CN110487737A - Image information for smart phone spectral detection is extracted and calculation method and system - Google Patents
Image information for smart phone spectral detection is extracted and calculation method and system Download PDFInfo
- Publication number
- CN110487737A CN110487737A CN201910914772.9A CN201910914772A CN110487737A CN 110487737 A CN110487737 A CN 110487737A CN 201910914772 A CN201910914772 A CN 201910914772A CN 110487737 A CN110487737 A CN 110487737A
- Authority
- CN
- China
- Prior art keywords
- value
- gray
- image
- sample
- max
- 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.)
- Granted
Links
- 230000003595 spectral effect Effects 0.000 title claims abstract description 38
- 238000004364 calculation method Methods 0.000 title claims abstract description 22
- 238000001514 detection method Methods 0.000 title claims abstract description 20
- 238000002835 absorbance Methods 0.000 claims abstract description 30
- 238000001228 spectrum Methods 0.000 claims abstract description 30
- 238000012360 testing method Methods 0.000 claims abstract description 11
- 238000000034 method Methods 0.000 claims description 12
- 239000011159 matrix material Substances 0.000 claims description 10
- 238000000605 extraction Methods 0.000 claims description 6
- 239000000203 mixture Substances 0.000 claims description 6
- 239000003086 colorant Substances 0.000 claims description 5
- 238000006243 chemical reaction Methods 0.000 claims description 3
- 238000012886 linear function Methods 0.000 claims description 3
- 238000012821 model calculation Methods 0.000 claims description 3
- 238000012545 processing Methods 0.000 claims description 3
- 238000002834 transmittance Methods 0.000 claims description 3
- 239000000284 extract Substances 0.000 claims description 2
- 238000010586 diagram Methods 0.000 claims 1
- 238000004422 calculation algorithm Methods 0.000 abstract description 3
- 238000002798 spectrophotometry method Methods 0.000 abstract description 2
- 239000000126 substance Substances 0.000 description 5
- XKMRRTOUMJRJIA-UHFFFAOYSA-N ammonia nh3 Chemical compound N.N XKMRRTOUMJRJIA-UHFFFAOYSA-N 0.000 description 3
- 239000006185 dispersion Substances 0.000 description 3
- 230000008569 process Effects 0.000 description 3
- 238000011088 calibration curve Methods 0.000 description 2
- 238000005516 engineering process Methods 0.000 description 2
- 230000003287 optical effect Effects 0.000 description 2
- 238000010422 painting Methods 0.000 description 2
- 241000531807 Psophiidae Species 0.000 description 1
- 239000000090 biomarker Substances 0.000 description 1
- 230000008859 change Effects 0.000 description 1
- 238000011161 development Methods 0.000 description 1
- 230000000694 effects Effects 0.000 description 1
- 230000036541 health Effects 0.000 description 1
- 230000006872 improvement Effects 0.000 description 1
- 238000007689 inspection Methods 0.000 description 1
- 238000012986 modification Methods 0.000 description 1
- 230000004048 modification Effects 0.000 description 1
- 238000012544 monitoring process Methods 0.000 description 1
- 230000001737 promoting effect Effects 0.000 description 1
- 102000004169 proteins and genes Human genes 0.000 description 1
- 108090000623 proteins and genes Proteins 0.000 description 1
- 238000011002 quantification Methods 0.000 description 1
- 238000004445 quantitative analysis Methods 0.000 description 1
- 238000011160 research Methods 0.000 description 1
- 230000004044 response Effects 0.000 description 1
- 210000003296 saliva Anatomy 0.000 description 1
- 238000010183 spectrum analysis Methods 0.000 description 1
- 210000004243 sweat Anatomy 0.000 description 1
Classifications
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N21/00—Investigating or analysing materials by the use of optical means, i.e. using sub-millimetre waves, infrared, visible or ultraviolet light
- G01N21/17—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
- G01N21/3103—Atomic absorption analysis
Landscapes
- Physics & Mathematics (AREA)
- Spectroscopy & Molecular Physics (AREA)
- Health & Medical Sciences (AREA)
- Life Sciences & Earth Sciences (AREA)
- Chemical & Material Sciences (AREA)
- Analytical Chemistry (AREA)
- Biochemistry (AREA)
- General Health & Medical Sciences (AREA)
- General Physics & Mathematics (AREA)
- Immunology (AREA)
- Pathology (AREA)
- Investigating Or Analysing Materials By Optical Means (AREA)
- Spectrometry And Color Measurement (AREA)
Abstract
The image information that the invention discloses a kind of for smart phone spectral detection is extracted and calculation method, comprising: obtains the RGB image of spectrum picture, and by image rotation to unified angle;According to different samples, the effective image-region of selected digital image;The rgb value in selection area is extracted, converts gray value for the rgb value in region;By gray value of image inverse model, the absorbance of sample is calculated, the absorbance of various concentration standard sample is obtained according to test, using sample concentration as abscissa, absorbance is ordinate, draws concentration-absorbance scatter plot and establishes sample standard curve, calculates the concentration of actual sample.The present invention is widely used in the sample that can be tested by spectrophotometry, and is suitable for various types of smart phones, and algorithm operation is simple and accuracy is high.
