CN107290309A - Field rice mildew automatic detection device and detection method based on fluorescence imaging - Google Patents
Field rice mildew automatic detection device and detection method based on fluorescence imaging Download PDFInfo
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- CN107290309A CN107290309A CN201710382321.6A CN201710382321A CN107290309A CN 107290309 A CN107290309 A CN 107290309A CN 201710382321 A CN201710382321 A CN 201710382321A CN 107290309 A CN107290309 A CN 107290309A
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- G—PHYSICS
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- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N21/00—Investigating or analysing materials by the use of optical means, i.e. using sub-millimetre waves, infrared, visible or ultraviolet light
- G01N21/62—Systems in which the material investigated is excited whereby it emits light or causes a change in wavelength of the incident light
- G01N21/63—Systems in which the material investigated is excited whereby it emits light or causes a change in wavelength of the incident light optically excited
- G01N21/64—Fluorescence; Phosphorescence
- G01N21/6428—Measuring fluorescence of fluorescent products of reactions or of fluorochrome labelled reactive substances, e.g. measuring quenching effects, using measuring "optrodes"
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- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N21/00—Investigating or analysing materials by the use of optical means, i.e. using sub-millimetre waves, infrared, visible or ultraviolet light
- G01N21/62—Systems in which the material investigated is excited whereby it emits light or causes a change in wavelength of the incident light
- G01N21/63—Systems in which the material investigated is excited whereby it emits light or causes a change in wavelength of the incident light optically excited
- G01N21/64—Fluorescence; Phosphorescence
- G01N21/645—Specially adapted constructive features of fluorimeters
- G01N21/6456—Spatial resolved fluorescence measurements; Imaging
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- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N21/00—Investigating or analysing materials by the use of optical means, i.e. using sub-millimetre waves, infrared, visible or ultraviolet light
- G01N21/62—Systems in which the material investigated is excited whereby it emits light or causes a change in wavelength of the incident light
- G01N21/63—Systems in which the material investigated is excited whereby it emits light or causes a change in wavelength of the incident light optically excited
- G01N21/64—Fluorescence; Phosphorescence
- G01N21/6428—Measuring fluorescence of fluorescent products of reactions or of fluorochrome labelled reactive substances, e.g. measuring quenching effects, using measuring "optrodes"
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Abstract
The invention discloses a kind of field rice mildew automatic detection device based on fluorescence imaging, including：Detection platform, bottom, which is provided with, is controlled by control module walking mechanism；Locating module, on platform, obtains the positional information of detection means and is sent to control module in real time；Fluorescence imaging module, on platform, gathers the fluoroscopic image of field rice and is sent to data processing module；Data processing module, extracts the characteristic parameter of the fluoroscopic image, judges the health status of field rice；Control module, according to default detection parameter and using being spaced, controls the sampling of fluorescence imaging module；The positional information of locating module acquisition is received simultaneously and is analyzed, and generates travel commands with reference to default walking path, and travel commands are sent to the walking mechanism.The automatic detection device can realize the automatic detection of field rice mildew.The invention also discloses the field rice mildew automated detection method based on fluorescence imaging.
Description
Technical field
The present invention relates to Imaging-PAM field, more particularly to a kind of field rice mildew based on fluorescence imaging are automatic
Change detection means and detection method.
Background technology
In recent years, application of the imaging technique in agricultural production is further extensive, and wherein Imaging-PAM is research luminous energy
The inherent probe of distribution, is the effective means for studying crop photosynthesis characteristic.When plant growth is by arid, a cold, huge sum of money
During the environment-stress such as category, obvious change can occur for Change of Chlorophyll Fluorescence Kinetics Parameters, by the analysis to a variety of Change of Chlorophyll Fluorescence Kinetics Parameters,
It may determine that whether photosynthetic performance, the growing state of crop are good.Therefore, health monitoring of the Imaging-PAM in crop, product
Plant in the fields such as screening and phenotypic analysis and show huge application value.
