Method and System for Controlling the Water Pump Flow Rate of a Garden Sprinkler Truck Based on Image Processing

Abstract

This application relates to the field of image processing technology, and particularly to a method and system for controlling the water pump flow rate of a garden sprinkler based on image processing. The method includes: obtaining a garden plant image; dividing the garden plant image into several regions, and obtaining the garden plant coverage rate according to the area occupied by the regions; obtaining the histogram of each region, screening the connected regions based on the histogram, and obtaining the drought degree of the garden image according to the gradient of the edge pixel points in the connected regions and the difference between the mean value of its gray scale value and the mean value of the gray scale value of the region; obtaining the water pump flow rate correction value corresponding to the garden plant image according to the drought degree and the garden plant coverage rate corresponding to the garden plant image; obtaining the expected water pump flow rate corresponding to the garden plant image according to the water pump flow rate correction value and the maximum flow rate of the water pump of the garden sprinkler; and controlling the water pump flow rate of the garden sprinkler at the current moment to be the expected water pump flow rate. This application improves the accuracy of watering and prevents waste of water resources.

Description

Technical Field

[0001] This application relates to the field of image processing technology, and particularly relates to a method and system for controlling the water pump flow rate of a garden sprinkler based on image processing. Background Art

[0002] Garden sprinklers can efficiently spray water through water pumps, which can keep garden plants healthy and increase soil humidity. They can efficiently cover large areas and save the time of manual watering. They are suitable for garden greening and landscape maintenance, which can reduce labor intensity and improve work efficiency. If the control of the water pump flow rate of the garden sprinkler is not precise enough, it may lead to waste of water resources, especially in arid areas.

[0003] If the same water pump flow rate is always used for irrigation, it will cause insufficient irrigation of some garden plants, affecting the growth of garden plants, and some garden plants will be over-irrigated, resulting in waste of water resources. Because the coverage rate and drought degree of garden plants in different positions in the garden are different, the greater the coverage rate and drought degree of garden plants, the greater the degree of irrigation required for garden plants, and the greater the water pump flow rate of the garden sprinkler. Conversely, the water pump flow rate of the garden sprinkler is smaller. Therefore, it is necessary to correct the water pump flow rate based on this and control the water pump flow rate. Summary of the Invention

[0004] To solve the technical problem of inaccurate water pump flow rate irrigation, this application provides a method and system for controlling the water pump flow rate of a garden sprinkler based on image processing. The specific technical solutions adopted are as follows:

[0005] In the first aspect, this application proposes a method for controlling the water pump flow rate of a garden sprinkler based on image processing. The method includes the following steps:

[0006] Obtain garden plant images;

[0007] Use a color-based image segmentation algorithm to segment the garden plant images to obtain several garden plant regions; obtain the garden plant coverage rate of the garden plant images according to the difference between the number of pixel points in the garden plant regions and the number of pixel points in the garden plant images;

[0008] Obtain the histogram of each landscape plant area, and obtain the peak ratio of the peaks therein based on the histogram; screen the gray levels in the histogram based on the magnitude of the peak ratio to form the connected region of water-deficient leaves; obtain the edge pixel points of the landscape plant area through edge detection, and calculate the difference between the variance of the gradient magnitudes of all edge pixel points in the connected region of water-deficient leaves and the variance of the gradient magnitudes of all edge pixel points in the adjacent connected region of water-deficient leaves as the drought impact coefficient; obtain the drought degree corresponding to the landscape plant image according to the difference between the average gray value of the pixel points in each connected region of water-deficient leaves and the average gray value of the pixel points in the landscape plant area where it is located, the drought impact coefficient of the connected region of water-deficient leaves, and the number of connected regions of water-deficient leaves;

[0009] Obtain the pump flow correction value corresponding to the landscape plant image according to the drought degree corresponding to the landscape plant image and the landscape plant coverage rate;

[0010] Obtain the expected pump flow corresponding to the landscape plant image according to the pump flow correction value and the maximum flow of the water pump of the landscape sprinkler; control the pump flow of the landscape sprinkler at the current moment to be the expected pump flow.

