CN109300156B - Urban greening intelligent management system - Google Patents
Urban greening intelligent management system Download PDFInfo
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- CN109300156B CN109300156B CN201811192873.1A CN201811192873A CN109300156B CN 109300156 B CN109300156 B CN 109300156B CN 201811192873 A CN201811192873 A CN 201811192873A CN 109300156 B CN109300156 B CN 109300156B
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T7/00—Image analysis
- G06T7/60—Analysis of geometric attributes
- G06T7/62—Analysis of geometric attributes of area, perimeter, diameter or volume
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01B—MEASURING LENGTH, THICKNESS OR SIMILAR LINEAR DIMENSIONS; MEASURING ANGLES; MEASURING AREAS; MEASURING IRREGULARITIES OF SURFACES OR CONTOURS
- G01B11/00—Measuring arrangements characterised by the use of optical techniques
- G01B11/28—Measuring arrangements characterised by the use of optical techniques for measuring areas
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T7/00—Image analysis
- G06T7/10—Segmentation; Edge detection
- G06T7/11—Region-based segmentation
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T7/00—Image analysis
- G06T7/10—Segmentation; Edge detection
- G06T7/194—Segmentation; Edge detection involving foreground-background segmentation
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T7/00—Image analysis
- G06T7/40—Analysis of texture
- G06T7/41—Analysis of texture based on statistical description of texture
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T7/00—Image analysis
- G06T7/90—Determination of colour characteristics
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T2207/00—Indexing scheme for image analysis or image enhancement
- G06T2207/10—Image acquisition modality
- G06T2207/10016—Video; Image sequence
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T2207/00—Indexing scheme for image analysis or image enhancement
- G06T2207/10—Image acquisition modality
- G06T2207/10024—Color image
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T2207/00—Indexing scheme for image analysis or image enhancement
- G06T2207/30—Subject of image; Context of image processing
- G06T2207/30181—Earth observation
- G06T2207/30188—Vegetation; Agriculture
Abstract
The invention provides an intelligent management system for urban greening, which comprises a green leaf area measuring device, a shooting device, a communication module and an alarm module, wherein the green leaf area measuring device is connected with the shooting device; the green leaf area measuring device is used for measuring the green leaf area of the urban plants so as to monitor whether the growth conditions of the plants are good or not; the shooting device is used for shooting videos of plant planting areas of the city so as to monitor whether people damage plants or not; the communication module is used for sending the green leaf area measurement result and the shot video to the alarm module; and the alarm module is used for sending out reminding information of poor plant growth condition and reminding information of preventing the plants from being damaged according to the green leaf area measurement result and the shot video. The invention has the beneficial effects that: the urban greening intelligent management system realizes the intelligent management of urban greening, including plant growth condition management and plant safety management.
Description
Technical Field
The invention relates to the technical field of management, in particular to an intelligent management system for urban greening.
Background
Urban greening improves living environment of people, and plant greening can also provide ornamental value for people; some people have poor self-control performance to destroy plants, need to supervise destruction behaviors through manpower, need to supervise a site by an administrator, need to increase more manpower resources if a monitoring area is too large, have poor management effect, and lack monitoring and management on the growth conditions of the plants.
Disclosure of Invention
In view of the above problems, the present invention aims to provide an intelligent management system for urban landscaping.
The purpose of the invention is realized by adopting the following technical scheme:
the intelligent management system for the urban greening comprises a green leaf area measuring device, a shooting device, a communication module and an alarm module;
the green leaf area measuring device is used for measuring the green leaf area of the urban plants so as to monitor whether the growth conditions of the plants are good or not;
the shooting device is used for shooting videos of plant planting areas of the city so as to monitor whether people damage plants or not;
the communication module is used for sending the green leaf area measurement result and the shot video to the alarm module;
and the alarm module is used for sending out reminding information of poor plant growth condition and reminding information of preventing the plants from being damaged according to the green leaf area measurement result and the shot video.
The invention has the beneficial effects that: the urban afforestation intelligent management system is provided, and realizes the intelligent management of urban afforestation, including plant growth condition management and plant safety management.
Drawings
The invention is further illustrated by means of the attached drawings, but the embodiments in the drawings do not constitute any limitation to the invention, and for a person skilled in the art, other drawings can be obtained on the basis of the following drawings without inventive effort.
FIG. 1 is a schematic structural view of the present invention;
reference numerals are as follows:
the device comprises a green leaf area measuring device 1, a shooting device 2, a communication module 3 and an alarm module 4.
Detailed Description
The invention is further described in connection with the following examples.
Referring to fig. 1, the urban afforestation intelligent management system of the present embodiment includes a green leaf area measuring device 1, a shooting device 2, a communication module 3 and an alarm module 4;
the green leaf area measuring device 1 is used for measuring the green leaf area of urban plants so as to monitor whether the growth condition of the plants is good or not;
the shooting device 5 is used for shooting videos of plant planting areas in cities so as to monitor whether people damage plants or not;
the communication module 3 is used for sending the green leaf area measurement result and the shot video to the alarm module 4;
and the alarm module 4 is used for sending out reminding information of poor plant growth condition and reminding information of preventing the plants from being damaged according to the green leaf area measurement result and the shot video.