With the propulsion of industrial automation process, people require more and more higher to the automaticity of detecting instrument, automatically
It is turned into the final developing direction that industry is each detection device.It is by fluorescence imaging mostly in existing fluorescence imaging detection device
Equipment is equipped in detection platform, it is necessary to which detection device is put to crop area to be detected and carries out detection and localization.Such as publication No. CN
A kind of plant disease detection method based on chlorophyll fluorescence and imaging technique disclosed in 104034710 A Chinese patent literature
And device, applicable object is not suitable for field Fields detection based on the single plant sample of small size.For the field of large area
Crop, commonly uses the fluorescence imaging information that Technology of low altitude remote sensing obtains crop, but the technology use cost is larger, data precision has
Limit, and need to carry out spatial domain request for utilization in advance.Therefore, it is necessary to improve automaticity and the behaviour of fluorescence field detection device
Make simplicity, expand the use scope during it is detected in the wild.
Automatic navigation technology as precision agriculture a core key technology, be widely used in crop sowing, weeding,
In the agricultural production processes such as fertilising, spray, harvesting.It can be the information such as path, the position needed for mechanical device provides movement,
Mechanical device is set to be travelled according to optimal path, the field detection range of expansion instrument, and simplify detection process, reduction operating personnel
Labor intensity.
The content of the invention
, can be real it is an object of the invention to provide a kind of field rice mildew automatic detection device based on fluorescence imaging
The automatic detection of existing field rice mildew, reduces the labor intensity of operating personnel.
A kind of field rice mildew automatic detection device based on fluorescence imaging, including：
Detection platform, bottom is provided with walking mechanism, and the walking mechanism is controlled by control module；
Locating module, on platform, obtains the positional information of detection means and is sent to control module in real time；
Fluorescence imaging module, on platform, gathers the fluoroscopic image of field rice and is sent to data processing module；
Data processing module, extracts the characteristic parameter of the fluoroscopic image, judges the health status of field rice；
Control module, according to default detection parameter and using being spaced, controls the sampling of fluorescence imaging module；Receive simultaneously
The positional information that locating module is obtained simultaneously is analyzed, and travel commands are generated with reference to default walking path, and by travel commands
It is sent to the walking mechanism.
Imaging-PAM and automatic navigation technology are combined by the present invention, realize the field rice based on fluorescence imaging
Mildew automatic detection, improves the automaticity and ease-to-operate of fluorescence field detection device, expands it and detect in the wild
In use scope.
In order to adapt to paddy-field-working, described walking mechanism includes at least four road wheel, and described road wheel has anti-skidding
Structure.Anti-skid structure can use prior art.
Each road wheel is independent automatically controlled type of drive, is independently controllable by self-navigation module, realizes self-navigation row
Walk.
Preferably, the height of the detection platform and across the row spacing degree of walking mechanism are adjustable.Can be according to different growth steps
The paddy rice of section highly adjusts the height of fluorescence imaging module, according to across row spacing degree of the plantation ridge of paddy rice away from regulation walking mechanism.
The method of self-navigation has a lot, navigated using every kind of single alignment system have it is respective unique and
Several different alignment systems, can be grouped together into the higher integrated positioning system of the degree of accuracy by limitation.
Preferably, described locating module includes being integrated positioning system.
It is further preferred that described integrated positioning system includes：
GPS positioning system, obtains absolute location coordinates, course heading and the travel speed of automatic detection device；
Machine vision alignment system, gathers the image information in front of automatic detection device and is handled, and obtains automatic
Change the image coordinate information of detection means.
In rice field, the border of paddy rice row sometimes and non-rectilinear, is used alone GPS and navigated, it is determined that the base that navigates
There is certain error in terms of directrix；Vision guided navigation can go out the characteristic information of current paddy rice row with extract real-time, improve positioning
Precision, but when being single use vision guided navigation, it sometimes appear that the situation of missing inspection in image processing process, therefore by GPS and
Vision guided navigation combines, and two kinds of navigation informations complement each other, and may make up a kind of redundancy and higher multi-functional of the degree of accuracy is led
Boat system.