[0011] In the above solution, the present application first analyzes the proportion of the landscape in the image at the current moment through image processing technology, that is, obtains the landscape plant coverage rate, and also analyzes the color and curling degree of the landscape leaves through image processing technology to judge the drought degree of the leaves; determines the water flow correction value according to the coverage rate and drought degree of the landscape plants in different positions in the landscape, and controls the pump flow at the current moment through the correction value, so that the landscape plants can be fully watered and water resource waste can be avoided.

[0012] In one embodiment, the method for obtaining the landscape plant coverage rate of the landscape plant image according to the difference between the number of pixel points in the landscape plant area and the number of pixel points in the landscape plant image is:

[0013] Count the number of landscape plant areas in the landscape plant image, and count the number of pixel points in each landscape plant area;

[0014] Let the ratio of the number of pixel points in all landscape plant areas in the landscape plant image to the number of pixel points in the landscape plant image be the landscape plant coverage rate of the landscape plant image.

[0015] In one embodiment, the method for obtaining the peak ratio of the peaks therein based on the histogram is:

[0016] For the histogram of each landscape plant area, use the peak detection algorithm to obtain the height and width of each peak in the histogram, and calculate the ratio of the height and width of each peak as the peak ratio of the peak.

[0017] In one embodiment, the method for screening gray levels in a histogram based on the peak ratio value to form the connected domain of water-deficient leaves is as follows:

[0018] If the peak ratio value is greater than a preset threshold, then mark this peak as an abnormal peak; extract the pixel points corresponding to the gray values of all abnormal peaks in the garden plant area, and form several connected domains through connected domain analysis for these pixel points, and mark the formed connected domains as the connected domains of water-deficient leaves.

[0019] In one embodiment, the method for obtaining the drought degree corresponding to the garden plant image according to the difference between the average gray value of the pixel points in each connected domain of water-deficient leaves and the average gray value of the pixel points in the garden plant area where it is located, the variance of the gradient amplitudes of all edge pixel points in the connected domain of water-deficient leaves, and the number of connected domains of water-deficient leaves is as follows:

[0020] , represents the average gray value of the pixel points in the r-th connected domain of water-deficient leaves in the h-th garden plant area, represents the average gray value of the pixel points in the h-th garden plant area, represents the drought influence coefficient of the r-th connected domain of water-deficient leaves in the h-th garden plant area, represents the normalization function, represents the number of connected domains of water-deficient leaves in the h-th garden plant area, represents the number of garden plant areas in the garden plant image, Z represents the number of connected domains of water-deficient leaves in the garden plant image, represents the drought degree corresponding to the garden plant image.

[0021] In one embodiment, the method for obtaining the pump flow correction value corresponding to the garden plant image according to the drought degree corresponding to the garden plant image and the garden plant coverage rate is as follows:

[0022] The pump flow correction value corresponding to the garden plant image has a positive correlation with the drought degree corresponding to the garden plant image and the garden plant coverage rate.

[0023] In one embodiment, the expression of the pump flow correction value is:

[0024] , represents the garden plant coverage rate of the garden plant image, represents the drought degree corresponding to the garden plant image, represents the pump flow correction value corresponding to the garden plant image.

[0025] In one embodiment, the method for obtaining the expected water pump flow rate corresponding to the garden plant image based on the water pump flow rate correction value and the maximum flow rate of the water pump of the garden sprinkler is as follows:

[0026] , represents the water pump flow rate correction value corresponding to the garden plant image, represents the maximum flow rate of the water pump, represents the expected water pump flow rate corresponding to the garden plant image.