The embodiment provides an urban greening intelligent management system, which realizes the intelligent management of urban greening, and comprises plant growth condition management and plant safety management.
Preferably, the green leaf area measuring device 1 comprises an image acquisition module, an image preprocessing module, an image processing module, an area measuring module and a verification module, the image acquisition module is used for acquiring the image of the plant, cutting off all leaves on the plant after the acquisition is finished, manually measuring the total green leaf area of the plant to obtain the true value of the total green leaf area, the image preprocessing module is used for preprocessing the plant image, the image processing module is used for extracting plant characteristic vectors according to the preprocessed image, the area measurement module takes the plant characteristic vector as an independent variable, the true value of the total green leaf area of the plant as a dependent variable, a green leaf area model is established by adopting a regression analysis method to measure the green leaf area, and the verification module is used for verifying the measurement precision of the area measurement module.
The preferred embodiment realizes accurate measurement of the green leaf area without damaging the plant.
Preferably, the image preprocessing module comprises a component extraction module and a segmentation module, wherein the component extraction module is used for extracting a first color component and a second color component of the plant image, and the segmentation module is used for segmenting the image based on the first color component and the second color component of the plant image to obtain a plant part binary image;
the first color component of the plant image is extracted in the following way:
in the formula, F1Representing a first color component of the plant image, R representing a red component of the plant image, G representing a green component of the plant image, and B representing a blue component of the plant image;
the second color component of the plant image is extracted in the following way:
in the formula, F2A second color component representing an image of the plant;
the segmentation module segments the image based on the first color component and the second color component of the plant image, and specifically comprises: and segmenting the plant part and the background part except the soil according to the first color component of the plant image, and segmenting the plant part and the soil part according to the second color component of the plant image.
The preferred embodiment passes the first color component
And a second color component
Accurate division of plant parts is realized, specifically, the contrast ratio of the first color component plant to the background except soil is high, and the contrast ratio of the second color component plant to the soil is high;
preferably, the image processing module 3 includes a first feature extraction module, a second feature extraction module and a feature vector determination module, the first feature extraction module is configured to obtain a first feature vector of a plant, the second feature extraction module is configured to obtain a second feature vector of the plant, and the feature vector determination module determines the feature vector of the plant according to the first feature vector and the second feature vector of the plant;
the first feature extraction module is used for acquiring a first feature vector of a plant, and specifically comprises:
calculating a first feature vector of the plant: t is1＝[D1，D2，D3]；
In the formula, T1Representing a first feature vector of the plant, D1Representing a first geometric characteristic factor, D2Representing a second geometric characteristic factor, D3Representing a third geometric characteristic factor;
the first geometric characteristic factor is determined using the following equation:
in the formula, a1Denotes the plant circumference, a2Representing the area of the plant;
the second geometric characteristic factor is the width of the plant, and the third geometric characteristic factor is the height of the plant;
The second feature extraction module is used for obtaining a second feature vector of the plant, and specifically comprises:
calculating a second feature vector of the plant: t is a unit of2＝[E1，E2]；
In the formula, T2Representing a second feature vector of the plant, E1Representing a first texture feature factor, E2Representing a second texture feature factor;
the first texture feature factor is determined in the following manner:
dividing the gray level and the gradient in the image into 16 levels, establishing a texture matrix of the image, wherein Y (i, j) is an element in the texture matrix and is used for representing the total number of pixel points with the gray level value i and the gradient value j in the image, and i, j is 1, 2, … and 16;
determining a first texture feature factor using the following equation:
by using a lower partThe second texture feature factor is determined by:
the characteristic vector determining module determines the characteristic vector of the plant according to the first characteristic vector and the second characteristic vector of the plant: t ═ D1，D2，D3，E1，E2]Wherein T represents a feature vector of a plant;
the preferred embodiment realizes the accurate acquisition of the plant characteristic vector, lays a foundation for the accurate measurement of the leaf area of the subsequent area measurement module, and particularly adopts the first characteristic vector T1＝[D1，D2，D3]And a second feature vector T2＝[E1，E2]The determined feature vector of the plant comprises the geometric feature of the plant and the textural feature of the plant.
Preferably, the verification module is configured to verify the measurement accuracy of the area measurement module, and specifically includes: comparing the measured value of the total green leaf area with the true value of the total green leaf area to obtain an error factor:
wherein W represents an error factor, s1Representing the total green leaf area measurement, s2Representing the real value of the total green leaf area; the smaller the error factor is, the higher the measurement precision of the area measurement module is, and an error threshold is set, and if the error factor is smaller than the set error threshold, the green leaf area measurement model of the area measurement module is available.
The preferred embodiment passes an error factor
The measurement precision of the area measurement module is verified, and the accuracy of area measurement is guaranteed.
