CN109146862A - Soil remediation condition intelligent detection device - Google Patents
Soil remediation condition intelligent detection device Download PDFInfo
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- CN109146862A CN109146862A CN201810882416.9A CN201810882416A CN109146862A CN 109146862 A CN109146862 A CN 109146862A CN 201810882416 A CN201810882416 A CN 201810882416A CN 109146862 A CN109146862 A CN 109146862A
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T7/00—Image analysis
- G06T7/0002—Inspection of images, e.g. flaw detection
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
- H04N7/00—Television systems
- H04N7/18—Closed-circuit television [CCTV] systems, i.e. systems in which the video signal is not broadcast
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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
-
- 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
- G06T2207/20—Special algorithmic details
- G06T2207/20048—Transform domain processing
- G06T2207/20064—Wavelet transform [DWT]
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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
- G06T2207/30184—Infrastructure
-
- 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
In order to avoid the characteristic of sensor oneself requirement fixed form installation monitors the blind area that may cause to blowdown, the present invention provides a kind of soil remediation condition intelligent detection devices, for to forest farm or pasture by being monitored in the governance process of the soil of organic contamination to soil remediation state, comprising: acquiring video information unit, ARM unit and intelligent identification unit.The present invention can be taken photo by plane by equipment such as unmanned planes and in the way of machine learning, obtain the growth characteristics such as the color of vegetation and state, and then carry out simple, quickly judgement to recovery situation of the soil after being polluted.
Description
Technical field
The present invention relates to environment monitoring techniques fields, set more particularly, to a kind of detection of soil remediation condition intelligentization
It is standby.
Background technique
Soil pollution is the environmental problem being on the rise, and directly threatens the safety and soil ecology function of human food's health
The sustainable development of energy.It has attracted wide public concern about the toxicity of contaminated soil and with risk assessment, but has only combined
The interaction between soil pollutant and organism can be just effectively detected in the method for chemistry and biology.
Currently, Soil K+adsorption instrument point includes following several: 1) for the soil sample collector of soil pre-treatment, soil vibration sieve
Instrument, cutting ring, soil sieve, soil liquid sampler etc.；2) by soil nutrient detection soil EC based on, soil nutrient tacheometer,
Desk-top near-infrared soil nutrient tacheometer, hand-held soil nutrient tacheometer, nylon mesh, azotometer, ionometer, PH meter, atom
Absorption spectrophotometer, inscription hollow cathode lamp, second block steel cylinder, Atomic Absorption Spectrometer, atomic fluorescence spectrophotometer, mercury vapourmeter, drop
Determine instrument, gas chromatograph, spectrophotometer, conductivity meter, soil salt analyzer etc.；3) for the portable of soil moisture detection
Formula soil moisture content quick analyser, soil moisture content quick analyser, portable soil soil moisture content analyzer, soil moisture temperature tacheometer, drying
Method infrared moisture tester, soil moisture temperature tacheometer etc.；4) it is used for the digital soil hardometer of soil hardness detection, refers to
Pin type stratameter, soil density analyzer etc.；5) based on the P in soil H of soil acidity or alkalinity detection, pointer soil acid
Spend meter, digital soil acidometer etc..
In the prior art, application No. is the Chinese invention patent applications of CN201410220674.2 to disclose one kind based on object
Enterprise's rainwater discharge outlet monitoring system of networking, including field data acquisition device, Internet of Things monitoring center and emergency processing dress
It sets, the field data acquisition device includes monitor, water quality testing meter, integrated water pump；The Internet of Things monitoring center packet
Include central processing unit, controller, display, emergency alarm device, 3G warning module；The emergency treatment device includes recirculation water
Pump, several electrically operated valves, emergency lagoon, the field data acquisition device, display, controller and communication system are and centre
Device connection is managed, each electrically operated valve is connect with controller, and the emergency alarm device and 3G warning module pass through wired or nothing
Line mode is connected with communication system, and the monitor and water quality testing meter are mounted on the water inlet of integrated pump station.However, including
The prior art including this mode requires to be arranged many Soil K+adsorption equipment to scene, and the purchase cost of these equipment compared with
Height, installation cost are higher, and maintenance cost is higher.
