions by those skilled in the art, for example sample 72 times.Adopt digital camera to take tealeaves image and storage at last.
Need to prove at this, for the acquisition mode of on-gauge plate with the reflectance spectrum of contrast tealeaves, can be identical with the mode of the reflectance spectrum that obtains above-mentioned tealeaves to be checked.
Because known standard plate spectral reflectance ρ 1 (λ), obtain averaged spectrum reflectance ρ 2 (λ)=φ 2 (λ) * ρ 1 (λ)/φ 1 (λ) of sample surfaces to be checked, according to cie color system tristimulus values calculating formula:
Wherein,
S (λ) is that the relative spectral power of D65 light source distributes.
It is CIE specified standard colourity observer's spectral tristimulus value.K is a normalization coefficient,
Δ λ=5mm wherein.Obtain tristimulus values X, Y, Z in the visible-range integrates.
Thereby calculate L
*, a
*, b
*The color space:
Wherein, X
n, Y
n, Z
nFor the CIE standard illuminants is radiated on the perfectly diffusion reflector, reflex to the white tristimulus values in observer's face.
Obtain color parameter L
*, a
*, b
*According to color parameter, adopt the BF neural network of three-decker that the color of tealeaves is judged at last.The BF neural network of this three-decker has 3 inputs, and output layer is 1 neuron, and hidden neuron is defined as 4 through experiment.
In the present invention, light source adopts the bromine tungsten filament lamp of dc current stabilized power supply power supply, light stability; Adopt in the sample chamber and shake and translation motorized stage sample presentation, avoid in the artificial sample presentation process influence of profile pattern is guaranteed the repeatedly consistance of sample presentation condition; Adopt large-scale irradiated area and detection area and repeatedly measure to be averaged the average reflection spectrum that obtains tealeaves, improve the anisotropic property of tealeaves; Adopt the digital camera store images, because of remeasuring the trade dispute that causes after the tealeaves variable color; Adopt the CCD spectrometer can measure the overall color of interior tealeaves in a big way fast as detector, compare with the color colour difference meter, can obtain the tealeaves colouring information of certain area, more accurate than multimetering, compare with the CCD camera in the Computer Recognition Technology, be not subjected to the influence of detecting element self misalignment, really realize the absolute measurement of color; Adopt 18% hawk as on-gauge plate, avoid the standard white plate reflection too high, the tealeaves reflection is low, causes the low problem of signal to noise ratio (S/N ratio); And there is not the influence of mirror image gloss, more accurate reflection actual color feature.The color parameter of measuring is formed database, and set up recognition mode and avoid artificial judgement difference under the different situations, not only realize objective measurement, and guarantee objective evaluation.Therefore this device is compared with classic method, has objective, advantage accurately, and its repeatability precision can reach ± and 0.5%.
The characteristic parameter of 5 measurements of table 1 blue mountains and green waters and 2 kinds of green bamboo snakes.
Specific embodiment described herein only is that the present invention's spirit is illustrated.The technician of the technical field of the invention can make various modifications or replenishes or adopt similar mode to substitute described embodiment, and can be individually or adopt above-mentioned each feature in combination, do not depart from spirit of the present invention, do not exceed the appended claims restricted portion yet.
Claims (10)
1. spectrum method for measuring color, this spectrum method for measuring color may further comprise the steps:
(1) adopts visible wide spectrum light source with 45 ° of irradiation detection viewing fields, on-gauge plate is placed detection viewing field, and adopt the reflected light of spectrometer (14) acceptance, thereby obtain the on-gauge plate reflectance spectrum from described on-gauge plate;
(2) first sample box that contrasts material will be housed and place described detection viewing field, adopt visible wide spectrum light source with 45 ° of irradiation detection viewing fields, and adopt the reflected light of spectrometer (14) acceptance, thereby obtain first contrast material reflectance spectrum from described contrast material;
(3) repeating step (2) repeatedly, first contrast material reflectance spectrum that repeatedly obtains is average and obtain first contrast material average reflection spectrum;
(4) with on-gauge plate reflectance spectrum, first contrast material average reflection spectrum and on-gauge plate spectral reflectance substitution CIE1976L under D65 standard sources, 45 °/0 ° test condition
*a
*b
*In uniform colour space and the colour difference formula, calculate the color characteristic parameter L of first contrast material
*, a
*, b
*
(5) choose many batches of contrast materials, and carry out above-mentioned steps (1), (2), (3) and (4), thereby obtain the color characteristic parameter L of many batches of contrast materials at each batch contrast material
*, a
*, b
*
(6) according to above-mentioned first contrast material and the many batches of color characteristic parameter L that contrast materials
*, a
*, b
*Set up the color parameter database;
(7) choose material to be checked, carry out above-mentioned steps (1), (2), (3) and (4) at this material to be checked, to obtain the color characteristic parameter L of material to be checked
*, a
*, b
*
(8) color characteristic parameter L that will this material to be checked
*, a
*, b
*Carry out data fusion with above-mentioned color parameter database, the row mode of going forward side by side identification.
2. spectrum method for measuring color as claimed in claim 1 is characterized in that:
Seed or blade that described material to be checked is a plant for example are tealeaves, tobacco leaf, pipe tobacco, corn seed, soya seeds, rapeseed etc.
3. spectrum method for measuring color as claimed in claim 1 or 2 is characterized in that:
In step (8) afterwards, adopt digital camera (11) to obtain the picture of described material to be checked, and with the color characteristic parameter L of this material to be checked
*, a
*, b
*Storage accordingly.
