CN113222925A - ImagePy-based water-sensitive paper fog drop parameter measuring device and measuring method thereof - Google Patents
ImagePy-based water-sensitive paper fog drop parameter measuring device and measuring method thereof Download PDFInfo
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Abstract
A water-sensitive paper fog droplet parameter measuring device based on ImagePy and a measuring method thereof comprise a water-sensitive paper image acquisition module, an image processing module and a fog droplet parameter statistical module; the image processing module comprises an image automatic rotating and cutting module based on ImagePy, an image splicing module and a color image segmentation module; and the fog drop parameter statistic module comprises six parameters of a maximum value, a minimum value, an average value, a median value, a fog drop coverage rate and a fog drop number. The fog drop coverage rate and the fog drop median function are added on the basis of the original function of ImagePy by writing a program; automatically cutting the water-sensitive paper image in a rotating manner through an image acquisition module and image processing software ImagePy, then carrying out image splicing and color image segmentation on the water-sensitive paper image, and further carrying out statistics on fog drop parameters such as the size of fog drops, the total fog drop number, the fog drop coverage rate and the like by using a fog drop parameter statistics module; the invention has the advantages of simple structure, convenient operation, accurate and quick measurement and wide application prospect.
Description
Technical Field
The invention relates to the technical field of image processing, in particular to a device and a method for measuring fog drop parameters of water-sensitive paper based on ImagePy.
Background
The pesticide has the characteristics of low cost, effectiveness and rapidness in the aspect of controlling crop diseases and insect pests, and is the most powerful method for controlling the crop diseases and insect pests. However, the pesticide is wasted due to a large amount of spraying, and the environment and the health of people are seriously harmed. Therefore, how to improve the utilization rate of the pesticide and reduce the using amount of the pesticide becomes an urgent problem to be solved. The information such as the spray amount of the deposited fog drops on the target, the size of the fog drops, the coverage uniformity of the fog drops on the target and the like after the pesticide is applied can be quickly and effectively obtained, the pesticide application effect can be quantitatively evaluated, and a reference is provided for further optimizing the pesticide spraying technology.
At present, various water-Sensitive test paper image processing software is developed abroad, wherein R.D.Fox provides a result of a WSP (Water Sensitive paper) visual grading spray covering method; pannton developed a camera/illumination system that measures the percentage of spot coverage on a WSP; cunha M evaluated the ability of several water-sensitive paper image processing software to analyze spray quality; zhu Heping developed a portable fog drop parameter measurement system based on a PC and a scanner. Although the start is late in China, a good research result is obtained, and Guo Na, Wu Asia base, Qili jun, Qibaijing, Zheng strengthening, Jiang Tao, Chun Jiang, Lianping and the like research fog drop detection methods based on image processing, when a digital image of the water-sensitive paper is obtained, the water-sensitive paper image is inclined, the software cannot automatically detect the inclination angle of the water-sensitive paper, the automatic rotation operation of the water-sensitive paper image is lacked, the region of interest of the water-sensitive paper cannot be automatically obtained, the preprocessing operation of the water-sensitive paper needs to be performed by other software, and meanwhile, when the water-sensitive paper image is segmented, the water-sensitive paper is converted into a gray image and then segmented, so that some useful information is lost in the conversion process, and the detection accuracy is not high.
Disclosure of Invention
In order to overcome the defects in the prior art, the invention aims to provide a device and a method for measuring fog drop parameters of water-sensitive paper based on ImagePy.
In order to achieve the purpose, the invention adopts the technical scheme that:
a water-sensitive paper fog droplet parameter measuring device based on ImagePy comprises a water-sensitive paper image acquisition module, an image processing module and a fog droplet parameter statistical module;
the image processing module comprises an image automatic rotating and cutting module based on ImagePy, an image splicing module and a color image segmentation module;
the fog drop parameter statistic module comprises fog drop maximum value, minimum value, average value, median, fog drop coverage rate and fog drop number parameter statistics; wherein, the fog drop coverage rate and the fog drop median function are added on the basis of the original function of ImagePy by writing a program.