In addition, the moment monitors the data that these equipment or regular monitoring these equipment obtain, it is difficult to which accurately reflecting it is
It is no the problem of soil secondary pollution occur.For current soil, pollution and repair process be typically all compared with
It is slow.Above-mentioned Soil K+adsorption equipment is unsuitable for being fixedly secured to these scenes, and otherwise efficiency is extremely low.And artificial scene inspection
The cost of survey is also higher, and detection activity is restricted by factors such as environment, geographical locations, thus what artificial on-site test obtained
Data accuracy leaves a question open.
Summary of the invention
In order to improve the efficiency of soil remediation detection and contamination monitoring, monitoring cost is reduced, the present invention provides a kind of soil
Earth repairs condition intelligent detection device, for forest farm or pasture by the governance process of the soil of organic contamination to soil
Reparation state is monitored, comprising:
Acquiring video information unit, the image letter of the vegetation for shooting soil region to be detected using unmanned plane mode
Breath, obtains video information；
ARM unit, the video information for being obtained according to the acquiring video information unit carry out the reparation state of soil
Detection；
Intelligent identification unit restores after by the pollution of different organic pollutants for the vegetation according to the pre-stored data
Feature is compared with the result of the ARM unit, so that it is determined that the possibility type of organic pollutant.
Further, the acquiring video information unit includes:
Latitude and longitude information obtains subelement, for obtaining the latitude and longitude information at each moment；
Soil remediation state determines subelement, for determining soil remediation state.
Further, the latitude and longitude information acquisition subelement includes:
It corrects video information image-latitude and longitude information packet and obtains module, for obtaining the vegetation of soil region to be detected
Video information is corrected, and the corresponding latitude and longitude information of video information after being corrected, according to the video information after correction
Image-latitude and longitude information packet.
Further, the soil remediation state determines that subelement is believed according to the video information image after correction-longitude and latitude
Breath packet carries out the determination of soil remediation state.
Further, the correction video information image-latitude and longitude information packet acquisition module includes:
Assuming that the T0 moment, the T1 moment, the T2 moment ..., the Tn moment be corresponding n+1 consecutive hours in the video information
It carves, wherein n is the natural number greater than 4；
The video information at T0 and T1 moment is converted to image respectively for carrying out framing to video information by framing module
Information Img0 and Img1, and obtain the correction coefficient of low frequency sub-band signal and the correction coefficient of high frequency subband signals；
Low frequency sub-band signal correction module, for according to the correction coefficient of low frequency sub-band signal and the school of high frequency subband signals
Positive coefficient, to the T2 moment ..., the video information at Tn moment is corrected；
Sorting module, for the corrected T0 moment, the T1 moment, the T2 moment ..., the video information at Tn moment into
Row sequence；
Video information image-latitude and longitude information packet generation module, for generating video information image-latitude and longitude information packet.
Further, the framing module includes:
First subband signal obtains submodule and is corresponding in turn to for carrying out wavelet transformation respectively to Img0 and Img1
In the low frequency sub-band signal L at T0 moment and T1 moment0, high frequency subband signals L1And high frequency subband signals H0, high frequency subband signals
H1；
Low frequency sub-band signal correction coefficient computational submodule, for calculating the correction coefficient C (x, y) of low frequency sub-band signalL:
Wherein, the x and y respectively indicates the abscissa and ordinate of some pixel in the frame image at T0 moment, βmIt indicates
The mean value of correction matrix, ηmIndicate correction matrix variance, the correction matrix be withFor variance,For mean value
2 rank diagonal matrix B；
Submodule is filtered, for, by Gaussian filter, obtaining H ' to high frequency subband signals0And H '1:
High frequency subband signals correction coefficient computational submodule calculates for the frame image for the T0 moment and is located at the position (x, y)
The correction coefficient C (x, y) of the high frequency subband signals for the pixel setH:
Wherein SδIndicate centered on (x, y),For the area in the circle domain of radius, the modulus value of D representing matrix A
Upper integer, A indicate following matrix:
Wherein i is the lower integer of the modulus value of matrix A.