Description
Technical field
The present invention relates to spectral detections and technical field of image processing, examine more particularly to one kind for smart phone spectrum
The image information of survey is extracted and calculation method and system.
Background technique
Spectrum analysis is determined for the chemical composition and relative amount of substance, in food safety, bio-safety, environment
The fields such as monitoring and health care play an important role.The large-scale spectrometer of use for laboratory is heavy and expensive, is unable to satisfy people
To target sample carry out in real time, the demand that detects on the spot, therefore, portable spectroanalysis instrument obtains continuous development.Modern intelligence
Energy mobile phone includes different sensor technology, can be used as independent measuring instrument and is widely used in every field.It is examined in spectrum
In survey, optical spectroscopic part can be integrated and be made into outer handset device, it is cooperated with mobile phone, utilizes smart phone
Cmos sensor will transmit through sample optical signal and be changed into electric signal, and image is shown on mobile phone screen by interpreting electric signal,
Cooperate the cell phone software with color quantizing model that the quantitative analysis of sample to be tested can be realized again.
Currently, many scholars at home and abroad carried out research to color quantizing model.Abbaspour et al. is by the RGB of image
Color value is converted into absorbance, calculates Fe+2、Fe3+Concentration;Oncescu proposes to represent face using the H value in HSV model
Color detects the biomarker in sweat and saliva;Suzuki etc. is using the chromaticity coordinate of CIE XYZ to Li+, NH4+ and protein
It is determined.The result shows that it is close with large-scale instrument test result using the testing concentration that image color information tests out,
With very strong feasibility.But different color model has differences the quantification manner of image, different for chromogenic reaction
Substance is needed using specific color model, therefore above-mentioned color model is difficult to be widely used.
Chinese patent literature CN 107084790A discloses a kind of spectrum inspection of portable spectrometer based on smart phone
Survey method, comprising: 1) collect to light signal;(2) it treats light signal and carries out collimating and correcting and dispersion light splitting, formed and press wavelength
The dispersion striped being arranged successively;(3) it is shot by the dispersion striped that smart phone obtains step (2), is formed and press wavelength
The color fringe picture being arranged successively;(4) rgb value of each location of pixels point of the color fringe picture that obtaining step (3) obtains,
And the corresponding light intensity value I of each location of pixels point is calculated, array I (x) is obtained, wherein x is picture pixels location point coordinate;(5)
According to wavelength-location of pixels nominal data λ (x), the x in array I (x) is replaced with corresponding λ, obtains pair of wavelength and light intensity
It answers relations I (λ), the corresponding curve of spectrum of drawing data I (λ), completes spectral detection.Above-mentioned color model is difficult to be widely used.
In addition to this, the image of different model mobile phone, which is shown, has differences, and can be suitably used for same model using the fixed method of pixel
Mobile phone, but use is there may be pictorial information load failure on the mobile phone of different model or data error is excessive etc. asks
Topic.Therefore, developing the image information that one can apply to different model mobile phone and extracting just seems most important with calculation method.
Summary of the invention
In order to solve above-mentioned technical problem, the present invention provides a kind of images for smart phone spectral detection
Information extraction and calculation method and system, the precision for promoting mobile phone spectrometer image procossing and APP are on various trumpeter's machine
Compatibility.