[0027] In one embodiment, the method for obtaining the garden plant image is as follows:

[0028] Install a camera on one side of the garden sprinkler. The garden sprinkler moves at a constant speed in real time and sprays water. The camera captures a garden plant image every preset time.

[0029] In a second aspect, an embodiment of the present application further provides a water pump flow rate control system for a garden sprinkler based on image processing, including a memory, a processor, and a computer program stored in the memory and running on the processor. When the processor executes the computer program, it implements the steps of the above-mentioned water pump flow rate control method for a garden sprinkler based on image processing.

[0030] The beneficial effects of the present application are as follows:

[0031] The present application first analyzes the proportion of the garden in the image at the current moment through image processing technology, that is, obtains the coverage rate of garden plants, and analyzes the color and curling degree of garden leaves through image processing technology to judge the drought degree of the leaves; determines the water flow rate correction value based on the coverage rate and drought degree of garden plants in different positions in the garden, and controls the water pump flow rate at the current moment through the correction value, so that the garden plants can be fully irrigated and water resource waste can be avoided. BRIEF DESCRIPTION OF THE DRAWINGS

[0032] In order to more clearly illustrate the technical solutions and advantages in the embodiments of the present application or the prior art, the following will briefly introduce the drawings required for the description of the embodiments or the prior art. Obviously, the following drawings are only some embodiments of the present application. For those of ordinary skill in the art, other drawings can be obtained based on these drawings without creative efforts.

[0033] Figure 1 is a flowchart of the water pump flow rate control method for a garden sprinkler based on image processing provided by an embodiment of the present application. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0034] To further elaborate on the technical means and effects adopted by this application to achieve the intended invention purpose, the following, in combination with the accompanying drawings and preferred embodiments, details the specific implementation manner, structure, features, and effects of the method and system for controlling the water pump flow rate of a garden sprinkler vehicle based on image processing proposed according to this application. In the following description, different "one embodiment" or "another embodiment" do not necessarily refer to the same embodiment. In addition, the specific features, structures, or characteristics in one or more embodiments can be combined in any suitable form.

[0035] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by those skilled in the technical field to which this application belongs.

[0036] Embodiment of the method and system for controlling the water pump flow rate of a garden sprinkler vehicle based on image processing:

[0037] The following specifically describes the specific solution of the method for controlling the water pump flow rate of a garden sprinkler vehicle provided by this application in combination with the accompanying drawings.

[0038] Please refer to Figure 1 , which shows the flowchart of the method for controlling the water pump flow rate of a garden sprinkler vehicle based on image processing provided by an embodiment of this application. The method includes the following steps:

[0039] Step S001, obtaining a garden plant image.

[0040] Install a camera on the right side of the garden sprinkler vehicle. Collect the garden plant image through the camera. After analyzing the collected garden plant image, irrigate the garden plants corresponding to the garden plant image. The garden sprinkler vehicle continuously moves at a constant speed along the established route and sprinkles water at all times. After analyzing the image, predict the water pump flow rate and adjust the flow rate. In this embodiment, a garden plant image is collected every 5 s, that is, the water pump flow rate is predicted every 5 s.

[0041] Thus, a garden plant image is obtained.

[0042] Step S002, dividing the garden plant image into several regions and obtaining the garden plant coverage rate according to the area occupied by the regions.

[0043] Since the drought degrees and distribution situations of different plants in the garden are different, if a single water pump flow rate is used for irrigation, it will cause insufficient irrigation of some garden plants, affecting the growth of garden plants, and there will also be excessive irrigation of some garden plants, resulting in waste of water resources. Therefore, analyze the irrigation requirements of different plots through image analysis to prevent waste of water resources.

[0044] Since the colors of garden plants are relatively single and vary greatly from those of non-garden plants, the color-based image segmentation algorithm is used to operate on each garden plant image to obtain several garden plant regions in each garden plant image.

