CN110487737A - Image information for smart phone spectral detection is extracted and calculation method and system - Google Patents
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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 invention relates to the technical field of spectrum detection and image processing, in particular to an image information extraction and calculation method and system for spectrum detection of a smart phone.
Background
The spectral analysis can be used for determining the chemical composition and relative content of substances, and has important functions in the fields of food safety, biological safety, environmental monitoring, medical care and the like. Large spectrometers for laboratory use are heavy and expensive and cannot meet the requirements of people for real-time, on-site detection of target samples, and therefore portable spectrometers are constantly being developed. Modern smart phones contain different sensor technologies and can be widely used in various fields as independent measuring instruments. In the spectrum detection, the optical light splitting part can be divided into a mobile phone external device, the mobile phone external device is matched with the mobile phone, a CMOS sensor of the smart phone is used for converting light signals of a transmitted sample into electric signals, the electric signals are read to display an image on a mobile phone screen, and then the mobile phone software with a color quantification model is matched to realize the quantitative analysis of the sample to be detected.
At present, many scholars at home and abroad research color quantification models. Abbasjour et al converted the RGB color values of the image into absorbance, and calculated Fe+2、Fe3+Concentration; onsecu proposed to use the H value in the HSV model to represent color, to detect biomarkers in sweat and saliva; suzuki et al measured Li +, NH4+ and proteins using CIE XYZ chromaticity coordinates. The result shows that the concentration of the object to be tested, which is tested by using the image color information, is similar to the test result of a large instrument, and the feasibility is very strong. However, different color models have different quantization methods for images, and it is necessary to use a specific color model for a substance having a different color reaction, and thus it is difficult to widely use the color model.
Chinese patent document CN 107084790a discloses a spectrum detection method of a portable spectrometer based on a smart phone, which includes: 1) collecting an optical signal to be detected; (2) carrying out collimation shaping and dispersion light splitting on a signal to be measured to form dispersion stripes which are sequentially arranged according to wavelength; (3) shooting the dispersion stripes obtained in the step (2) through a smart phone to form color stripe pictures which are sequentially arranged according to the wavelength; (4) acquiring the RGB value of each pixel position point of the color stripe picture obtained in the step (3), and calculating a light intensity value I corresponding to each pixel position point to obtain an array I (x), wherein x is the coordinate of the picture pixel position point; (5) according to the wavelength-pixel position calibration data lambda (x), replacing x in the array I (x) with corresponding lambda to obtain the corresponding relation I (lambda) of the wavelength and the light intensity, and drawing a spectrum curve corresponding to the data I (lambda) to finish spectrum detection. The above color model is difficult to be widely used. In addition, the image display of different models of mobile phones has difference, the method using pixel fixation can be suitable for the mobile phones of the same model, but the problems of picture information loading failure or overlarge data error and the like may exist when the mobile phones of different models are used. Therefore, it is very important to develop an image information extraction and calculation method applicable to mobile phones of different models.
Disclosure of Invention
In order to solve the technical problems, the invention provides an image information extraction and calculation method and system for spectrum detection of a smart phone, which improve the accuracy of image processing of a spectrometer of the smart phone and the compatibility of APP on various models of mobile phones.
The technical scheme of the invention is as follows:
an image information extraction and calculation method for spectrum detection of a smart phone comprises the following steps:
s01: obtaining RGB images of the spectrum images, and rotating the images to a uniform angle;
s02: selecting an effective image area of the image according to different samples;
s03: extracting RGB values in the selected region, and converting the RGB values in the region into gray values;
s04: calculating the absorbance of the sample through an image gray value inversion model, obtaining the absorbance of standard samples with different concentrations according to the test, drawing a concentration-absorbance scattergram to establish a sample standard curve by taking the concentration of the sample as an abscissa and the absorbance as an ordinate, and calculating the concentration of the actual sample.