The technical scheme is that
A kind of image information extraction and calculation method for smart phone spectral detection, comprising the following steps:
S01: obtaining the RGB image of spectrum picture, and by image rotation to unified angle;
S02: according to different samples, the effective image-region of selected digital image;
S03: the rgb value in selection area is extracted, converts gray value for the rgb value in region;
S04: by gray value of image inverse model, calculating the absorbance of sample, obtains various concentration standard according to test
The absorbance of sample, using sample concentration as abscissa, absorbance is ordinate, draws concentration-absorbance scatter plot and establishes sample
Standard curve calculates the concentration of actual sample.
In preferred technical solution, in the step S02 selected digital image effective image-region the following steps are included:
S21: setting is multiple be more than or equal to 2 × 2 color block message, obtained on RGB image and continuously meet the face of condition
The color block of color dot composition, records the location information (x, y) of color block;
S22: union is taken to obtain x the position of all colours blockmax、xmin、ymax、ymin, a square is determined by this 4 points
Shape region scales the coordinate size of spectral diffraction vertical direction y on the basis of this rectangular area, and scaling formula is as follows:
(y1,y2)=(ymax-(ymax-ymin)/a,ymin+(ymax-ymin)/a)
Wherein y1, y2For the coordinate after scaling;A is the scaling multiple of setting, and a cannot be less than 2;
S23: effective image-region is (xmax, y1), (xmin, y1), (xmax, y2), (xmin, y2) this 4 points determinations rectangle
Region.
In preferred technical solution, in the step S03 rgb value be converted into gray value formula it is as follows:
Gray=(Rvalue+Gvalue+Bvalue)/3
Wherein Gray is gray value, Rvalue、Gvalue、BvalueFor the value of each component of R, G, B;
In preferred technical solution, the gray value two-dimensional matrix of acquisition is reduced to one-dimensional, calculating spectral diffraction vertical direction
Gray value average value, the calculation formula of average gray is as follows:
Wherein,For average gray, n y1-y2, i y2To y1Between coordinate value;
Gray value-pixel curve graph is drawn with the one-dimensional matrix along spectral diffraction direction being calculated.
In preferred technical solution, in the step S04 most by gray scale in the spectrum picture region generated without sample
Big value is used as incident intensity, and gray scale maximum value is as output intensity, image grayscale in the spectrum picture region generated by sample
It is as follows to be worth inverse model calculation formula:
A=lg (1/T)=lg (gray1/gray2)
Wherein, A is absorbance, and T is transmittance, gray1For the spectrum picture area grayscale maximum generated without sample
Value, gray2For the spectrum picture area grayscale maximum value generated by sample.
In preferred technical solution, according to least square method in the step S04, a linear function curve is fitted,
As sample standard curve, calibration curve formula is as follows:
Y=aX+b
Wherein, Y is sample concentration, and X is the absorbance of sample, and a is the slope fitted, and b is the intercept fitted.
The image information extraction and computing system that the invention also discloses a kind of for smart phone spectral detection, comprising:
Spectrum picture processing module, obtains the RGB image of spectrum picture, and by image rotation to unified angle;
Effective image-region extraction module, according to different samples, the effective image-region of selected digital image;
Conversion module extracts the rgb value in selection area, converts gray value for the rgb value in region;
Sample standard curve establishes module, by gray value of image inverse model, the absorbance of sample is calculated, according to test
The absorbance of various concentration standard sample is obtained, using sample concentration as abscissa, absorbance is ordinate, draws concentration-extinction
Degree scatter plot establishes sample standard curve, calculates the concentration of actual sample.
In preferred technical solution, the effective image-region of the selected digital image the following steps are included:
S21: setting is multiple be more than or equal to 2 × 2 color block message, obtained on RGB image and continuously meet the face of condition
The color block of color dot composition, records the location information (x, y) of color block;
S22: union is taken to obtain x the position of all colours blockmax、xmin、ymax、ymin, a square is determined by this 4 points
Shape region scales the coordinate size of spectral diffraction vertical direction y on the basis of this rectangular area, and scaling formula is as follows:
(y1,y2)=(ymax-(ymax-ymin)/a,ymin+(ymax-ymin)/a)
Wherein y1, y2For the coordinate after scaling;A is the scaling multiple of setting, and a cannot be less than 2;
S23: effective image-region is (xmax, y1), (xmin, y1), (xmax, y2), (xmin, y2) this 4 points determinations rectangle
Region.