[0045] It should be noted that in the garden, if the coverage rate of a certain garden plant region is larger, the degree of irrigation required is greater, and vice versa. Therefore, this feature is used to adjust the water pump flow rate. Here, calculate the garden plant coverage rate of each garden plant image.

[0046] For a garden plant image, count the number of garden plant regions in it, and count the number of pixel points in each garden plant region. Obtain the garden plant coverage rate of the garden plant image based on the ratio of the number of pixel points in all garden plant regions to the number of pixel points in the garden plant image.

[0047] In this embodiment, let the ratio of the number of pixel points in all garden plant regions in the garden plant image to the number of pixel points in the garden plant image be the garden plant coverage rate of the garden plant image.

[0048] The larger the garden plant coverage rate, it indicates that there are more garden plants in the image collected at this time, and the water pump flow rate needs to be increased.

[0049] So far, the garden plant coverage rate of the garden plant image has been obtained.

[0050] Step S003: Obtain the histogram of each region, screen the connected regions based on the histogram, and obtain the drought degree of the garden image according to the difference between the gradient of the edge pixel points in the connected region and the average gray value of the region and the average gray value of the region.

[0051] In the garden, the drought conditions of different garden plants are different. The more drought the garden plant is, the greater the degree of irrigation required, and vice versa. When the garden plant is drought, there will be subtle changes in color, and the leaves of the garden plant will curl to a certain extent, especially in the delicate areas on the leaves, where the curling degree is the largest. The edges of the leaves of normal garden plants are relatively smooth, while the edges of the curled leaves are very rough. From the plant characteristics, the delicate areas in the leaves are yellowish or light green, and their gray values are relatively large, while the mature areas in the leaves are dark green and the gray values are relatively small. Therefore, the above features are used to judge the drought degree of the garden plant. Here, calculate the drought degree of the garden plants in each garden plant image.

[0052] First, a histogram is made for each garden plant area in each garden plant image; for the histogram of each garden plant area, a peak detection algorithm is used to obtain the height and width of each peak in the histogram, and the ratio of the height and width of each peak is calculated as the peak ratio of the peak. Among them, the peak detection algorithm is a well-known technology and will not be elaborated in detail in this application.

[0053] Since the width of the peak of a normal leaf will be relatively large and there will be a relatively natural color transition, when the garden plant is drought-stricken, the color will change, and the width of the peak in the changed part will be relatively narrow and rather abrupt. Therefore, for the peak ratio of each peak, if the peak ratio is greater than the preset threshold, then this peak is recorded as an abnormal peak; the pixel points corresponding to the gray values of all abnormal peaks in the garden plant area are extracted, and these pixel points are formed into several connected regions through connected component analysis, and the formed connected regions are recorded as water-deficient leaf connected regions. That is, the pixel points corresponding to the abnormal peaks are more likely to be relatively drought-stricken leaves.

[0054] The above calculations are performed for each garden plant area to obtain the water-deficient leaf connected regions of each garden plant image.

[0055] If the garden plant is water-deficient, the degree of leaf curling of the same plant is usually similar. That is, the water-deficient leaf connected regions of multiple garden plants within the garden plant area obtained from the garden plant image will show regional distribution on the garden plant image because they are located in the same garden plant area, and there will also be a dryness level division on the plant. The leaves at the top of the plant are more likely to show drought characteristics, but the lower garden plant leaves are more plump. Therefore, when distinguishing the drought situation of the garden plant area, the influence of the plant area distribution should be considered more carefully;

[0056] Based on this, a drought impact analysis is performed on a single water-deficient leaf connected region. The variance of the gradient amplitudes of all edge pixel points of the water-deficient leaf connected region within the garden plant area is calculated. If the variance difference between the water-deficient leaf connected region and its surrounding water-deficient leaf connected regions is smaller, it indicates that it has regional distribution characteristics and the drought situation of its water-deficient leaf connected region is more serious; the adjacent water-deficient leaf connected regions adjacent to each water-deficient leaf connected region are recorded as adjacent connected regions, and the mean value of the difference in the variance of the gradient amplitudes of the edge pixel points between the water-deficient leaf connected region and its adjacent connected regions is normalized as the drought impact coefficient of the water-deficient leaf connected region.