Further, the low frequency sub-band signal correction module includes:
Second subband signal obtains submodule, for the T2 moment ..., the video information at Tn moment carry out small echo change
It changes, respectively obtains and the one-to-one high frequency subband signals of these video informations and low frequency sub-band signal；
First high frequency correction submodule, for these high frequency subband signals for its correspondence at the time of video information in
Each point, with C (x, y)HSubtract each other；
Second high frequency correction submodule, for these low frequency sub-band signals for its correspondence at the time of video information in
Each point, with C (x, y)LSubtract each other；
It corrects video information and obtains submodule, for passing through the high frequency subband signals subtracted each other and low frequency sub-band signal for above-mentioned
At the time of according to its correspondence, carry out wavelet inverse transformation respectively, obtain with the corrected T2 moment ..., the video at Tn moment
Information.
Further, above-mentioned sorting module includes:
Record sub module, for recording in above-mentioned correction course, corrected each high frequency subband signals；
Convolution submodule, for each high frequency subband signals according to chronological order, to be carried out convolution two-by-two；
Median computational submodule, for calculating the median of convolution value；
Minimum convoluted value determines submodule, for the determining the smallest convolution value of absolute value of the difference with the median；
Reference video information determines submodule, for determine it is corresponding with the smallest convolution value of the absolute value, according to when
Between sequentially come subsequent video information, as the T0 moment, the T1 moment, the T2 moment ..., in this n+1 moment at Tn moment
Reference video information.
Further, the video information image-latitude and longitude information packet generation module includes:
Submodule is encapsulated, for corresponding latitude and longitude information in video information to be sealed with it by the reference video information
Dress；
Sending submodule, for transmitting the information after the encapsulation.
Further, the soil remediation state determines that subelement includes:
Receiving submodule obtains reference video information and matched for receiving the information after encapsulation and unlocking
Latitude and longitude information；
Vegetation identifies submodule, for carrying out vegetation identification to reference video information in the way of machine learning；
Growth characteristics identify submodule, for carrying out growth characteristics identification to the vegetation identified；
Detection sub-module, for being compared according to the growth characteristics identified with reference to growth characteristics, when lower than threshold value
Or when being higher than threshold value, it is determined as soil restoration exception.
Further, the growth characteristics include: leaf color, plant trunk, trunk diameter.
The beneficial effect comprise that can be taken photo by plane by equipment such as unmanned planes and in the way of machine learning,
Growth characteristics and the states such as the color of vegetation are obtained, and then recovery situation of the soil after being polluted is carried out simple, quick
Judgement.Since this recovery process is very slow, it is being located at the domestic many places forest land progress in the Inner Mongol on a small scale through applicant
The monitoring frequency of test, unmanned plane can be primary for primary even two months one month, not only significantly reduces from energy consumption
Monitoring requirements, and monitoring cost is also greatly reduced from equipment purchase and maintenance cost.
Detailed description of the invention
Fig. 1 shows the composition block diagram of equipment of the invention.
Specific embodiment
As shown in Figure 1, preferred embodiment in accordance with the present invention, the present invention provides a kind of inspections of soil remediation condition intelligentization
Measurement equipment, for forest farm or pasture by being monitored in the governance process of the soil of organic contamination to soil remediation state,
Include:
Acquiring video information unit, the image letter of the vegetation for shooting soil region to be detected using unmanned plane mode
Breath, obtains video information；
ARM unit, the video information for being obtained according to the acquiring video information unit carry out the reparation state of soil
Detection；
Intelligent identification unit restores after by the pollution of different organic pollutants for the vegetation according to the pre-stored data
Feature is compared with the result of the ARM unit, so that it is determined that the possibility type of organic pollutant.
