CN103674864B - A kind of fish water content distribution detection method based on high light spectrum image-forming technology - Google Patents
A kind of fish water content distribution detection method based on high light spectrum image-forming technology Download PDFInfo
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Abstract
The invention discloses a kind of fish water content distribution detection method based on high light spectrum image-forming technology, comprise the following steps: (1) gathers the single band spectrum picture of fish to be measured 12 characteristic wave strong points; Described 12 characteristic wavelengths are respectively 956nm, 1047nm, 1100nm, 1134nm, 1167nm, 1205nm, 1244nm, 1325nm, 1354nm, 1373nm, 1575nm, 1637nm; (2) according to the gray-scale value of single band spectrum picture and the linear relationship of reflectivity, the single band spectrum picture in step (1) is converted into albedo image; (3) the fish moisture in the albedo image of fish corresponding to each pixel is obtained according to formulae discovery.Fish water content distribution detection method provided by the invention, accuracy of detection is high, and detection time is short, not only reduces environmental pollution, also reduces testing cost to a certain extent.
Description
Technical field
The present invention relates to moisture detection field, be specifically related to a kind of fish water content distribution detection method based on high light spectrum image-forming technology.
Background technology
High light spectrum image-forming technology is that spectrum and image processing techniques become one by one, possesses the feature of spectrum and image simultaneously, and detection yardstick can be accurate to nanoscale, owing to possessing these advantages, in prior art, high light spectrum image-forming technology has been widely used in multiple industries such as agricultural, food, petrochemical complex, pharmacy, feed, especially in the quick detect delay of agricultural product life-information, has very large application potential.
Moisture is the important component part of fish, analyzes, can realize the detection of the upgrowth situation of fish and monitor continuously by carrying out detection to fish moisture, significant for the seed output and quality improving fish.
The traditional fish and water point safe standard GB/T 5009.5-2010 of content detection based food carries out, although reliable measurement result can be obtained according to this method, but waste time and energy, and the long-run average of fish moisture can only be obtained, and the distribution situation of fish moisture can not be obtained.
To be the disclosure of the invention of CN101881729A a kind of predicts the method for the rotten moisture of wall pollack fish and protein content for application publication number, comprise the following steps: a-1, utilize near infrared spectrometer to gather the near infrared spectrum reflectivity of the rotten samples of several wall pollack fishes respectively, thus obtain the near infrared spectrum spectrogram of the rotten sample moisture of several wall pollack fishes and protein content respectively; Measure moisture and the protein content of the rotten sample of several wall pollack fishes respectively, thus obtain moisture and the protein content determination value of the rotten sample of several wall pollack fishes respectively; By measured value respectively with corresponding wall pollack the fish rotten moisture of sample and the near infrared spectrum spectrogram matching of protein of NIRCal5.2 near-infrared analysis software by the moisture of rotten for several wall pollack fishes samples and protein content, obtain the typical curve of the rotten moisture of wall pollack fish and protein content; B, utilize near infrared spectrometer to gather the near infrared spectrum reflectivity of wall pollack fish gruel, thus obtain the near infrared spectrum spectrogram of the rotten moisture of wall pollack fish and protein content; The typical curve of c, the rotten moisture of the wall pollack fish obtained by NIRCal5.2 near-infrared analysis software transfer a step and protein content, the rotten moisture of wall pollack fish obtain b step and the near infrared spectrum spectrogram of protein content are analyzed, thus obtain the moisture of wall pollack fish gruel and the predicted value of protein content.
The method utilizing this invention to provide also only can obtain the average content of moisture and protein, and can not obtain distribution, therefore, needs to provide a kind of detection method that can detect fish and water point content distribution fast.
Summary of the invention
The invention provides a kind of fish water content distribution detection method based on high light spectrum image-forming technology, accuracy of detection is high, and detection time is short, not only reduces environmental pollution, also reduces testing cost to a certain extent.
Based on a fish water content distribution detection method for high light spectrum image-forming technology, comprise the following steps:
(1) the single band spectrum picture of fish to be measured 12 characteristic wave strong points is gathered; Described 12 characteristic wavelengths are respectively 956nm, 1047nm, 1100nm, 1134nm, 1167nm, 1205nm, 1244nm, 1325nm, 1354nm, 1373nm, 1575nm, 1637nm;
(2) according to the gray-scale value of single band spectrum picture and the linear relationship of reflectivity, the single band spectrum picture in step (1) is converted into albedo image;
(3) the fish moisture in the albedo image of fish corresponding to each pixel is calculated according to following formula;
Y=108.61X
1+246.267X
2-206.439X
3+172.62X
4-121.423X
5+214.724X
6-136.875X
7+133.606X
8+141.559X
9-214.251X
10+191.275X
11-149.463X
12+65.536
In formula: X
arepresent in the albedo image of anm characteristic wave strong point, the reflectivity of a certain pixel;
Y represents the fish moisture at respective pixel point place.