In preferred technical solution, the formula that the rgb value is converted into gray value is as follows:
Gray=(Rvalue+Gvalue+Bvalue)/3
Wherein Gray is gray value, Rvalue、Gvalue、BvalueFor the value of each component of R, G, B;
In preferred technical solution, the gray value two-dimensional matrix of acquisition is reduced to one-dimensional, calculating spectral diffraction vertical direction
Gray value average value, the calculation formula of average gray is as follows:
Wherein,For average gray, n y1-y2, i y2To y1Between coordinate value;
Gray value-pixel curve graph is drawn with the one-dimensional matrix along spectral diffraction direction being calculated.
Compared with prior art, the invention has the advantages that
The present invention is directed to different test substances, and frame, which is selected, needs spectrum picture region to be used, it is possible to reduce mobile phone
Operand optimizes the speed of service of APP, and can promote the accuracy of data in subsequent calculating process.The present invention fits extensively
Sample for that can be tested by spectrophotometry, and it is suitable for various types of smart phones, algorithm operation is simple and accurate
Degree is high.
Detailed description of the invention
The invention will be further described with reference to the accompanying drawings and embodiments:
Fig. 1 is the flow chart of image information extraction and calculation method of the present invention for smart phone spectral detection;
Fig. 2 is the effective image-region that frame is selected;
Fig. 3 is gray value-pixel curve graph;
Fig. 4 is the gray value curve of various concentration ammonia nitrogen standard sample;
Fig. 5 is ammonia nitrogen standard curve.
Specific embodiment
In order to make the objectives, technical solutions and advantages of the present invention clearer, With reference to embodiment and join
According to attached drawing, the present invention is described in more detail.It should be understood that these descriptions are merely illustrative, and it is not intended to limit this hair
Bright range.In addition, in the following description, descriptions of well-known structures and technologies are omitted, to avoid this is unnecessarily obscured
The concept of invention.
Embodiment:
With reference to the accompanying drawing, presently preferred embodiments of the present invention is described further.
The present embodiment is by taking ammonia nitrogen is tested as an example.
As shown in Figure 1, a kind of image information for smart phone spectral detection is extracted and calculation method, calculation of the invention
Method operation is simple and accuracy is high, and the mobile phone generally configured can be run, and can also be certainly PAD etc. other terminal devices,
It includes identifying and obtaining the spectrum picture generated by external device, and be based on mobile phone placement angle, adjusts picture angle, passes through
Color block parameter is set, effective image-region is obtained, the gray scale of spectral diffraction directional image is obtained eventually by RGB color model
Value, brings into the model of foundation, calculates the concentration of determinand (sample).Comprising the following steps:
1) in the image projection for taking mobile phone to two-dimentional canvas painting canvas, RGB image is obtained;
2) image rotation angle information is transferred from mobile phone camera, and the RGB image on canvas painting canvas is rotated into unification
The angle of setting;
3) it is directed to different test substances, frame, which is selected, needs spectrum picture region to be used, it is possible to reduce the operation of mobile phone
Amount, optimizes the speed of service of APP, and can promote the accuracy of data in subsequent calculating process.The core of this process is to make
With tracking.js database, the position of color block on the entire image is judged on the basis of the color block parameter of setting,
Specific color block parameter can be arranged by a configuration file;
3.1) configuration file by set it is multiple be more than or equal to 2 × 2 color block message (rgb value), obtained on RGB image
The color block for continuously meeting the color point composition of condition is taken, records the fast location information (x, y) of these colors, x spreads out for spectrum
Direction coordinate is penetrated, y is spectral diffraction vertical direction coordinate.Union is taken to obtain x the position of these color blocksmax、xmin、ymax、
ymin, can determine a rectangular area by this 4 points, scaling is perpendicular to spectral diffraction direction on the basis of this rectangular area
Coordinate size, the difference bring for reducing spectrum picture two sides and middle section calculate error.Specific scaling formula is as follows:
(y1,y2)=(ymax-(ymax-ymin)/a,ymin+(ymax-ymin)/a)
Wherein y1, y2For the coordinate after scaling;A is the scaling multiple being arranged according to concrete condition, and the smaller scaling multiple of a is got over
Greatly, the bigger scaling multiple of a is smaller, and a cannot be less than 2;
3.2)(xmax, y1), (xmin, y1), (xmax, y2), (xmin, y2) it is the final rectangular image area for participating in calculating
Four vertex, as shown in Figure 2.