Preferably, the acquiring video information unit includes:
Latitude and longitude information obtains subelement, for obtaining the latitude and longitude information at each moment；
Soil remediation state determines subelement, for determining soil remediation state.
Preferably, the latitude and longitude information acquisition subelement includes:
It corrects video information image-latitude and longitude information packet and obtains module, for obtaining the vegetation of soil region to be detected
Video information is corrected, and the corresponding latitude and longitude information of video information after being corrected, according to the video information after correction
Image-latitude and longitude information packet.
Preferably, the soil remediation state determines subelement according to video information image-latitude and longitude information after correction
Packet carries out the determination of soil remediation state.
Preferably, the correction video information image-latitude and longitude information packet acquisition module includes:
Assuming that the T0 moment, the T1 moment, the T2 moment ..., the Tn moment be corresponding n+1 consecutive hours in the video information
It carves, wherein n is the natural number greater than 4；
The video information at T0 and T1 moment is converted to image respectively for carrying out framing to video information by framing module
Information Img0 and Img1, and obtain the correction coefficient of low frequency sub-band signal and the correction coefficient of high frequency subband signals；
Low frequency sub-band signal correction module, for according to the correction coefficient of low frequency sub-band signal and the school of high frequency subband signals
Positive coefficient, to the T2 moment ..., the video information at Tn moment is corrected；
Sorting module, for the corrected T0 moment, the T1 moment, the T2 moment ..., the video information at Tn moment into
Row sequence；
Video information image-latitude and longitude information packet generation module, for generating video information image-latitude and longitude information packet.
Preferably, the framing module includes:
First subband signal obtains submodule and is corresponding in turn to for carrying out wavelet transformation respectively to Img0 and Img1
In the low frequency sub-band signal L at T0 moment and T1 moment0, high frequency subband signals L1And high frequency subband signals H0, high frequency subband signals
H1；
Low frequency sub-band signal correction coefficient computational submodule, for calculating the correction coefficient C (x, y) of low frequency sub-band signalL:
Wherein, the x and y respectively indicates the abscissa and ordinate of some pixel in the frame image at T0 moment, βmIt indicates
The mean value of correction matrix, ηmIndicate correction matrix variance, the correction matrix be withFor variance,For mean value
2 rank diagonal matrix B；
Submodule is filtered, for, by Gaussian filter, obtaining H ' to high frequency subband signals0And H '1:
High frequency subband signals correction coefficient computational submodule calculates for the frame image for the T0 moment and is located at the position (x, y)
The correction coefficient C (x, y) of the high frequency subband signals for the pixel setH:
Wherein SδIndicate centered on (x, y),For the area in the circle domain of radius, the modulus value of D representing matrix A
Upper integer, A indicate following matrix:
Wherein i is the lower integer of the modulus value of matrix A.
Preferably, the low frequency sub-band signal correction module includes:
Second subband signal obtains submodule, for the T2 moment ..., the video information at Tn moment carry out small echo change
It changes, respectively obtains and the one-to-one high frequency subband signals of these video informations and low frequency sub-band signal；
First high frequency correction submodule, for these high frequency subband signals for its correspondence at the time of video information in
Each point, with C (x, y)HSubtract each other；
Second high frequency correction submodule, for these low frequency sub-band signals for its correspondence at the time of video information in
Each point, with C (x, y)LSubtract each other；
It corrects video information and obtains submodule, for passing through the high frequency subband signals subtracted each other and low frequency sub-band signal for above-mentioned
At the time of according to its correspondence, carry out wavelet inverse transformation respectively, obtain with the corrected T2 moment ..., the video at Tn moment
Information.