Wherein, GPS location part is mainly to provide absolute location coordinates, course heading and the travel speed of detection means；
Machine vision position portion is that the image that will be collected passes through image preprocessing, obtains the relative position of known point in guidance path
Coordinate, by under two group informations unification to the same coordinate system, obtains new positional information.
Described GPS positioning system is Big Dipper GPS navigation system；Described machine vision alignment system is imaged by head
Machine carries out IMAQ to the path in front of automatic detection device.
Described fluorescence imaging module includes：
Excitation source, excites field rice to be measured to send fluorescence,
Phosphorimager, for gathering the fluoroscopic image of field rice and being sent to data processing module.
Preferably, described excitation source includes the lumiere blue diode array equidistantly arranged by Back Word type.
Lumiere blue diode is equidistantly arranged by Back Word type, forms collimating optics correcting structure, can be in operating distance
Produce uniform illumination.
The invention also discloses a kind of field rice mildew automated detection method based on fluorescence imaging, including：
(1) paddy rice for planting in field by row is as object to be measured, operating distance, detection parameter to fluorescence imaging module
And image acquisition interval is configured；
(2) walking mechanism is controlled by control module, is walked according to default walking path self-navigation；
(3) in the process of walking, fluorescence imaging module gathers the fluoroscopic image of paddy rice to be measured and is sent to data processing mould
Block；
(4) data processing module extracts the characteristic parameter of the fluoroscopic image, judges the health status of paddy rice to be measured.
Described field rice mildew includes the diseases as caused by mould such as downymildewofrice, head blight, gray mold.
Preferably, the automatic detection time to field rice mildew is night.
Due to carrying out usually requiring to carry out plant the dark adaptation of a period of time before fluoroscopic image collection to plant, and for
The long-term cropping of large area can not generally meet the condition requirement of dark adaptation on daytime, therefore selection night is checked.
In step (1), fluorescence imaging module uses tight shot, and best effort distance is 20cm, regulation excitation source
Intensity of illumination, be specially：Measure 1 μm of ol (photons)/m of luminous intensity ＜2.s, saturation luminous intensity is 4000 μm of ol
(photons)/m2.s, photochemical luminous intensity is the intensity of illumination in paddy growth environment；Image acquisition interval is according to traveling
During stroke distances, gait of march and sampling number be configured.
The self-navigation of step (2) includes：
(i) machine vision alignment system obtains the image of detection means forward path, is extracted and led by image processing techniques
Position of the course line characteristic point in image coordinate；Meanwhile, GPS positioning system obtain in real time detection means absolute location coordinates,
Course heading and travel speed；
(ii) what the positional information and GPS positioning system of the navigation line feature point obtained to machine vision alignment system were obtained
The positional information of detection means carries out Coordinate Conversion and filtering process, obtains final navigate line feature point and the seat of detection means
Information is marked, is navigated according to default walking path.
Wherein, in step (i), machine vision alignment system obtains the image of detection means forward path, at image
Reason technology extracts position of the navigation line feature point in image coordinate, including：
(i-1) the path image information in front of detection means is acquired；
(i-2) grey linear transformation is carried out to gathered path image, to strengthen the contrast of paddy rice and field；
(i-3) using paddy rice as area-of-interest to be extracted, using fixed threshold method to the gray-scale map that is obtained after conversion
As being split；
(i-4) noise is removed using morphology opening operation and closed operation to the image after segmentation；
(i-5) using Hough transform algorithm to obtaining leading line except the paddy rice row in the image after making an uproar carries out fitting a straight line,
Using leading line midpoint as delegated path information navigation line feature point.