4) image information that step (3) obtain is changed into digital information;
4.1) rgb value for extracting effective image-region, converts gray value for the rgb value in region.RGB turns the calculation of gray scale
There are many kinds of methods, and this method chooses the best average algorithm of effect by attempting, RGB turn gray value specific formula is as follows:
Gray=(Rvalue+Gvalue+Bvalue)/3
Wherein Gray is gray value, Rvalue、Gvalue、BvalueFor the value of each component of R, G, B.
4.2) the gray value two-dimensional matrix of acquisition is reduced to one-dimensional, the gray value for calculating spectral diffraction vertical direction is average
Value, y are the coordinate perpendicular to spectral diffraction direction, and average gray specific formula for calculation is as follows:
Wherein,For average gray, n y1-y2, i y2To y1Between coordinate value;
Gray value-pixel curve graph is made with the one-dimensional matrix along spectral diffraction direction being calculated, as shown in figure 3,
This curve graph includes the above-mentioned average gray selected within the scope of figure;
5) gray value of image inverse model is used, sample standard curve is established;
5.1) gray value of image inverse model simulates lambert-Beer law, will be without to keep signal response maximum
Gray scale maximum value is as incident intensity in the spectrum picture region that sample generates, ash in the spectrum picture region generated by sample
Maximum value is spent as output intensity, and model calculation formula is as follows:
A=lg (1/T)=lg (gray1/gray2)
Wherein, A is absorbance, and T is transmittance, gray1For the spectrum picture area grayscale maximum generated without sample
Value, gray2For the spectrum picture area grayscale maximum value generated by sample;
5.2) absorbance of various concentration standard sample is tested out, as shown in figure 4, wherein black box has for what frame was selected
Region is imitated, I0 is for the gray value curve of the spectrum picture generated without sample, and 0-2 is raw by various concentration standard sample
At spectrum picture gray value curve.
Using sample concentration as abscissa, absorbance is ordinate, concentration-absorbance scatter plot is made, according to least square
Method fits a linear function curve, which is the standard curve of sample, as shown in Figure 5.Calibration curve formula is such as
Under:
Y=aX+b
Wherein, Y is sample concentration, and X is the absorbance of sample, and a is the slope fitted, and b is the intercept fitted;
The actual sample absorbance value that test is obtained substitutes into standard curve, can calculate the concentration of actual sample.
It should be understood that above-mentioned specific embodiment of the invention is used only for exemplary illustration or explains of the invention
Principle, but not to limit the present invention.Therefore, that is done without departing from the spirit and scope of the present invention is any
Modification, equivalent replacement, improvement etc., should all be included in the protection scope of the present invention.In addition, appended claims purport of the present invention
Covering the whole variations fallen into attached claim scope and boundary or this range and the equivalent form on boundary and is repairing
Change example.
Claims (10)
1. a kind of image information for smart phone spectral detection is extracted and calculation method, which is characterized in that including following step
It is rapid:
S01: obtaining the RGB image of spectrum picture, and by image rotation to unified angle;
S02: according to different samples, the effective image-region of selected digital image;
S03: the rgb value in selection area is extracted, converts gray value for the rgb value in region;
S04: by gray value of image inverse model, calculating the absorbance of sample, obtains various concentration standard sample according to test
Absorbance, using sample concentration as abscissa, absorbance is ordinate, draw concentration-absorbance scatter plot establish sample standard
Curve calculates the concentration of actual sample.
2. the image information according to claim 1 for smart phone spectral detection is extracted and calculation method, feature
Be, in the step S02 selected digital image effective image-region the following steps are included:
S21: setting is multiple be more than or equal to 2 × 2 color block message, obtained on RGB image and continuously meet the color point of condition
The color block of composition records the location information (x, y) of color block;
S22: union is taken to obtain x the position of all colours blockmax、xmin、ymax、ymin, a rectangle region is determined by this 4 points
Domain scales the coordinate size of spectral diffraction vertical direction y on the basis of this rectangular area, and scaling formula is as follows:
(y1,y2)=(ymax-(ymax-ymin)/a,ymin+(ymax-ymin)/a)
Wherein y1, y2For the coordinate after scaling;A is the scaling multiple of setting, and a cannot be less than 2;
S23: effective image-region is (xmax, y1), (xmin, y1), (xmax, y2), (xmin, y2) this 4 points determinations rectangular area.