The image automatic rotary cutting module realizes automatic rotary cutting of the water-sensitive paper image through a minimum external rectangular function (minAreaRect) and a vertical boundary minimum positive rectangular function (bounding) and comprises a cutting module, a cutting module and a cutting module, wherein the cutting module is used for cutting the water-sensitive paper image; and obtaining a minimum positive rectangle wrapping the outline of the water-sensitive paper image by using boundingRect (), and obtaining a minimum oblique rectangle wrapping the outline of the water-sensitive paper image by using minAreaRect ().
The image splicing module defines img _ center as a middle 1/2 area, img [1] as a left 1/4 area, img [2] as a right 1/4 area and img [3] as an image spliced by the img [1] and the img [2] by programming for the water-sensitive paper acquired by the water-sensitive paper image acquisition module, and outputs the img [3] and the img _ center.
The color image segmentation module adopts an RGB color space model.
A measuring method of a water-sensitive paper fog droplet parameter measuring device based on ImagePy specifically comprises the following steps:
step one, acquiring a water-sensitive paper image:
1) winding and fixing the water-sensitive paper on a vertical rod which is at the same height and level with the wheat seedlings to form a cylinder, wherein an 1/2 area in the middle of the water-sensitive paper faces the direction of spraying pesticides on agricultural machinery, and a 1/4 area on the left side and a 1/4 area on the right side of the water-sensitive paper are adhered together and are places where the agricultural machinery cannot directly spray, namely the back side;
2) by changing the type of a nozzle for spraying the pesticide and the spraying pressure, the agricultural machine carrying the pesticide respectively carries out multiple spraying experiments in the test wheat field, and multiple pieces of water-sensitive paper with sequential numbers can be obtained at different positions driven by the agricultural machine in each spraying experiment;
3) pasting the water-sensitive paper obtained in the last step on the same paper, and acquiring a group of experimentally collected water-sensitive paper images through an image acquisition module;
step two, the water sensitive paper image processing process:
1) collecting the water-sensitive paper image obtained in the step 3) by using an image collection module, importing the water-sensitive paper image into a computer, and opening the water-sensitive paper image to be processed by using ImagePy software;
2) firstly, graying, binaryzation, negation, corrosion and filtering operations are carried out on the water-sensitive paper image by ImagePy software, interference of useless information is eliminated, then area analysis operation is carried out, area screening is carried out on the water-sensitive paper image, and noise which does not belong to the water-sensitive paper is filtered by an area threshold value; because each water-sensitive paper image is of a fixed size, the value is taken as a threshold value, if the value is smaller than the threshold value, the water-sensitive paper image is determined to be unnecessary noise, and the noise is filtered out, so that an area only containing the water-sensitive paper image is obtained;
3) through the automatic rotary cutting module of the water-sensitive paper image, with the help of a minimum external rectangular function (minAreaRect) and a perpendicular boundary minimum positive rectangular function (boundingRect), the automatic rotary cutting of the water-sensitive paper image area obtained in the step 2) is realized: determining the angle of the water-sensitive paper image needing to be rotated by adopting a minimum circumscribed rectangular function (minAreaRect), and realizing rotation to enable the inclined water-sensitive paper image to be corrected; obtaining an interested area by adopting a smallest bounding rectangle function (bounding rectangle) to realize cutting of the water-sensitive paper area;
4) according to the real situation of pesticide spraying in the field, an image splicing module named montage img is added into open source software ImagePy image processing software, collected water-sensitive paper images are cut into a left 1/4 area, a middle 1/2 area and a right 1/4 area of the images, and then the left 1/4 and the right 1/4 are spliced together to serve as the back of crops;
5) the water-sensitive paper image is further segmented by a color image segmentation module by adopting a color image segmentation method, and threshold values of R, G, B colors are set: r, G, B, setting a threshold value according to the color, and displaying an area in which the RGB three-channel color value in the image is smaller than the threshold value, namely a fog drop area, as white, and other areas, namely a background, as black according to the set threshold value, so as to obtain the required fog drop area;
step three, a droplet parameter measuring method:
counting fog drop parameters of the water-sensitive paper image obtained in the second step and the 5) through a fog drop parameter counting module, wherein the fog drop parameters comprise the maximum value, the minimum value, the average value, the median value, the fog drop coverage rate and the fog drop number parameter; wherein, the fog drop coverage rate and the fog drop median function are added on the basis of the original function of ImagePy by writing a program: writing a fog drop coverage program according to a formula (1); the fog drop median program calculates according to the odd number and the even number of the fog drop number, all the numbers are sorted from small to large, if the numbers are odd, the median value is directly taken, and if the numbers are even, the two numbers positioned in the middle are added and divided by 2 to obtain the median value; automatic statistics of fog droplet parameters can be realized in ImagePy software;
the droplet coverage was calculated as the percentage of the droplet coverage area to the total area of the statistic:
in the formula: c is the fog drop coverage rate; a. thesThe number of pixels in a fog drop area is shown; a. thepThe total pixel number of the test paper area is shown.