[0057] The mean value of the gray values of all pixel points in each water-deficient leaf connected region within each garden plant area is calculated, and the mean value of the gray values of all pixel points in the garden plant area is calculated. For the garden plant image, an edge detection algorithm is used to obtain the edge pixel points. In this embodiment, the Canny operator is used for the edge detection algorithm, which is a well-known technology and will not be elaborated here.

[0058] Obtain the drought degree corresponding to the garden plant image based on the difference between the average gray value of the pixel points in each water-deficient leaf connected region and the average gray value of the pixel points in the garden plant region where it is located, the drought influence coefficient of the water-deficient leaf connected region, and the number of water-deficient leaf connected regions. The expression is as follows:

[0059] , represents the average gray value of the pixel points in the r-th water-deficient leaf connected region of the h-th garden plant region, represents the average gray value of the pixel points in the h-th garden plant region, represents the drought influence coefficient of the r-th water-deficient leaf connected region of the h-th garden plant region, represents the normalization function, represents the number of water-deficient leaf connected regions in the h-th garden plant region, represents the number of garden plant regions in the garden plant image, Z represents the number of water-deficient leaf connected regions in the garden plant image, represents the drought degree corresponding to the garden plant image.

[0060] Among them, is positively correlated with The larger the value of , it indicates that the edge of the -th suspected water-deficient leaf connected region in the -th garden plant region of the garden plant image is less smooth, and the greater the drought degree of the garden plants in the garden plant image. The greater the difference between the average gray value of the pixel points in the water-deficient leaf connected region and the average gray value of the pixel points in the garden plant region where it is located, the more it indicates that the -th garden plant region of the garden plant image -th suspected water-deficient leaf connected region is very likely to be the tender region of the garden plant. According to the characteristics of the plant, when drought occurs, the curling degree of the tender region is the largest, indicating that the drought degree of the garden plants in the garden plant image is greater.

[0061] So far, the drought degree corresponding to the garden plant image has been obtained.

[0062] Step S004, obtain the pump flow correction value corresponding to the garden plant image according to the drought degree corresponding to the garden plant image and the garden plant coverage rate.

[0063] Through the above steps, the coverage rate and drought degree of garden plants in the garden plant image are obtained. The greater the coverage rate and drought degree of garden plants, the greater the degree of irrigation required, and the greater the pump flow rate of the garden sprinkler; conversely, the smaller the pump flow rate of the garden sprinkler. Then, according to the coverage rate and drought degree of garden plants in each garden plant image, calculate the pump flow correction value of the garden plants in each garden plant image to predict the pump flow rate of the garden sprinkler.

[0064] Obtain the pump flow correction value corresponding to the garden plant image according to the drought degree and garden plant coverage rate corresponding to the garden plant image.

[0065] The pump flow correction value corresponding to the garden plant image is positively correlated with the drought degree and garden plant coverage rate corresponding to the garden plant image.

[0066] It should be noted that positive correlation means that when one variable increases, the other variable also increases, and the change directions of the two variables are the same. When one variable changes from large to small or from small to large, the other variable also changes from large to small or from small to large; the specific relationship is determined by the actual application, and this application does not make special restrictions.

[0067] Preferably, in this embodiment, the expression of the pump flow correction value is: , represents the garden plant coverage rate of the garden plant image, represents the drought degree corresponding to the garden plant image, represents the pump flow correction value corresponding to the garden plant image.

[0068] So far, the pump flow correction value corresponding to the garden plant image has been obtained.

[0069] Step S005, obtain the expected pump flow corresponding to the garden plant image according to the pump flow correction value and the maximum flow rate of the garden sprinkler pump; control the pump flow rate of the garden sprinkler at the current moment to be the expected pump flow rate.