In a preferred embodiment, the step S02 of selecting the effective image area of the image includes the following steps:
s21: setting a plurality of pieces of color block information of 2 x 2 or more, acquiring color blocks composed of color points continuously satisfying conditions on an RGB image, and recording position information (x, y) of the color blocks;
s22: the positions of all color blocks are collected to obtain xmax、xmin、ymax、yminAnd determining a rectangular area through the four points, and scaling the coordinate size of the vertical direction y of the spectral diffraction on the basis of the rectangular area, wherein the scaling formula is as follows:
(y1,y2)＝(ymax-(ymax-ymin)/a,ymin+(ymax-ymin)/a)
wherein y is1，y2The scaled coordinates; a is a set zoom multiple, and a cannot be smaller than 2;
s23: the effective image area is (x)max，y1)，(xmin，y1)，(xmax，y2)，(xmin，y2) These four points define a rectangular area.
In a preferred technical solution, the formula for converting the RGB values into the gray-scale values in step S03 is as follows:
Gray＝(Rvalue+Gvalue+Bvalue)/3
wherein Gray is the Gray value, Rvalue、Gvalue、BvalueR, G, B values for each component;
in the preferred technical scheme, the obtained gray value two-dimensional matrix is reduced to one dimension, and the gray value average value in the vertical direction of the spectrum diffraction is calculated, wherein the calculation formula of the gray value average value is as follows:
wherein,is a gray average value, n is y1-y2I is y2To y1Coordinate values therebetween;
and drawing a gray value-pixel curve graph by using the calculated one-dimensional matrix along the spectral diffraction direction.
In a preferred technical solution, in step S04, the maximum gray value in the spectral image region generated without passing through the sample is used as the incident light intensity, the maximum gray value in the spectral image region generated with passing through the sample is used as the emergent light intensity, and the image gray value inversion model has the following calculation formula:
A＝lg(1/T)＝lg(gray1/gray2)
wherein A is absorbance, T is transmittance, gray1Gray for spectral image area intensity maximum generated without passing through the sample2The spectral image area gray scale maximum generated for the passing sample.
In a preferred technical solution, in the step S04, a linear function curve is fitted according to a least square method, and is used as a sample standard curve, where the standard curve formula is as follows:
Y＝aX+b
wherein Y is the sample concentration, X is the absorbance of the sample, a is the fitted slope, and b is the fitted intercept.
The invention also discloses an image information extraction and calculation system for the spectrum detection of the smart phone, which comprises the following steps:
the spectral image processing module is used for obtaining RGB images of the spectral images and rotating the images to a uniform angle;
the effective image area extraction module is used for selecting an effective image area of an image according to different samples;
the conversion module is used for extracting the RGB values in the selected area and converting the RGB values in the area into gray values;
and the sample standard curve establishing module is used for calculating the absorbance of the sample through the image gray value inversion model, obtaining the absorbance of standard samples with different concentrations according to the test, drawing a concentration-absorbance scattergram by taking the concentration of the sample as a horizontal coordinate and the absorbance as a vertical coordinate to establish a sample standard curve, and calculating the concentration of the actual sample.
In a preferred embodiment, the selecting the effective image area of the image includes the steps of:
s21: setting a plurality of pieces of color block information of 2 x 2 or more, acquiring color blocks composed of color points continuously satisfying conditions on an RGB image, and recording position information (x, y) of the color blocks;
s22: the positions of all color blocks are collected to obtain xmax、xmin、ymax、yminAnd determining a rectangular area through the four points, and scaling the coordinate size of the vertical direction y of the spectral diffraction on the basis of the rectangular area, wherein the scaling formula is as follows:
(y1,y2)＝(ymax-(ymax-ymin)/a,ymin+(ymax-ymin)/a)
wherein y is1，y2The scaled coordinates; a is a set zoom multiple, and a cannot be smaller than 2;
s23: the effective image area is (x)max，y1)，(xmin，y1)，(xmax，y2)，(xmin，y2) These four points define a rectangular area.
In a preferred technical solution, the formula for converting the RGB values into the gray-scale values is as follows:
Gray＝(Rvalue+Gvalue+Bvalue)/3
wherein Gray is the Gray value, Rvalue、Gvalue、BvalueR, G, B values for each component;
in the preferred technical scheme, the obtained gray value two-dimensional matrix is reduced to one dimension, and the gray value average value in the vertical direction of the spectrum diffraction is calculated, wherein the calculation formula of the gray value average value is as follows:
wherein,is a gray average value, n is y1-y2I is y2To y1Coordinate values therebetween;
and drawing a gray value-pixel curve graph by using the calculated one-dimensional matrix along the spectral diffraction direction.