The area threshold value in the second step 2) is 1000000.
Compared with the prior art, the invention has the beneficial effects that:
the device integrates an image acquisition module and image processing software ImagePy, the software is composed of a set of self-defined modules, automatic detection and rotation can be carried out on a water-sensitive paper image, then color image segmentation is carried out on the water-sensitive paper image, and then the modules are used for counting and measuring fog drop parameters such as fog drop size, total fog drop number and fog drop coverage rate, so that the problems that the existing water-sensitive paper image processing software lacks preprocessing operations such as rotation of the water-sensitive paper image and the detection precision is low due to the fact that the water-sensitive paper image is firstly converted into a gray image and then segmented are solved; the method can accurately and quickly count and measure the fog drop parameters, and provides a theoretical basis for researching the model of the agricultural mechanical nozzle and the influence of the spraying pressure on the pesticide spraying system.
Drawings
FIG. 1 is a flow chart of the water-sensitive paper image processing of the present invention.
FIG. 2 is a schematic diagram of the automatic rotary cutting of water-sensitive paper images according to the present invention.
FIG. 3 is a block diagram of the water-sensitive paper image stitching process of the present invention.
FIG. 4 is a diagram showing the cutting and splicing results of the water-sensitive paper of the present invention.
Fig. 5 is a droplet parameter dialog of the present invention.
FIG. 6 is a schematic view showing the fixing of the water-sensitive paper in the experiment of the present invention.
FIG. 7 is a schematic view of the operation of the agricultural machine during the experiment of the present invention.
Detailed Description
The invention is explained in more detail below with reference to the figures and examples:
referring to fig. 1, a device for measuring fog drop parameters of water-sensitive paper based on ImagePy comprises a water-sensitive paper image acquisition module, an image processing module and a fog drop parameter statistic module;
the image acquisition module adopts a scanner.
The image processing module comprises an image automatic rotating and cutting module based on ImagePy, an image splicing module and a color image segmentation module;
the fog drop parameter statistic module comprises fog drop maximum value, minimum value, average value, median, fog drop coverage rate and fog drop number parameter statistics; wherein, the fog drop coverage rate and the fog drop median function are added on the basis of the original function of ImagePy by writing a program.
The ImagePy software is an extensible image processing framework written by Python language; and the user carries out secondary development of the software according to the requirement, writes and names a corresponding function script, runs the software, and generates a corresponding plug-in after being loaded by a loader.
Referring to fig. 2, the image automatic rotation cropping module implements automatic rotation cropping of the water-sensitive paper image through a minimum circumscribed rectangle function (minAreaRect) and a vertical boundary minimum positive rectangle function (bounding rectangle); and obtaining a minimum positive rectangle wrapping the outline of the water-sensitive paper image by using boundingRect (), and obtaining a minimum oblique rectangle wrapping the outline of the water-sensitive paper image by using minAreaRect ().
Referring to fig. 3 and 4, the image stitching module defines img _ center as a middle 1/2 area, img [1] as a left 1/4 area, img [2] as a right 1/4 area, and img [3] as an image in which img [1] and img [2] are stitched, and outputs img [3] and img _ center, for the collected water-sensitive paper.