The urban greening intelligent management system is adopted to carry out urban greening management, 5 cities are selected to carry out experiments, namely city 1, city 2, city 3, city 4 and city 5, the management efficiency and the management cost are counted, and compared with the prior art, the urban greening intelligent management system has the following beneficial effects as shown in the following table:
| management efficiency enhancement | Management cost reduction | |
| City 1 | 29％ | 27％ |
| City 2 | 27％ | 26％ |
| City 3 | 26％ | 26％ |
| City 4 | 25％ | 24％ |
| City 5 | 24％ | 22％ |
Finally, it should be noted that the above embodiments are only used for illustrating the technical solutions of the present invention, and not for limiting the protection scope of the present invention, although the present invention is described in detail with reference to the preferred embodiments, it should be understood by those skilled in the art that modifications or equivalent substitutions can be made on the technical solutions of the present invention without departing from the spirit and scope of the technical solutions of the present invention.
Claims (1)
1. An urban greening intelligent management system is characterized by comprising a green leaf area measuring device, a shooting device, a communication module and an alarm module;
the green leaf area measuring device is used for measuring the green leaf area of the urban plants so as to monitor whether the growth conditions of the plants are good or not;
the shooting device is used for shooting videos of plant planting areas of the city so as to monitor whether people damage plants or not;
the communication module is used for sending the green leaf area measurement result and the shot video to the alarm module;
the alarm module is used for sending out reminding information of poor plant growth condition and reminding information of preventing damage to plants according to the green leaf area measurement result and the shot video;
the green leaf area measuring device comprises an image acquisition module, an image preprocessing module, an image processing module, an area measuring module and a verification module, wherein the image acquisition module is used for acquiring an image of a plant, after the acquisition is finished, all leaves on the plant are cut off, the total green leaf area of the plant is manually measured, a true value of the total green leaf area is obtained, the image preprocessing module is used for preprocessing the image of the plant, the image processing module is used for extracting a plant characteristic vector according to the preprocessed image, the area measuring module takes the plant characteristic vector as an independent variable, the true value of the total green leaf area of the plant as a dependent variable, a green leaf area model is established by adopting a regression analysis method to measure the green leaf area, and the verification module is used for verifying the measurement precision of the area measuring module;
The image preprocessing module comprises a component extracting module and a segmenting module, wherein the component extracting module is used for extracting a first color component and a second color component of the plant image, and the segmenting module is used for segmenting the image based on the first color component and the second color component of the plant image to obtain a plant part binary image;
the first color component of the plant image is extracted in the following way:
in the formula, F1Representing a first color component of the plant image, R representing a red component of the plant image, G representing a green component of the plant image, and B representing a blue component of the plant image;
the second color component of the plant image is extracted in the following way:
in the formula, F2A second color component representing an image of the plant;
the segmentation module segments the image based on the first color component and the second color component of the plant image, and specifically comprises: dividing the plant part and the background part except the soil according to the first color component of the plant image, and dividing the plant part and the soil part according to the second color component of the plant image;
the image processing module comprises a first feature extraction module, a second feature extraction module and a feature vector determination module, wherein the first feature extraction module is used for acquiring a first feature vector of a plant, the second feature extraction module is used for acquiring a second feature vector of the plant, and the feature vector determination module is used for determining the feature vector of the plant according to the first feature vector and the second feature vector of the plant;
The first feature extraction module is used for acquiring a first feature vector of a plant, and specifically comprises:
calculating plantingFirst feature vector of strain: t is1＝[D1，D2，D3]；
In the formula, T1Representing a first feature vector of the plant, D1Representing a first geometric characteristic factor, D2Representing a second geometric characteristic factor, D3Representing a third geometric characteristic factor;
the first geometric characteristic factor is determined using the following equation:
in the formula, a1Denotes the plant circumference, a2Representing the area of the plant;
the second geometric characteristic factor is the width of the plant, and the third geometric characteristic factor is the height of the plant;
the second feature extraction module is used for acquiring a second feature vector of the plant, and specifically comprises:
calculating a second feature vector of the plant: t is2＝[E1，E2]；
In the formula, T2Representing a second feature vector of the plant, E1Representing a first texture feature factor, E2Representing a second texture feature factor;
the first texture feature factor is determined in the following manner:
dividing the gray level and the gradient in the image into 16 levels, establishing a texture matrix of the image, wherein Y (i, j) is an element in the texture matrix and is used for representing the total number of pixel points with the gray level value i and the gradient value j in the image, and i, j is 1, 2, … and 16;
determining a first texture feature factor using the following equation: 
Determining a second texture characteristic factor using:
the characteristic vector determining module determines the characteristic vector of the plant according to the first characteristic vector and the second characteristic vector of the plant: t ═ D1，D2，D3，E1，E2]Wherein T represents a feature vector of a plant;
the verification module is used for verifying the measurement precision of the area measurement module, and specifically comprises: comparing the measured value of the total green leaf area with the true value of the total green leaf area to obtain an error factor:
wherein W represents an error factor, s1Representing the total green leaf area measurement, s2Representing the real value of the total green leaf area; the smaller the error factor is, the higher the measurement precision of the area measurement module is, and an error threshold is set, and if the error factor is smaller than the set error threshold, the green leaf area measurement model of the area measurement module is available.
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