What machine vision alignment system was obtained is the relative coordinate position of navigation line feature point, by entering to monopod video camera
Rower is determined, and is changed navigation line feature point to world coordinate system by its inside and outside parameter；GPS positioning system can be obtained from real time
The earth coordinates position of dynamicization detection means and course heading；Machine vision alignment system and GPS positioning system are obtained
Positional information is unified under earth coordinates.Filtering process is carried out after Coordinate Conversion.
Preferably, in step (ii), described filtering process is using global multi tate expanded Kalman filtration algorithm.
Kalman filtering algorithm can go over to research object, the state of the present and the future makes linear optimal estimation, be suitable to
The real time fusion for the positional information that alignment system is obtained in dynamic environment.
In step (3), described fluoroscopic image includes the maximum light after paddy rice dark adaptation to be measured and efficiency imaging Fv/Fm,
Non- Photochemical quenching imaging NPQ and photosynthetic electron transfer speed imaging ETR.
In step (4), described characteristic parameter is the average gray value and textural characteristics of each fluoroscopic image, the texture
Feature includes standard deviation, smoothness, third moment, uniformity and entropy.
Compared with prior art, beneficial effects of the present invention are：
(1) present invention detects integrated navigation and location Technology application in application in the field of fluorescence imaging, by navigation
The positional information of route is extracted, and realizes the automatic running of fluorescence imaging field detection device, and overcoming in generally detection needs
The drawbacks of detection means artificially is moved into target location, improves the automaticity of detection means, is the field of large area
Experiment is provided convenience；
(2) due to the particular surroundings of rice terrace, the accurate of common detection means large area Rice information relatively difficult to achieve is obtained
Take, field detection device provided by the present invention is suitable for the particular surroundings of rice terrace, using automatic navigation technology, realizes field
The large area quick detection of paddy rice；
(3) field fluorescence imaging detection device provided by the present invention, with it is simple in construction, easy to operate the features such as, can
The paddy rice of different growth phases is detected, use value of the Imaging-PAM in agricultural production application is improved.
Brief description of the drawings
Fig. 1 is the structural representation of the field rice mildew automatic detection device of the invention based on fluorescence imaging；
Fig. 2 is the internal structure schematic diagram of detection platform.
Embodiment
The present invention is described in further detail with reference to the accompanying drawings and examples.
As shown in figure 1, the field rice mildew automatic detection device of the invention based on fluorescence imaging includes：Installation is expert at
Walk the detection platform 2 in mechanism 1, the Big Dipper GPS positioning system 31 above detection platform and machine vision alignment system
32nd, the phosphorimager 62 and excitation source 61 below detection platform, the power supply 3 inside detection platform, control
Device 4 and data processor 5 processed.
Walking mechanism 1 includes walker and the anti-skid wheel 13 installed in walker bottom, and walker is by two triangles
Support frame 12 and crossbeam 11 are constituted, and are suitable for the complicated landform of rice terrace.
The top of two triangular support brackets 12 is enclosed on crossbeam 11, can on crossbeam 11 triangular support bracket 12 of slidable adjustment two
The distance between, so as to the plantation ridge according to paddy rice away from difference, regulation two triangular support brackets 12 between across row spacing degree.
Detection platform 2 is arranged by elevating lever 7 and is fixed on crossbeam 11, lateral attitude of the detection platform 2 on crossbeam 11
It can adjust, the height of detection platform 2 can be adjusted by elevating lever 7.Therefore, can be according to the height of the paddy rice of different growth phases
Detection platform 1 is adjusted degree.
Two bottoms of triangular support bracket 12 are separately installed with two anti-skid wheels 13, and each anti-skid wheel 13 is only
Vertical automatically controlled type of drive, is controlled by controller, realizes that self-navigation is walked.