Referring to fig. 5, the droplet parameter statistics module is to program a program for calculating droplet coverage and a droplet size intermediate value on the basis of ImagePy, and after image processing is completed, statistically measure various parameters of the droplets, including statistics of a droplet maximum value, a minimum value, an average value, a median value, a droplet coverage and a droplet number. The color image segmentation plug-in adopts an RGB color space model.
A measuring method of a water-sensitive paper fog droplet parameter measuring device based on ImagePy specifically comprises the following steps:
step one, acquiring a water-sensitive paper image:
1) winding and fixing the water-sensitive paper on a vertical rod which is at the same height and level with the wheat seedlings to form a cylinder, wherein an 1/2 area in the middle of the water-sensitive paper faces the direction of spraying pesticides on agricultural machinery, and a left 1/4 area and a right 1/4 area of the water-sensitive paper are adhered together and are places where the agricultural machinery cannot directly spray, namely the back, as shown in fig. 6;
2) by changing the type of a nozzle for spraying the pesticide and the spraying pressure, the agricultural machine carrying the pesticide carries out 15 spraying experiments in the test wheat field according to the experimental requirements, and four pieces of water-sensitive paper with the sequential reference number of A, B, C, D can be obtained at different positions driven by the agricultural machine in each spraying experiment, as shown in figure 7;
3) pasting the water-sensitive paper obtained in the last step on the same paper, and acquiring a group of experimentally collected water-sensitive paper images through an image acquisition module;
step two, the water sensitive paper image processing process:
1) collecting the water-sensitive paper image obtained in the step 3) by using an image collection module, importing the water-sensitive paper image into a computer, and opening the water-sensitive paper image to be processed by using ImagePy software;
2) firstly, graying, binaryzation, negation, corrosion and filtering operations are carried out on the water-sensitive paper image by ImagePy software, interference of useless information is eliminated, then area analysis operation is carried out, area screening is carried out on the water-sensitive paper image, and noise which does not belong to the water-sensitive paper is filtered by an area threshold value; because each water-sensitive paper image is of a fixed size, the value is taken as a threshold value, if the value is smaller than the threshold value, the water-sensitive paper image is determined to be unnecessary noise, and the noise is filtered out, so that an area only containing the water-sensitive paper image is obtained;
3) through the automatic rotary cutting module of the water-sensitive paper image, with the help of a minimum external rectangular function (minAreaRect) and a perpendicular boundary minimum positive rectangular function (boundingRect), the automatic rotary cutting of the area of the water-sensitive paper image obtained in the step 2) is realized: determining the angle of the water-sensitive paper image needing to be rotated by adopting a minimum circumscribed rectangular function (minAreaRect), and realizing rotation to enable the inclined water-sensitive paper image to be corrected; obtaining an interested area by adopting a smallest bounding rectangle function (bounding rectangle) to realize cutting of the water-sensitive paper area;
4) according to the real situation of pesticide spraying in the field, an image splicing module named montage img is added in an open source software ImagePy image processing module, collected water-sensitive paper images are cut into a left 1/4 area, a middle 1/2 area and a right 1/4 area of the images, and then the left 1/4 and the right 1/4 are spliced together to serve as the back of crops;
5) the water-sensitive paper image is further segmented by a color image segmentation module by adopting a color image segmentation method, and threshold values of R, G, B colors are set: r, G, B, setting a threshold value according to the color, and displaying an area in which the RGB three-channel color value in the image is smaller than the threshold value, namely a fog drop area, as white, and other areas, namely a background, as black according to the set threshold value, so as to obtain the required fog drop area;
step three, a droplet parameter measuring method:
counting fog drop parameters of the water-sensitive paper image obtained in the second step and the 5) through a fog drop parameter counting module, wherein the fog drop parameters comprise the maximum value, the minimum value, the average value, the median value, the fog drop coverage rate and the fog drop number; wherein, the fog drop coverage rate and the fog drop median function are added on the basis of the original function of ImagePy by writing a program: the fog drop coverage rate program is written according to a formula (1), the fog drop median program is calculated according to the odd number and the even number of the fog drop numbers, all the numbers are sequenced from small to large, if the numbers are odd numbers, the median value is directly taken, and if the numbers are even numbers, the median value is obtained by dividing the sum of the two numbers positioned in the middle by 2; the two functions are loaded into software, so that automatic statistics of fog drop parameters can be realized in ImagePy software;
the droplet coverage was calculated as the percentage of the droplet coverage area to the total area of the statistic:
in the formula: c is the fog drop coverage rate; a. thesThe number of pixels in a fog drop area is shown; a. thepThe total pixel number of the test paper area is shown.