4. spectrum method for measuring color as claimed in claim 1 or 2 is characterized in that: carry out above-mentioned steps (1), (2), (5) and (7) in the darkroom, to avoid the influence of parasitic light.
5. spectrum method for measuring color as claimed in claim 1 or 2 is characterized in that: described visible wide spectrum light source adopts the stabilized current supply power supply.
6. spectrum method for measuring color as claimed in claim 1 or 2 is characterized in that: add gradual change frosted glass before visible wide spectrum light source, so that form uniform light distribution on shadow surface.
7. spectrum method for measuring color as claimed in claim 1 or 2, it is characterized in that: on the direction parallel with the material surface in the sample box, the center of sample box is this visible wide spectrum light source spot radius size on the material surface in sample box apart with the center of visible wide spectrum light source shadow surface of material surface in sample box, and the center of described visible wide spectrum light source shadow surface overlaps with the center of the optical fiber interface of described spectrometer.
8. spectrum method for measuring color as claimed in claim 1 or 2 is characterized in that: described sample box is the rotation of stepping ground in detection viewing field.
9. spectrum method for measuring color as claimed in claim 8 is characterized in that: described sample box is placed on the electric rotary table in the detection viewing field, by the integral time interval greater than spectrometer of each step rotation of computer regulated electric rotary table.
10. spectrum method for measuring color as claimed in claim 1 or 2 is characterized in that: adopt the method for classifying modes of BF neural network to set up pattern recognition model.
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Cited By (9)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102829872A (en) * | 2012-08-14 | 2012-12-19 | 北京印刷学院 | Method and device for color measurement with contact image sensor |
| CN105300522A (en) * | 2015-09-20 | 2016-02-03 | 杭州电子科技大学 | Chromaticity quantitative calculation method capable of reducing influence of color measurement uncertainty |
| CN107578067A (en) * | 2017-09-15 | 2018-01-12 | 国家烟草质量监督检验中心 | A kind of recognition methods of pipe tobacco component and device based on convolutional neural networks |
| CN108627458A (en) * | 2018-04-02 | 2018-10-09 | 江苏科泰检测技术服务有限公司 | Spectral method of detection and system |
| CN109655413A (en) * | 2017-10-11 | 2019-04-19 | 罗伯特·博世有限公司 | The method for obtaining plant information |
| CN110411955A (en) * | 2019-07-15 | 2019-11-05 | 中山大学中山眼科中心 | A kind of artificial intelligence training system based on characterization of molecules predicting of substance color smell |
| CN111380812A (en) * | 2020-02-24 | 2020-07-07 | 红塔烟草(集团)有限责任公司 | Method for quickly identifying flue-cured tobacco and cinnabar tobacco leaves |
| CN111964781A (en) * | 2020-07-31 | 2020-11-20 | 上海毅兴塑胶原料有限公司 | Double color matching spectrum color measuring instrument for nonhomogeneity |
| CN112071257A (en) * | 2020-07-31 | 2020-12-11 | 佛山市青松科技股份有限公司 | LED screen correction method and device, storage medium and LED screen |
Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US5759030A (en) * | 1996-01-02 | 1998-06-02 | Lj Laboratories, L.L.C. | Method for determing optical characteristics of teeth |
| US20020063721A1 (en) * | 1998-01-26 | 2002-05-30 | Yutaka Masuda | Method for classifying and arranging metallic paint colors |
| CN101620180A (en) * | 2009-05-08 | 2010-01-06 | 合肥美亚光电技术有限责任公司 | Method for rapidly detecting tea quality through near infrared technology |
-
2010
- 2010-04-30 CN CN201010160453.2A patent/CN102235972B/en not_active Expired - Fee Related
Patent Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US5759030A (en) * | 1996-01-02 | 1998-06-02 | Lj Laboratories, L.L.C. | Method for determing optical characteristics of teeth |
| US20020063721A1 (en) * | 1998-01-26 | 2002-05-30 | Yutaka Masuda | Method for classifying and arranging metallic paint colors |
| CN101620180A (en) * | 2009-05-08 | 2010-01-06 | 合肥美亚光电技术有限责任公司 | Method for rapidly detecting tea quality through near infrared technology |
Non-Patent Citations (5)
| Title |
|---|
| 吴迪 等: "基于离散余弦变换和支持向量机的多光谱纹理图像的茶叶分类研究", 《光谱学与光谱分析》 * |
| 孟宪江: "利用光谱和神经网络技术的生物表面特性研究", 《中国优秀博硕士学位论文全文数据库》 * |
| 李晓丽 等: "一种基于可见近红外光谱快速鉴别茶叶品种的新方法", 《光谱学与光谱分析》 * |
| 陈孝敬 等: "基于多光谱图像颜色特征的茶叶分类研究", 《光谱学与光谱分析》 * |
| 陈潇潇 等: "基于光纤光谱仪测量茶叶表面颜色的研究", 《应用光学》 * |
Cited By (11)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102829872A (en) * | 2012-08-14 | 2012-12-19 | 北京印刷学院 | Method and device for color measurement with contact image sensor |
| CN105300522A (en) * | 2015-09-20 | 2016-02-03 | 杭州电子科技大学 | Chromaticity quantitative calculation method capable of reducing influence of color measurement uncertainty |
| CN107578067A (en) * | 2017-09-15 | 2018-01-12 | 国家烟草质量监督检验中心 | A kind of recognition methods of pipe tobacco component and device based on convolutional neural networks |
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