3. the image information according to claim 1 for smart phone spectral detection is extracted and calculation method, feature
Be, in the step S03 rgb value be converted into gray value formula it is as follows:
Gray=(Rvalue+Gvalue+Bvalue)/3
Wherein Gray is gray value, Rvalue、Gvalue、BvalueFor the value of each component of R, G, B.
4. the image information according to claim 3 for smart phone spectral detection is extracted and calculation method, feature
It is, the gray value two-dimensional matrix of acquisition is reduced to one-dimensional, the gray value average value of calculating spectral diffraction vertical direction, and gray scale is flat
The calculation formula of mean value is as follows:
Wherein,For average gray, n y1-y2, i y2To y1Between coordinate value;
Gray value-pixel curve graph is drawn with the one-dimensional matrix along spectral diffraction direction being calculated.
5. the image information according to claim 1 for smart phone spectral detection is extracted and calculation method, feature
It is, using gray scale maximum value in the spectrum picture region generated without sample as incident intensity in the step S04, passes through
Gray scale maximum value is as output intensity in the spectrum picture region that sample generates, and gray value of image inverse model calculation formula is such as
Under:
A=lg (1/T)=lg (gray1/gray2)
Wherein, A is absorbance, and T is transmittance, gray1For the spectrum picture area grayscale maximum value generated without sample,
gray2For the spectrum picture area grayscale maximum value generated by sample.
6. the image information according to claim 1 for smart phone spectral detection is extracted and calculation method, feature
It is, according to least square method in the step S04, a linear function curve is fitted, as sample standard curve, standard
Curve equation is as follows:
Y=aX+b
Wherein, Y is sample concentration, and X is the absorbance of sample, and a is the slope fitted, and b is the intercept fitted.
7. a kind of image information for smart phone spectral detection is extracted and computing system characterized by comprising
Spectrum picture processing module, obtains the RGB image of spectrum picture, and by image rotation to unified angle;
Effective image-region extraction module, according to different samples, the effective image-region of selected digital image;
Conversion module extracts the rgb value in selection area, converts gray value for the rgb value in region;
Sample standard curve establishes module, by gray value of image inverse model, calculates the absorbance of sample, is obtained according to test
The absorbance of various concentration standard sample, using sample concentration as abscissa, absorbance is ordinate, draws concentration-absorbance and dissipates
Point diagram establishes sample standard curve, calculates the concentration of actual sample.
8. the image information according to claim 7 for smart phone spectral detection is extracted and computing system, feature
Be, the effective image-region of the selected digital image the following steps are included:
S21: setting is multiple be more than or equal to 2 × 2 color block message, obtained on RGB image and continuously meet the color point of condition
The color block of composition records the location information (x, y) of color block;
S22: union is taken to obtain x the position of all colours blockmax、xmin、ymax、ymin, a rectangle region is determined by this 4 points
Domain scales the coordinate size of spectral diffraction vertical direction y on the basis of this rectangular area, and scaling formula is as follows:
(y1,y2)=(ymax-(ymax-ymin)/a,ymin+(ymax-ymin)/a)
Wherein y1, y2For the coordinate after scaling;A is the scaling multiple of setting, and a cannot be less than 2;
S23: effective image-region is (xmax, y1), (xmin, y1), (xmax, y2), (xmin, y2) this 4 points determinations rectangular area.
9. the image information according to claim 7 for smart phone spectral detection is extracted and computing system, feature
It is, the formula that the rgb value is converted into gray value is as follows:
Gray=(Rvalue+Gvalue+Bvalue)/3
Wherein Gray is gray value, Rvalue、Gvalue、BvalueFor the value of each component of R, G, B.
10. the image information according to claim 9 for smart phone spectral detection is extracted and computing system, feature
It is, the gray value two-dimensional matrix of acquisition is reduced to one-dimensional, the gray value average value of calculating spectral diffraction vertical direction, and gray scale is flat
The calculation formula of mean value is as follows:
Wherein,For average gray, n y1-y2, i y2To y1Between coordinate value;
Gray value-pixel curve graph is drawn with the one-dimensional matrix along spectral diffraction direction being calculated.