The area threshold value in the second step 2) is 1000000.
The water-sensitive paper (WSP) is a simple mechanical method providing rapid assessment of spray coverage, is a yellow-surfaced coated paper that turns dark blue upon contact with liquid droplets, has the characteristics of significant color development, and is easy for image processing and storage, and is currently the most commonly used collector for mist droplets. The water sensitive paper can be used to check the droplet distribution, the density of the spray and the droplet size.
The image acquisition module adopts a scanner, the model of the scanner is preferably Epson DS-570w, the scanning breadth is A4 paper size, the scanning speed is 35 pages/70 surfaces per minute, and the WIFI function is supported; the scanner is connected with a computer, four pieces of water-sensitive paper are pasted on the same A4 paper, and the scanner scans to obtain the water-sensitive paper image collected in one experiment.
The working principle of the invention is as follows:
the method comprises the steps of automatically rotating and cutting a water-sensitive paper image through an image acquisition module and image processing software ImagePy, then carrying out image splicing and color image segmentation on the water-sensitive paper image, and further carrying out statistics on fog drop parameters such as the size of fog drops, the total fog drop number, the fog drop coverage rate and the like by using a fog drop parameter statistics module.
Claims (7)
1. A water-sensitive paper fog droplet parameter measuring device based on ImagePy comprises a water-sensitive paper image acquisition module, an image processing module and a fog droplet parameter statistical module;
the image processing module comprises an image automatic rotating and cutting module based on ImagePy, an image splicing module and a color image segmentation module;
the fog drop parameter statistic module comprises fog drop maximum value, minimum value, average value, median, fog drop coverage rate and fog drop number parameter statistics; wherein, the fog drop coverage rate and the fog drop median function are added on the basis of the original function of ImagePy by writing a program.
2. The ImagePy-based water-sensitive paper droplet parameter measuring device of claim 1, wherein: the image automatic rotary cutting module realizes automatic rotary cutting of the water-sensitive paper image through a minimum external rectangular function (minAreaRect) and a vertical boundary minimum positive rectangular function (bounding) and comprises a cutting module, a cutting module and a cutting module, wherein the cutting module is used for cutting the water-sensitive paper image; and obtaining a minimum positive rectangle wrapping the outline of the water-sensitive paper image by using boundingRect (), and obtaining a minimum oblique rectangle wrapping the outline of the water-sensitive paper image by using minAreaRect ().
3. The ImagePy-based water-sensitive paper droplet parameter measuring device of claim 1, wherein: the image splicing module defines img _ center as a middle 1/2 area, img [1] as a left 1/4 area, img [2] as a right 1/4 area and img [3] as an image spliced by img [1] and img [2] by programming for the collected water-sensitive paper, and outputs img [3] and img _ center.
4. The ImagePy-based water-sensitive paper droplet parameter measuring device of claim 1, wherein: the color image segmentation module adopts an RGB color space model.
5. The ImagePy-based water-sensitive paper droplet parameter measuring device of claim 1, wherein: the fog drop parameter statistical module is used for compiling a program of fog drop coverage and a fog drop size intermediate value on the original basis of ImagePy through programming, and after image processing is completed, performing statistics on various parameters of the measured fog drops, including statistics on the maximum value, the minimum value, the average value, the median value, the fog drop coverage and the number of the fog drops.