Compared with the prior art, the invention has the advantages that:
according to the invention, the spectral image area required to be used is selected according to different substances to be detected, so that the calculation amount of the mobile phone can be reduced, the operation speed of the APP can be optimized, and the accuracy of data in the subsequent calculation process can be improved. The invention is widely applicable to samples which can be tested by a spectrophotometry method and is applicable to various types of smart phones, and the algorithm is simple to operate and high in accuracy.
Drawings
The invention is further described with reference to the following figures and examples:
FIG. 1 is a flow chart of an image information extraction and calculation method for smart phone spectrum detection according to the present invention;
FIG. 2 is a block diagram of a selected active image area;
FIG. 3 is a gray value-pixel plot;
FIG. 4 is a gray value curve of ammonia nitrogen standard samples with different concentrations;
FIG. 5 is a standard curve of ammonia nitrogen.
Detailed Description
In order to make the objects, technical solutions and advantages of the present invention more apparent, the present invention will be described in further detail with reference to the accompanying drawings in conjunction with the following detailed description. It should be understood that the description is intended to be exemplary only, and is not intended to limit the scope of the present invention. Moreover, in the following description, descriptions of well-known structures and techniques are omitted so as to not unnecessarily obscure the concepts of the present invention.
Example (b):
the preferred embodiments of the present invention will be further described with reference to the accompanying drawings.
This example takes ammonia nitrogen test as an example.
As shown in figure 1, the algorithm of the invention is simple to operate and has high accuracy, a commonly configured mobile phone can operate, and the algorithm can also be used as PAD (PAD application program) and other terminal equipment. The method specifically comprises the following steps:
1) projecting an image shot by a mobile phone onto a two-dimensional canvas to obtain an RGB image;
2) the image rotation angle information is called from a mobile phone camera, and the RGB image on the canvas is rotated to a uniformly set angle;
3) the spectral image regions to be used are selected according to different substances to be detected, so that the calculation amount of the mobile phone can be reduced, the operation speed of the APP can be optimized, and the accuracy of data in the subsequent calculation process can be improved. The core of the process is that a tracking.js database is used, the position of a color block on the whole image is judged on the basis of the set color block parameters, and the specific color block parameters can be set through a configuration file;
3.1) the profile sets a plurality of pieces of color block information (RGB values) of 2 × 2 or more, acquires color blocks composed of color points satisfying the conditions continuously on an RGB image, and records positional information (x, y) of the color blocks, where x is a spectral diffraction direction coordinate and y is a spectral diffraction vertical direction coordinate. The positions of the color blocks are collected to obtain xmax、xmin、ymax、yminAnd a rectangular area can be determined through the four points, and the size of the coordinate perpendicular to the spectrum diffraction direction is scaled on the basis of the rectangular area, so that the calculation error caused by the difference between the two sides and the middle part of the spectrum image is reduced. The specific scaling formula is as follows:
(y1,y2)＝(ymax-(ymax-ymin)/a,ymin+(ymax-ymin)/a)
wherein y is1，y2The scaled coordinates; a is a zoom factor set according to specific conditions, the smaller a is, the larger a is, the smaller a is, and a cannot be smaller than 2;
3.2)(xmax，y1)，(xmin，y1)，(xmax，y2)，(xmin，y2) Four vertices of the rectangular image area that eventually participate in the computation, as shown in fig. 2.
4) Converting the image information obtained in the step (3) into digital information;
4.1) extracting the RGB value of the effective image area, and converting the RGB value in the area into a gray value. The method selects an average value algorithm with the best effect after an attempt, and a specific formula for converting RGB into gray value is as follows:
Gray＝(Rvalue+Gvalue+Bvalue)/3
wherein Gray is the Gray value, Rvalue、Gvalue、BvalueR, G, B for each component.