As preferably, in described step (2), the obtaining step of the gray-scale value of single band spectrum picture and the linear relationship of reflectivity is as follows:
2-1, collection at least three pieces of diffuse reflection on-gauge plates are at the benchmark single band spectrum picture of 12 characteristic wave strong points, ask for the gray-scale value of every width benchmark single band image, within the scope of visible and near infrared spectrum, the diffuse reflection on-gauge plate adopted has mutually different reflectivity;
2-2, for each characteristic wavelength, the gray-scale value of corresponding benchmark single band image and reflectivity are carried out linear fit, obtains the linear relationship of gray-scale value and reflectivity.
As preferably, described diffuse reflection on-gauge plate is three ~ 12 pieces.
In each characteristic wave strong point, every block diffuse reflection on-gauge plate is a corresponding width single band image separately, the corresponding gray-scale value of every width single band image, with the gray-scale value of diffuse reflection on-gauge plate for independent variable, with the reflectivity of diffuse reflection on-gauge plate for dependent variable, linear fit obtains the relation of gray-scale value and reflectivity.
The number of diffuse reflection on-gauge plate is more, the relation of the gray-scale value that linear fit obtains and reflectivity is more accurate, corresponding consuming time also longer, preferably, described diffuse reflection on-gauge plate is three pieces, is respectively 99% diffuse reflection on-gauge plate, 75% diffuse reflection on-gauge plate and 2% diffuse reflection on-gauge plate.
99% diffuse reflection on-gauge plate refers to: within the scope of whole visible and near infrared spectrum, and the reflectivity of diffuse reflection on-gauge plate is 99%.
75% diffuse reflection on-gauge plate refers to: within the scope of whole visible and near infrared spectrum, and the reflectivity of diffuse reflection on-gauge plate is 75%.
2% diffuse reflection on-gauge plate refers to: within the scope of whole visible and near infrared spectrum, and the reflectivity of diffuse reflection on-gauge plate is 2%.
Adopt 99% diffuse reflection on-gauge plate, 75% diffuse reflection on-gauge plate and 2% diffuse reflection on-gauge plate, at utmost cover the scope of reflectivity, make the linear relationship of gray-scale value and the reflectivity obtained more accurate.
In order to know the distributed intelligence of fish moisture intuitively, preferably, in described step (3), after calculating the fish moisture in the albedo image of fish corresponding to each pixel, drawing fish and water and dividing content distribution figure.
Compared with prior art, the present invention has following useful technique effect:
A) gather the high spectrum image of fish at selected a few features wavelength place, utilize multiple linear regression analysis to obtain the relation of pixel reflectivity in fish moisture and high spectrum image, quick and precisely detect fish and water and divide content distribution, save time.
B) not using any chemical material, without the need to carrying out physico-chemical analysis, reducing testing cost, free from environmental pollution.
C) sample of larger-size sample and multi items can be analyzed, content distribution can be divided by real-time online detection fish and water.
D) fish and water point content distribution spectral information characteristics and light spectrum image-forming information feature are merged on characteristic layer, obtain the visual image of fish and water point content distribution, be convenient to further analysis.
Accompanying drawing explanation
Fig. 1 is the reflectivity of three pieces of diffuse reflection on-gauge plates and the graph of a relation of wavelength;
Fig. 2 is the distribution plan of fish moisture.
Embodiment
Embodiment 1
(1) gray-scale value of single band spectrum picture and the relation of reflectivity is set up
1-a, collection three pieces of diffuse reflection on-gauge plates, at the benchmark single band spectrum picture (every block diffuse reflection on-gauge plate gathers a width benchmark single band spectrum picture in each characteristic wave strong point) of 12 characteristic wave strong points, ask for the gray-scale value of every width benchmark single band image.
Within the scope of whole visible and near infrared spectrum, the reflectivity that the diffuse reflection on-gauge plate adopted is corresponding is respectively 99%, 75% and 2%, as shown in Figure 1, three pieces of diffuse reflection on-gauge plate diffuse reflections within the scope of whole visible and near infrared spectrum are mutually different, for each block diffuse reflection on-gauge plate, the reflectivity at all wavelengths place is all identical.