Preferably, above-mentioned sorting module includes:
Record sub module, for recording in above-mentioned correction course, corrected each high frequency subband signals；
Convolution submodule, for each high frequency subband signals according to chronological order, to be carried out convolution two-by-two；
Median computational submodule, for calculating the median of convolution value；
Minimum convoluted value determines submodule, for the determining the smallest convolution value of absolute value of the difference with the median；
Reference video information determines submodule, for determine it is corresponding with the smallest convolution value of the absolute value, according to when
Between sequentially come subsequent video information, as the T0 moment, the T1 moment, the T2 moment ..., in this n+1 moment at Tn moment
Reference video information.
Preferably, the video information image-latitude and longitude information packet generation module includes:
Submodule is encapsulated, for corresponding latitude and longitude information in video information to be sealed with it by the reference video information
Dress；
Sending submodule, for transmitting the information after the encapsulation.
Preferably, the soil remediation state determines that subelement includes:
Receiving submodule obtains reference video information and matched for receiving the information after encapsulation and unlocking
Latitude and longitude information；
Vegetation identifies submodule, for carrying out vegetation identification to reference video information in the way of machine learning；
Growth characteristics identify submodule, for carrying out growth characteristics identification to the vegetation identified；
Detection sub-module, for being compared according to the growth characteristics identified with reference to growth characteristics, when lower than threshold value
Or when being higher than threshold value, it is determined as soil restoration exception.
Preferably, the growth characteristics include: leaf color, plant trunk, trunk diameter.
The above-described embodiments merely illustrate the principles and effects of the present invention, and is not intended to limit the present invention.It is any ripe
The personage for knowing this technology all without departing from the spirit and scope of the present invention, carries out modifications and changes to above-described embodiment.Cause
This, institute is complete without departing from the spirit and technical ideas disclosed in the present invention by those of ordinary skill in the art such as
At all equivalent modifications or change, should be covered by the claims of the present invention.
Claims (10)
1. a kind of soil remediation condition intelligent detection device, for the improvement to forest farm or pasture by the soil of organic contamination
Soil remediation state is monitored in the process, comprising:
Acquiring video information unit, the image information of the vegetation for being shot soil region to be detected using unmanned plane mode, is obtained
To video information；
ARM unit, the video information for being obtained according to the acquiring video information unit carry out the inspection of the reparation state of soil
It surveys；
Intelligent identification unit, the spy restored after by the pollution of different organic pollutants for the vegetation according to the pre-stored data
Sign, is compared, so that it is determined that the possibility type of organic pollutant with the result of the ARM unit.
2. equipment according to claim 1, which is characterized in that the acquiring video information unit includes:
Latitude and longitude information obtains subelement, for obtaining the latitude and longitude information at each moment；
Soil remediation state determines subelement, for determining soil remediation state.
3. equipment according to claim 2, which is characterized in that the latitude and longitude information obtains subelement and includes:
It corrects video information image-latitude and longitude information packet and obtains module, the video of the vegetation for obtaining soil region to be detected
Information is corrected, and the corresponding latitude and longitude information of video information after being corrected, according to the video information image-after correction
Latitude and longitude information packet.
4. equipment according to claim 3, which is characterized in that after the soil remediation state determines subelement according to correction
Video information image-latitude and longitude information packet carry out soil remediation state determination.
5. equipment according to claim 4, which is characterized in that the correction video information image-latitude and longitude information packet obtains
Obtaining module includes:
Assuming that the T0 moment, the T1 moment, the T2 moment ..., the Tn moment be corresponding n+1 continuous moment in the video information,
Wherein n is the natural number greater than 4；
The video information at T0 and T1 moment is converted to image information respectively for carrying out framing to video information by framing module
Img0 and Img1, and obtain the correction coefficient of low frequency sub-band signal and the correction coefficient of high frequency subband signals；
Low frequency sub-band signal correction module, for according to the correction coefficient of low frequency sub-band signal and the correction system of high frequency subband signals
Number, to the T2 moment ..., the video information at Tn moment is corrected；
Sorting module, for the corrected T0 moment, the T1 moment, the T2 moment ..., the video information at Tn moment arranges
Sequence；
Video information image-latitude and longitude information packet generation module, for generating video information image-latitude and longitude information packet.