[0070] Through the above steps, the pump flow correction value corresponding to the garden plant image is obtained, and the pump flow rate of the garden sprinkler is corrected by using the pump flow correction value to obtain the expected pump flow rate. The expected pump flow rate is used as the pump flow rate adjusted by the garden sprinkler at this time, so as to adjust the pump flow rate in real time.

[0071] The garden sprinkler collects a garden plant image every preset time. For this garden plant image, obtain the expected pump flow corresponding to the garden plant image according to the corresponding pump flow correction value and the maximum flow rate of the garden sprinkler pump. Its expression is: , represents the pump flow correction value corresponding to the garden plant image, Indicates the maximum flow rate of the water pump Indicates the expected water pump flow rate corresponding to the garden plant image

[0072] For the garden plant image collected after a preset time, controlling the water pump flow rate of the garden sprinkler at the current moment to the expected water pump flow rate completes the water pump flow rate control of the garden sprinkler at the current moment

[0073] Based on the same inventive concept as the above method, an embodiment of the present invention further provides a water pump flow rate control system for a garden sprinkler based on image processing, including a memory, a processor, and a computer program stored in the memory and running on the processor. When the processor executes the computer program, it implements the steps of any one of the above methods for controlling the water pump flow rate of the garden sprinkler based on image processing

[0074] It should be noted that the above embodiments are only used to illustrate the technical solutions of the present application, rather than to limit them; although the present application has been described in detail with reference to the foregoing embodiments, those of ordinary skill in the art should understand that they can still modify the technical solutions described in the foregoing embodiments, or perform equivalent replacements for some of the technical features; and these modifications or replacements do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the embodiments of the present application, and should all be included in the protection scope of the present application

[0075] Each embodiment in this specification is described in a progressive manner. The same or similar parts between the embodiments can be referred to each other, and the key points of each embodiment are the differences from other embodiments

Claims

1. A method for controlling the flow rate of a garden sprinkler water pump based on image processing, characterized in that: The method comprises the following steps: Get images of garden plants; The garden plant image is segmented using a color-based image segmentation algorithm to obtain a number of garden plant regions; the garden plant coverage rate of the garden plant image is obtained according to the difference between the number of pixel points in the garden plant region and the number of pixel points in the garden plant image; The histogram of each garden plant area is obtained, and the peak ratio of the peaks therein is obtained based on the histogram; the grayscale is screened in the histogram based on the size of the peak ratio to form a water-deficient leaf connected domain; the edge pixel points of the garden plant area are obtained by edge detection, and the difference between the variance of the gradient amplitude of all edge pixel points in the water-deficient leaf connected domain and the variance of the gradient amplitude of all edge pixel points in its adjacent water-deficient leaf connected domain is calculated as the drought influence coefficient; the drought degree corresponding to the garden plant image is obtained according to the difference between the grayscale value mean of the pixel points in each water-deficient leaf connected domain and the grayscale mean of the pixel points in the garden plant area where it is located, the drought influence coefficient of the water-deficient leaf connected domain, and the number of water-deficient leaf connected domains; According to the drought degree and the coverage rate of the garden plants corresponding to the garden plant images, a water pump flow correction value corresponding to the garden plant images is obtained; The expected water pump flow corresponding to the garden plant image is obtained according to the water pump flow correction value and the maximum flow of the water pump of the garden sprinkler truck; and the water pump flow of the garden sprinkler truck at the current moment is controlled to be the expected water pump flow.

2. A method for controlling the flow rate of a garden sprinkler water pump based on image processing as claimed in claim 1, characterized in that: The method for obtaining the garden plant coverage rate of the garden plant image according to the difference between the number of pixels in the garden plant area and the number of pixels in the garden plant image is: Counting the number of garden plant areas in the garden plant image, and counting the number of pixel points in each garden plant area; The ratio of the number of pixels in all garden plant areas in the garden plant image to the number of pixels in the garden plant image is taken as the garden plant coverage rate of the garden plant image.