6. A measuring method of a water-sensitive paper fog droplet parameter measuring device based on ImagePy specifically comprises the following steps:
step one, acquiring a water-sensitive paper image:
1) winding and fixing the water-sensitive paper on a vertical rod which is at the same height and level with the wheat seedlings to form a cylinder, wherein an 1/2 area in the middle of the water-sensitive paper faces the direction of spraying pesticides on agricultural machinery, and a 1/4 area on the left side and a 1/4 area on the right side of the water-sensitive paper are adhered together and are places where the agricultural machinery cannot directly spray, namely the back side;
2) by changing the type of a nozzle for spraying the pesticide and the spraying pressure, the agricultural machine carrying the pesticide respectively carries out multiple spraying experiments in the test wheat field, and multiple pieces of water-sensitive paper with sequential numbers can be obtained at different positions driven by the agricultural machine in each spraying experiment;
3) pasting the water-sensitive paper obtained in the last step on the same paper, and acquiring a group of experimentally collected water-sensitive paper images through an image acquisition module;
step two, the water sensitive paper image processing process:
1) collecting the water-sensitive paper image obtained in the step 3) by using an image collection module, importing the water-sensitive paper image into a computer, and opening the water-sensitive paper image to be processed by using ImagePy software;
2) firstly, graying, binaryzation, negation, corrosion and filtering operations are carried out on the water-sensitive paper image by ImagePy software, interference of useless information is eliminated, then area analysis operation is carried out, area screening is carried out on the water-sensitive paper image, and noise which does not belong to the water-sensitive paper is filtered by an area threshold value; because each water-sensitive paper image is of a fixed size, the value is taken as a threshold value, if the value is smaller than the threshold value, the water-sensitive paper image is determined to be unnecessary noise, and the noise is filtered out, so that an area only containing the water-sensitive paper image is obtained;
3) through the automatic rotary cutting module of the water-sensitive paper image, with the help of a minimum external rectangular function (minAreaRect) and a perpendicular boundary minimum positive rectangular function (boundingRect), the automatic rotary cutting of the area of the water-sensitive paper image obtained in the step 2) is realized: determining the angle of the water-sensitive paper image needing to be rotated by adopting a minimum circumscribed rectangular function (minAreaRect), and realizing rotation to enable the inclined water-sensitive paper image to be corrected; obtaining an interested area by adopting a smallest bounding rectangle function (bounding rectangle) to realize cutting of the water-sensitive paper area;
4) according to the real situation of pesticide spraying in the field, an image splicing module named montageimg is added into open source software ImagePy image processing software, collected water-sensitive paper images are cut into a left 1/4 area, a middle 1/2 area and a right 1/4 area of the images, and then the left 1/4 and the right 1/4 are spliced together to serve as the back of crops;
5) the water-sensitive paper image is further segmented by a color image segmentation module by adopting a color image segmentation method, and threshold values of R, G, B colors are set: r, G, B, setting a threshold value according to the color, and displaying an area in which the RGB three-channel color value in the image is smaller than the threshold value, namely a fog drop area, as white, and other areas, namely a background, as black according to the set threshold value, so as to obtain the required fog drop area;
step three, a droplet parameter measuring method:
counting fog drop parameters of the water-sensitive paper image obtained in the second step and the 5) through a fog drop parameter counting module, wherein the fog drop parameters comprise the maximum value, the minimum value, the average value, the median value, the fog drop coverage rate and the fog drop number parameter; wherein, the fog drop coverage rate and the fog drop median function are added on the basis of the original function of ImagePy by writing a program: writing a fog drop coverage program according to a formula (1); the fog drop median program calculates according to the odd number and the even number of the fog drop number, all the numbers are sorted from small to large, if the numbers are odd, the median value is directly taken, and if the numbers are even, the two numbers positioned in the middle are added and divided by 2 to obtain the median value; automatic statistics of fog droplet parameters can be realized in ImagePy software;
the droplet coverage was calculated as the percentage of the droplet coverage area to the total area of the statistic:
in the formula: c is the fog drop coverage rate; a. thesThe number of pixels in a fog drop area is shown; a. thepThe total pixel number of the test paper area is shown.
7. The method of claim 6, wherein the ImagePy-based device for measuring the fog drop parameters of the water-sensitive paper is characterized in that: the area threshold value in the second step 2) is 1000000.
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