6. equipment according to claim 5, which is characterized in that the framing module includes:
First subband signal obtains submodule and obtains being corresponding in turn in T0 for carrying out wavelet transformation respectively to Img0 and Img1
The low frequency sub-band signal L at moment and T1 moment0, high frequency subband signals L1And high frequency subband signals H0, high frequency subband signals H1；
Low frequency sub-band signal correction coefficient computational submodule, for calculating the correction coefficient C (x, y) of low frequency sub-band signalL:
Wherein, the x and y respectively indicates the abscissa and ordinate of some pixel in the frame image at T0 moment, βmIndicate amendment square
The mean value of battle array, ηmIndicate correction matrix variance, the correction matrix be withFor variance,For 2 ranks of mean value
Diagonal matrix B；
Submodule is filtered, for, by Gaussian filter, obtaining H ' to high frequency subband signals0And H '1:
High frequency subband signals correction coefficient computational submodule calculates for the frame image for the T0 moment and is located at the position (x, y)
The correction coefficient C (x, y) of the high frequency subband signals of pixelH:
Wherein SδIndicate centered on (x, y),For the area in the circle domain of radius, the modulus value of D representing matrix A it is upper whole
Number, A indicate following matrix:
Wherein i is the lower integer of the modulus value of matrix A.
7. equipment according to claim 6, which is characterized in that the low frequency sub-band signal correction module includes:
Second subband signal obtains submodule, for the T2 moment ..., the video information at Tn moment carry out wavelet transformation, point
It does not obtain and the one-to-one high frequency subband signals of these video informations and low frequency sub-band signal；
First high frequency correction submodule, for these high frequency subband signals for its correspondence at the time of video information in it is each
It is a, with C (x, y)HSubtract each other；
Second high frequency correction submodule, for these low frequency sub-band signals for its correspondence at the time of video information in it is each
It is a, with C (x, y)LSubtract each other；
Correct video information and obtain submodule, for by it is above-mentioned through the high frequency subband signals that subtracting each other and low frequency sub-band signal according to
At the time of it is corresponded to, carry out wavelet inverse transformation respectively, obtain with the corrected T2 moment ..., the video information at Tn moment.
8. equipment according to claim 7, which is characterized in that above-mentioned sorting module includes:
Record sub module, for recording in above-mentioned correction course, corrected each high frequency subband signals；
Convolution submodule, for each high frequency subband signals according to chronological order, to be carried out convolution two-by-two；
Median computational submodule, for calculating the median of convolution value；
Minimum convoluted value determines submodule, for the determining the smallest convolution value of absolute value of the difference with the median；
Reference video information determines submodule, corresponding with the smallest convolution value of the absolute value, suitable according to the time for determination
Sequence comes subsequent video information, as the T0 moment, the T1 moment, the T2 moment ..., the reference in this n+1 moment at Tn moment
Video information.
9. equipment according to claim 8, which is characterized in that the video information image-latitude and longitude information packet generates mould
Block includes:
Submodule is encapsulated, for corresponding latitude and longitude information in video information to be packaged with it by the reference video information；
Sending submodule, for transmitting the information after the encapsulation.
10. equipment according to claim 9, which is characterized in that the soil remediation state determines that subelement includes:
Receiving submodule obtains reference video information and matched warp for receiving the information after encapsulating and unlocking
Latitude information；
Vegetation identifies submodule, for carrying out vegetation identification to reference video information in the way of machine learning；
Growth characteristics identify submodule, for carrying out growth characteristics identification to the vegetation identified；
Detection sub-module, for being compared according to the growth characteristics that identify with reference to growth characteristics, when be lower than threshold value or
When higher than threshold value, it is determined as soil restoration exception.
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| 肖武、胡振琪等: ""无人机遥感在矿区监测与土地复垦中的应用前景"", 《中国矿业》 * |
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