3. A method for controlling the flow rate of a garden sprinkler water pump based on image processing as claimed in claim 1, characterized in that: The method for obtaining the peak ratio of the peaks in the histogram based on the histogram is: A peak detection algorithm is used for the histogram of each garden plant area to obtain the height and width of each peak in the histogram, and the ratio of the height and width of each peak is calculated as the peak ratio of the peak.

4. A method for controlling the flow rate of a garden sprinkler water pump based on image processing as claimed in claim 1, characterized in that: The method for filtering the grayscale in the histogram based on the size of the peak ratio to form the connected domain of the water-deficient leaves is: If the peak ratio is greater than the preset threshold, the peak is recorded as an abnormal peak; the pixel points of the grayscale values ​​corresponding to all abnormal peaks in the garden plant area are extracted, and these pixel points are formed into several connected domains through connected domain analysis, and the formed connected domains are recorded as water-deficient leaf connected domains.

5. A method for controlling the flow rate of a garden sprinkler water pump based on image processing as claimed in claim 1, characterized in that: The method for obtaining the drought degree corresponding to the garden plant image according to the difference between the gray value mean of the pixel points in each water-deficient leaf connected domain and the gray value mean of the pixel points in the garden plant area where it is located, the drought influence coefficient of the water-deficient leaf connected domain and the number of water-deficient leaf connected domains is: , represents the mean gray value of the pixels in the rth water-deficient leaf connected domain of the hth garden plant area, represents the mean gray value of the pixel points in the h-th garden plant area, represents the drought impact coefficient of the rth water-deficient leaf connected domain in the hth garden plant area, represents the normalization function, represents the number of connected domains of water-deficient leaves in the h-th garden plant region, represents the number of garden plant areas in the garden plant image, Z represents the number of connected domains of water-deficient leaves in the garden plant image, Indicates the drought degree corresponding to the garden plant image.

6. A method for controlling the flow rate of a garden sprinkler water pump based on image processing as claimed in claim 1, characterized in that: The method for obtaining the water pump flow correction value corresponding to the garden plant image according to the drought degree and the garden plant coverage rate corresponding to the garden plant image is: The water pump flow correction value corresponding to the garden plant image is positively correlated with the drought degree and garden plant coverage rate corresponding to the garden plant image.

7. A method for controlling the flow rate of a garden sprinkler water pump based on image processing as claimed in claim 6, characterized in that: The expression of the water pump flow correction value is: , represents the garden plant coverage rate of the garden plant image, Indicates the drought degree corresponding to the garden plant image, Indicates the water pump flow correction value corresponding to the garden plant image.

8. A method for controlling the flow rate of a garden sprinkler water pump based on image processing as claimed in claim 1, characterized in that: The method for obtaining the expected water pump flow corresponding to the garden plant image according to the water pump flow correction value and the maximum flow of the garden sprinkler water pump is: , Indicates the water pump flow correction value corresponding to the garden plant image, Indicates the maximum flow rate of the pump. Indicates the expected water pump flow corresponding to the garden plant image.

9. A method for controlling the flow rate of a garden sprinkler water pump based on image processing as claimed in claim 1, characterized in that: The method for obtaining the garden plant image is: A camera is installed on one side of a garden sprinkler truck, wherein the garden sprinkler truck moves at a constant speed in real time and sprinkles water, and the camera collects an image of garden plants every preset time.

10. A garden sprinkler water pump flow control system based on image processing, comprising a memory, a processor, and a computer program stored in the memory and running on the processor, characterized in that: When the processor executes the computer program, the steps of the method for controlling the flow rate of a garden sprinkler truck water pump based on image processing as described in any one of claims 1 to 9 are implemented.

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