1-b, for each characteristic wavelength, the gray-scale value of corresponding benchmark single band image and reflectivity are carried out linear fit, obtains the linear relationship of gray-scale value and reflectivity.
For each characteristic wavelength, there are three groups of corresponding gray-scale values and reflectance value (each group gray-scale value and reflectivity are obtained by the benchmark single band image of same diffuse reflection on-gauge plate collection), take gray-scale value as independent variable, reflectivity is dependent variable, linear fit is carried out to these three groups of gray-scale values and reflectance value, obtains the linear relationship of gray-scale value and reflectance value.
The distribution of the acquisition of the linear relationship of gray-scale value and reflectance value in the inventive method, the collection of high spectrum image and fish moisture is all completed automatically by ENVI program.
(2) calculate fish and water and divide content distribution
2-a, collection 150 fishes, first adopt high spectrum image imaging system (ImSpectorV10E, SpectralImagingLtd., Oulu, Finland) to scan the single band spectrum picture of every bar fish 12 characteristic wave strong points respectively; 12 characteristic wavelengths are respectively 956nm, 1047nm, 1100nm, 1134nm, 1167nm, 1205nm, 1244nm, 1325nm, 1354nm, 1373nm, 1575nm, 1637nm; The corresponding width single band spectrum picture in each wavelength place, then adopt GB5009.5-2010 national standard method to measure the moisture of 20 zoness of different of these 150 fishes, be cut into 20 parts by every bar fish, all sites of whole piece fish is included in 20 regions.
Random selecting in 150 fishes 100 is as modeling collection sample, and all the other 50 as forecast set.
2-b, the gray-scale value of foundation single band spectrum picture and the linear relationship of reflectivity, be converted into albedo image by every bar fish at the single band spectrum picture of 12 characteristic wave strong points.
Based on the gray-scale value of 12 characteristic wave strong points in step (1) and the relation of reflectivity, can the single band spectrum picture of a fish to be measured (site on the corresponding fish of each pixel difference in single band spectrum picture, each pixel has different gray-scale values) be converted to albedo image, the reflectivity that each pixel in albedo image is corresponding different.
For 100 fishes that modeling is concentrated, high spectrum image for each region can obtain corresponding albedo image, the average reflectance in each region is obtained after average, the fish moisture in each region (GB measures and obtains) and average Reflectance curve fitting is utilized to obtain the relation of fish moisture and average reflectance as shown in the formula shown in (I)
Y’=108.61X’
1+246.267X’
2-206.439X’
3+172.62X’
4-121.423X’
5+
214.724X’
6-136.875X’
7+133.606X’
8+141.559X’
9-214.251X’
10+
191.275X’
11-149.463X’
12+65.536（I）
In formula: X '
arepresent the average reflectance in the albedo image of anm characteristic wave strong point;
Y ' represents the fish moisture at respective pixel point place.
The formula (I) utilizing average reflectance and the matching of fish moisture to obtain have expressed the relation of average reflectance and fish moisture, and formula (I) has also reacted the relation of each pixel place reflectivity and moisture, obtains formula (II) as follows according to formula (I):
Y=108.61X
1+246.267X
2-206.439X
3+172.62X
4-121.423X
5+214.724X
6-136.875X
7+133.606X
8+141.559X
9-214.251X
10+191.275X
11-149.463X
12+65.536（II）
In formula: X
arepresent in the albedo image of anm characteristic wave strong point, the reflectivity of a certain pixel;
Y represents the fish moisture at respective pixel point place.
Reflectivity corresponding to each pixel in albedo image is substituted into the calculating carrying out moisture in formula (II), obtain the moisture at each pixel place in fish diagram picture to be measured, and then draw the moisture distribution plan of fish accordingly, obtain the moisture distributed intelligence at fish each point place, the moisture distribution in a region as shown in Figure 2.
The inventive method is utilized to detect the results contrast of the prediction moisture (substituted into by average reflectance in formula (I) and try to achieve) obtained and the true moisture utilizing GB to detect in table 1 to the fish of 50 in forecast set (corresponding 20 regions of every bar fish).
Table 1
| Data set | Number of samples | Related coefficient | Root-mean-square error |
| Modeling collection | 100 | 0.9348 | 1.5638 |
| Forecast set | 50 | 0.9267 | 1.6246 |
As can be seen from Table 1, the detection method that proposes of the present invention to predict the outcome with the measured value of national standard method be high correlation.