4.2) reducing the obtained gray value two-dimensional matrix into one dimension, calculating the gray value average value in the vertical direction of the spectrum diffraction, wherein y is the coordinate vertical to the spectrum diffraction direction, and the specific calculation formula of the gray value average value is as follows:
wherein,is a gray average value, n is y1-y2I is y2To y1Coordinate values therebetween;
making a gray value-pixel curve graph by using the calculated one-dimensional matrix along the spectral diffraction direction, wherein the curve graph comprises a gray average value in the selected graph range as shown in fig. 3;
5) establishing a sample standard curve by using an image gray value inversion model;
5.1) simulating Lambert-beer law by using an image gray value inversion model, wherein in order to maximize a signal response value, the maximum gray value in a spectral image region which is not subjected to sample generation is used as incident light intensity, the maximum gray value in the spectral image region which is subjected to sample generation is used as emergent light intensity, and a model calculation formula is as follows:
A＝lg(1/T)＝lg(gray1/gray2)
wherein A is absorbance, T is transmittance, gray1Gray for spectral image area intensity maximum generated without passing through the sample2The maximum value of the gray scale of the spectral image area generated by the sample;
5.2) the absorbance of the standard samples with different concentrations is measured, as shown in FIG. 4, wherein the black box is the effective area selected by the frame, I0 is the gray scale value curve of the spectral image generated without passing through the sample, and 0-2 is the gray scale value curve of the spectral image generated with passing through the standard samples with different concentrations.
Taking the sample concentration as the abscissa and the absorbance as the ordinate, a concentration-absorbance scattergram is made, and a linear function curve, which is the standard curve of the sample, is fitted according to the least square method, as shown in fig. 5. The standard curve formula is as follows:
Y＝aX+b
wherein Y is the concentration of the sample, X is the absorbance of the sample, a is the fitted slope, and b is the fitted intercept;
substituting the absorbance value of the actual sample obtained by the test into the standard curve to calculate the concentration of the actual sample.
It is to be understood that the above-described embodiments of the present invention are merely illustrative of or explaining the principles of the invention and are not to be construed as limiting the invention. Therefore, any modification, equivalent replacement, improvement and the like made without departing from the spirit and scope of the present invention should be included in the protection scope of the present invention. Further, it is intended that the appended claims cover all such variations and modifications as fall within the scope and boundaries of the appended claims or the equivalents of such scope and boundaries.
Claims (10)
1. An image information extraction and calculation method for spectrum detection of a smart phone is characterized by comprising the following steps:
s01: obtaining RGB images of the spectrum images, and rotating the images to a uniform angle;
s02: selecting an effective image area of the image according to different samples;
s03: extracting RGB values in the selected region, and converting the RGB values in the region into gray values;
s04: calculating the absorbance of the sample through an image gray value inversion model, obtaining the absorbance of standard samples with different concentrations according to the test, drawing a concentration-absorbance scattergram to establish a sample standard curve by taking the concentration of the sample as an abscissa and the absorbance as an ordinate, and calculating the concentration of the actual sample.
2. The image information extraction and calculation method for smartphone spectrum detection according to claim 1, wherein the step S02 of selecting the effective image area of the image includes the following steps:
s21: setting a plurality of pieces of color block information of 2 x 2 or more, acquiring color blocks composed of color points continuously satisfying conditions on an RGB image, and recording position information (x, y) of the color blocks;
s22: the positions of all color blocks are collected to obtain xmax、xmin、ymax、yminAnd determining a rectangular area through the four points, and scaling the coordinate size of the vertical direction y of the spectral diffraction on the basis of the rectangular area, wherein the scaling formula is as follows:
(y1,y2)＝(ymax-(ymax-ymin)/a,ymin+(ymax-ymin)/a)
wherein y is1，y2The scaled coordinates; a is a set zoom multiple, and a cannot be smaller than 2;
s23: the effective image area is (x)max，y1)，(xmin，y1)，(xmax，y2)，(xmin，y2) These four points define a rectangular area.