Priority Applications (1)
Application Number | Priority Date | Filing Date | Title |
---|---|---|---|
CN201910914772.9A CN110487737B (en) | 2019-09-26 | 2019-09-26 | Image information extraction and calculation method and system for spectrum detection of smart phone |
Applications Claiming Priority (1)
Application Number | Priority Date | Filing Date | Title |
---|---|---|---|
CN201910914772.9A CN110487737B (en) | 2019-09-26 | 2019-09-26 | Image information extraction and calculation method and system for spectrum detection of smart phone |
Publications (2)
Publication Number | Publication Date |
---|---|
CN110487737A true CN110487737A (en) | 2019-11-22 |
CN110487737B CN110487737B (en) | 2020-09-04 |
Family
ID=68544347
Family Applications (1)
Application Number | Title | Priority Date | Filing Date |
---|---|---|---|
CN201910914772.9A Active CN110487737B (en) | 2019-09-26 | 2019-09-26 | Image information extraction and calculation method and system for spectrum detection of smart phone |
Country Status (1)
Country | Link |
---|---|
CN (1) | CN110487737B (en) |
Cited By (6)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN110887761A (en) * | 2019-12-07 | 2020-03-17 | 宁夏大学 | Method and system for measuring surface soil water content |
CN111321078A (en) * | 2020-03-05 | 2020-06-23 | 吉林大学 | Cell culture box, control method thereof and culture dish |
CN111986113A (en) * | 2020-08-20 | 2020-11-24 | 浙江理工大学 | Optical image shadow eliminating method and system |
CN113640225A (en) * | 2021-08-23 | 2021-11-12 | 广西埃索凯新材料科技有限公司 | Sulfuric acid concentration monitoring system applied to manganese sulfate production |
CN116309505A (en) * | 2023-03-28 | 2023-06-23 | 北京理工大学 | Visual image calibration system, method and detection method for hydrogen concentration |
CN117074321A (en) * | 2023-08-15 | 2023-11-17 | 浙江大学 | Method for detecting chemical components of extracting solution based on infrared light information smart phone |
Citations (3)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN202856815U (en) * | 2012-10-18 | 2013-04-03 | 深圳市中达瑞和科技有限公司 | Intelligent handset capable of acquiring high spectral image and spectrums |
CN108051434A (en) * | 2017-12-13 | 2018-05-18 | 深圳市在田翊方科技有限公司 | A kind of prepare liquid concentration quantitative detection method based on color identification |
CN109323999A (en) * | 2018-10-24 | 2019-02-12 | 大连理工大学 | A kind of spectrophotometric detecting method based on image values analysis |
-
2019
- 2019-09-26 CN CN201910914772.9A patent/CN110487737B/en active Active
Patent Citations (3)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN202856815U (en) * | 2012-10-18 | 2013-04-03 | 深圳市中达瑞和科技有限公司 | Intelligent handset capable of acquiring high spectral image and spectrums |
CN108051434A (en) * | 2017-12-13 | 2018-05-18 | 深圳市在田翊方科技有限公司 | A kind of prepare liquid concentration quantitative detection method based on color identification |
CN109323999A (en) * | 2018-10-24 | 2019-02-12 | 大连理工大学 | A kind of spectrophotometric detecting method based on image values analysis |
Non-Patent Citations (2)
Title |
---|
SILVIJA SAFRANKO等: "Designing ColorX, Image Processing Determination of Concentration, To Software for Colorimetric Facilitate Students" Investigation of Analytical Chemistry Concepts Using Digital Imaging Technology", 《JOURNAL OF CHEMICAL EDUCATION》 * |
秦永乐等: "智能手机光谱仪的开发与水中六价铬的定量检测", 《仪表技术与传感器》 * |
Cited By (10)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN110887761A (en) * | 2019-12-07 | 2020-03-17 | 宁夏大学 | Method and system for measuring surface soil water content |
CN111321078A (en) * | 2020-03-05 | 2020-06-23 | 吉林大学 | Cell culture box, control method thereof and culture dish |
CN111321078B (en) * | 2020-03-05 | 2023-12-22 | 吉林大学 | Cell culture box, control method thereof and culture dish |
CN111986113A (en) * | 2020-08-20 | 2020-11-24 | 浙江理工大学 | Optical image shadow eliminating method and system |
CN111986113B (en) * | 2020-08-20 | 2024-03-22 | 浙江理工大学 | Optical image shadow elimination method and system |