Comparative example 1
Choose 12 characteristic wavelengths, be respectively 952nm, 1049nm, 1102nm, 1130nm, 1162nm, 1208nm, 1248nm, 1320nm, 1350nm, 1378nm, 1570nm, 1630nm, and set up the relation of moisture and reflectivity in the same manner as shown in the formula (III) based on these 12 characteristic wavelengths:
Y=105.025X
1+245.265X
2-204.236X
3+175.145X
4-125.321X
5+216.025X
6-130.126X
7+135.231X
8+145.256X
9-216.124X
10+195.245X
11-145.217X
12+62.327（III）
In formula (III): X
arepresent in the albedo image of anm characteristic wave strong point, the reflectivity of a certain pixel;
Y represents the moisture at respective pixel point place.
Obtain the single band spectrum picture of fish 12 characteristic wave strong points, and calculate the moisture of fish based on formula (III), the Comparative result of the true moisture detected with utilizing national standard method is as shown in table 2.
Table 2
| Data set | Number of samples | Related coefficient | Root-mean-square error |
| Modeling collection | 100 | 0.7563 | 1.9256 |
| Forecast set | 50 | 0.7324 | 1.9904 |
Comparative example 2
Choose 12 characteristic wavelengths, be respectively 953nm, 1048nm, 1108nm, 1137nm, 1169nm, 1204nm, 1246nm, 1329nm, 1358nm, 1370nm, 1576nm, 1638nm, and the relation setting up moisture and reflectivity based on these 12 characteristic wavelengths is in the same manner such as formula shown in (IV):
Y=107.215X
1+244.265X
2-206.206X
3+178.165X
4-127.458X
5+217.865X
6-138.684X
7+138.478X
8+149.176X
9-211.324X
10+197.354X
11-148.841X
12+60.983（IV）
In formula (IV): X
arepresent in the albedo image of anm characteristic wave strong point, the reflectivity of a certain pixel;
Y represents the moisture at respective pixel point place.
Obtain the single band spectrum picture of fish 12 characteristic wave strong points, and calculate the moisture of fish based on formula (IV), the Comparative result of the true moisture detected with utilizing national standard method is as shown in table 3.
Table 3
| Data set | Number of samples | Related coefficient | Root-mean-square error |
| Modeling collection | 100 | 0.6824 | 2.0935 |
| Forecast set | 50 | 0.6597 | 2.2486 |
By the result of embodiment 1 and comparative example 1,2, whether selected characteristic wavelength accurately has material impact for detection fish moisture, the present invention, by choosing suitable characteristic wavelength, obtains the testing result that the coefficient of determination is very high, for carrying out the spatial distribution result of fish moisture fast.
Claims (2)
1. based on a fish water content distribution detection method for high light spectrum image-forming technology, it is characterized in that, comprise the following steps:
(1) the single band spectrum picture of fish to be measured 12 characteristic wave strong points is gathered; Described 12 characteristic wavelengths are respectively 956nm, 1047nm, 1100nm, 1134nm, 1167nm, 1205nm, 1244nm, 1325nm, 1354nm, 1373nm, 1575nm, 1637nm;
(2) according to the gray-scale value of single band spectrum picture and the linear relationship of reflectivity, the single band spectrum picture in step (1) is converted into albedo image;
The obtaining step of the gray-scale value of single band spectrum picture and the linear relationship of reflectivity is as follows:
2-1, collection three pieces of diffuse reflection on-gauge plates are at the benchmark single band spectrum picture of 12 characteristic wave strong points, ask for the gray-scale value of every width benchmark single band image, within the scope of visible and near infrared spectrum, the diffuse reflection on-gauge plate adopted has mutually different reflectivity;
Three pieces of diffuse reflection on-gauge plates are respectively 99% diffuse reflection on-gauge plate, 75% diffuse reflection on-gauge plate and 2% diffuse reflection on-gauge plate;
2-2, for each characteristic wavelength, the gray-scale value of corresponding benchmark single band image and reflectivity are carried out linear fit, obtains the linear relationship of gray-scale value and reflectivity;
(3) the fish moisture in the albedo image of fish corresponding to each pixel is calculated according to following formula;
Y＝108.61X
1+246.267X
2-206.439X
3+172.62X
4-121.423X
5+214.724X
6-136.875X
7+133.606X
8+141.559X
9-214.251X
10+191.275X
11-149.463X
12+65.536
In formula: X
arepresent in the albedo image at character pair wavelength place, the reflectivity of a certain pixel;
Y represents the fish moisture at respective pixel point place.
2. as claimed in claim 1 based on the fish water content distribution detection method of high light spectrum image-forming technology, it is characterized in that, in described step (3), after calculating the fish moisture in the albedo image of fish corresponding to each pixel, draw fish and water and divide content distribution figure.
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