3. The method for extracting and calculating image information for smartphone spectrum detection according to claim 1, wherein the formula for converting RGB values into grayscale values in step S03 is as follows:
Gray＝(Rvalue+Gvalue+Bvalue)/3
wherein Gray is the Gray value, Rvalue、Gvalue、BvalueR, G, B for each component.
4. The image information extraction and calculation method for smartphone spectrum detection according to claim 3, wherein the obtained two-dimensional matrix of gray values is reduced to one dimension, and the average value of gray values in the vertical direction of spectrum diffraction is calculated, wherein the calculation formula of the average value of gray values is as follows:
wherein,is a gray average value, n is y1-y2I is y2To y1Coordinate values therebetween;
and drawing a gray value-pixel curve graph by using the calculated one-dimensional matrix along the spectral diffraction direction.
5. The image information extraction and calculation method for smartphone spectrum detection according to claim 1, wherein in step S04, the maximum grayscale value in the spectral image region that is not generated by the sample is used as the incident light intensity, the maximum grayscale value in the spectral image region that is generated by the sample is used as the emergent light intensity, and the image grayscale value inversion model calculation formula is as follows:
A＝lg(1/T)＝lg(gray1/gray2)
wherein A is absorbance, T is transmittance, gray1Gray for spectral image area intensity maximum generated without passing through the sample2The spectral image area gray scale maximum generated for the passing sample.
6. The method for extracting and calculating image information for smartphone spectrum detection according to claim 1, wherein a linear function curve is fitted in step S04 according to a least square method, and is used as a sample standard curve, and the standard curve formula is as follows:
Y＝aX+b
wherein Y is the sample concentration, X is the absorbance of the sample, a is the fitted slope, and b is the fitted intercept.
7. An image information extraction and calculation system for smartphone spectrum detection, comprising:
the spectral image processing module is used for obtaining RGB images of the spectral images and rotating the images to a uniform angle;
the effective image area extraction module is used for selecting an effective image area of an image according to different samples;
the conversion module is used for extracting the RGB values in the selected area and converting the RGB values in the area into gray values;
and the sample standard curve establishing module is used for calculating the absorbance of the sample through the image gray value inversion model, obtaining the absorbance of standard samples with different concentrations according to the test, drawing a concentration-absorbance scattergram by taking the concentration of the sample as a horizontal coordinate and the absorbance as a vertical coordinate to establish a sample standard curve, and calculating the concentration of the actual sample.
8. The image information extraction and calculation system for smartphone spectral detection according to claim 7, wherein the active image area of the selected image includes the steps of:
s21: setting a plurality of pieces of color block information of 2 x 2 or more, acquiring color blocks composed of color points continuously satisfying conditions on an RGB image, and recording position information (x, y) of the color blocks;
s22: the positions of all color blocks are collected to obtain xmax、xmin、ymax、yminAnd determining a rectangular area through the four points, and scaling the coordinate size of the vertical direction y of the spectral diffraction on the basis of the rectangular area, wherein the scaling formula is as follows:
(y1,y2)＝(ymax-(ymax-ymin)/a,ymin+(ymax-ymin)/a)
wherein y is1，y2The scaled coordinates; a is a set zoom multiple, and a cannot be smaller than 2;
s23: the effective image area is (x)max，y1)，(xmin，y1)，(xmax，y2)，(xmin，y2) These four points define a rectangular area.
9. The system for extracting and calculating image information for smartphone spectrum detection according to claim 7, wherein the formula for converting the RGB values into grayscale values is as follows:
Gray＝(Rvalue+Gvalue+Bvalue)/3
wherein Gray is the Gray value, Rvalue、Gvalue、BvalueR, G, B for each component.
10. The system for extracting and calculating image information for smartphone spectrum detection according to claim 9, wherein the obtained two-dimensional matrix of gray values is reduced to one dimension, and the average value of gray values in the vertical direction of spectrum diffraction is calculated, wherein the calculation formula of the average value of gray values is as follows:
wherein,is a gray average value, n is y1-y2I is y2To y1Coordinate values therebetween;
and drawing a gray value-pixel curve graph by using the calculated one-dimensional matrix along the spectral diffraction direction.
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