CN113640225A (en) * | 2021-08-23 | 2021-11-12 | 广西埃索凯新材料科技有限公司 | Sulfuric acid concentration monitoring system applied to manganese sulfate production |
CN113640225B (en) * | 2021-08-23 | 2024-04-19 | 广西埃索凯新材料科技有限公司 | Sulfuric acid concentration monitoring system applied to manganese sulfate production |
CN116309505A (en) * | 2023-03-28 | 2023-06-23 | 北京理工大学 | Visual image calibration system, method and detection method for hydrogen concentration |
CN116309505B (en) * | 2023-03-28 | 2024-04-05 | 北京理工大学 | Visual image calibration system, method and detection method for hydrogen concentration |
CN117074321A (en) * | 2023-08-15 | 2023-11-17 | 浙江大学 | Method for detecting chemical components of extracting solution based on infrared light information smart phone |
Also Published As
Publication number | Publication date |
---|---|
CN110487737B (en) | 2020-09-04 |
Similar Documents
Publication | Publication Date | Title |
---|---|---|
CN110487737A (en) | Image information for smart phone spectral detection is extracted and calculation method and system | |
Fan et al. | Digital image colorimetry on smartphone for chemical analysis: A review | |
CN106546581B (en) | Test paper detection card intelligent detection system and test paper detection card intelligent analysis method | |
US9506855B2 (en) | Method and system for analyzing a colorimetric assay | |
US20080080766A1 (en) | Apparatus and Method for Analyzing Skin Using L*a*b* Colorspace | |
CN101207832A (en) | Method for checking digital camera color reduction | |
CN103900972B (en) | Multi-feature fusion-based meat freshness hyperspectral image visual detection | |
CN106846295A (en) | The assay method and device of the soil organism | |
TW202103484A (en) | System and method for creation of topical agents with improved image capture | |
CN103308517A (en) | Traditional Chinese medicine color objectification method and traditional Chinese medicine image acquisition device | |
CN105913460A (en) | Skin color detection method and device | |
Yoo et al. | Extraction of colour information from digital images towards cultural heritage characterisation applications | |
Lamb et al. | Digitalization of colourimetric sensor arrays for volatile fatty acid detection in anaerobic digestion | |
EP4343307A1 (en) | Water quality testing method and water quality testing apparatus | |
CN116630148A (en) | Spectral image processing method and device, electronic equipment and storage medium | |
CN112488997B (en) | Method for detecting and evaluating color reproduction of ancient painting printed matter based on characteristic interpolation | |
Khalili Moghaddam et al. | Smartphone-based quantitative measurements on holographic sensors | |
EP3410101B1 (en) | Evaluation device and recording medium storing evaluation program | |
CN103308173A (en) | Color difference measuring method and device | |
US9668653B2 (en) | Quantification of under-eye skin color | |
Hu et al. | Analyzing the color of forensic textile using smartphone-based machine vision | |
Pladellorens et al. | A device for the color measurement and detection of spots on the skin | |
Tonmoy et al. | Error reduction in arsenic detection through color spectrum analysis | |
KR102399939B1 (en) | Detection method and detection pad | |
Syah et al. | The utilization OpenCV to measure the water pollutants concentration |
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 | ||
GR01 | Patent grant | ||
GR01 | Patent grant | ||
TR01 | Transfer of patent right | ||
TR01 | Transfer of patent right |
Effective date of registration: 20221129 Address after: 215000 2F, building 1, No. 100, Guangqi Road, high tech Zone, Suzhou City, Jiangsu Province Patentee after: Suzhou Aopu Smart Core Technology Co.,Ltd. Address before: 215000 building 16, 158 Jinfeng Road, science and Technology City, Suzhou high tech Zone, Jiangsu Province Patentee before: RESEARCH INSTITUTE FOR ENVIRONMENTAL INNOVATION (SUZHOU) TSINGHUA Patentee before: TSINGHUA University |