The top of detection platform 2 is provided with Big Dipper GPS positioning system 31 and machine vision alignment system 32, machine vision positioning
System includes monopod video camera.GPS location part is mainly to provide absolute location coordinates, course heading and the traveling of detection means
Speed；Machine vision position portion is that the image for collecting monopod video camera passes through image preprocessing, is obtained in guidance path
The relative position coordinates of known point, by under two group informations unification to the same coordinate system, obtain new positional information, and be sent to
Control module.
The lower section of detection platform 2 is provided with phosphorimager 62 and excitation source 61.Excitation source 61 is installed in LED/light source
There is a hollow out circular hole at high-power light-emitting blue diode array on plate, light source board center, and phosphorimager 62 is installed on this circle
Fluoroscopic image collection is carried out in hole, blue diode presses three-back-shaped equidistant arrangement centered on circular hole.
As shown in Fig. 2 the inside of detection platform 1 is provided with power supply 3, controller 4 and data processor 5.
Controller 4 controls the sampling of phosphorimager 62 according to default detection parameter and using being spaced；North is received simultaneously
Bucket GPS positioning system 31 and the positional information that obtains in real time of machine vision alignment system 32 are simultaneously analyzed, with reference to default row
Coordinates measurement travel commands are walked, and travel commands are sent to anti-skid wheel 13.
Data processor 5 extracts the characteristic parameter of fluoroscopic image, judges the health status of field rice.
Power supply 3 provides electric power for detection means.
The method for detecting field rice mildew using above-mentioned automatic detection device includes：
(1) it is high according to the growth of paddy rice according to the plantation ridge of paddy rice away from the width between two triangular support brackets 12 of regulation
Operating distance is set to 20cm by degree, adjustment detection platform 2 to the operating distance of rice canopy；
(2) the optimum detection parameter and sampling time interval of phosphorimager 62 are set：The intensity of excitation source is adjusted, point
It is not：Measure 1 μm of ol (photons)/m of luminous intensity ＜2.s, 4000 μm of ol (photons)/m of saturation luminous intensity2.s, photochemical light intensity
Spend for the intensity of illumination in paddy growth environment.Stroke distances, gait of march and sampling number in traveling process are set
Put the sampling interval duration of detection means；
(3-1) monopod video camera obtains the path image in front of detection means, carries out successively：
Grey linear transformation is carried out to path image, to strengthen the contrast of paddy rice and field；
Using paddy rice as area-of-interest to be extracted, the gray level image obtained after conversion is carried out using fixed threshold method
Segmentation；
Noise is removed using morphology opening operation and closed operation to the image after segmentation；
Using Hough transform algorithm to obtaining leading line except the paddy rice row in the image after making an uproar carries out fitting a straight line, it will lead
Course line midpoint as delegated path information navigation line feature point；
By carrying out parameter calibration to monopod video camera, the position in the navigation alive boundary's coordinate system of line feature point is obtained；
(3-2) GPS positioning system 31 obtains position of the detection means in earth coordinates in real time；
Position and detection means in the acquisition navigation alive boundary's coordinate system of line feature point of (3-3) controller 4 are sat in the earth
Position in mark system, two kinds of positions are unified in earth coordinates, then using global multi tate expanded Kalman filtration algorithm
GMEKF is merged, and generates the location information of final detection means；
(4) controller 4 controls the track route of detection means according to the positional information of navigation line feature point, in walking process
In, the peace of phosphorimager 62 is acquired according to default detection parameter and time interval to the fluoroscopic image of paddy rice；What is gathered is glimmering
Light image includes the maximum light after paddy rice dark adaptation to be measured and efficiency imaging Fv/Fm, non-Photochemical quenching imaging NPQ and photosynthetic electricity
Sub- transfer rate is imaged ETR；
(5) data processor 5 extracts the characteristic parameter of fluoroscopic image, and characteristic parameter includes the average gray value of fluoroscopic image
And textural characteristics, textural characteristics include standard deviation, smoothness, third moment, uniformity and entropy；The characteristic parameter extracted is made
For input variable, judged using the Decision Tree Algorithm established in advance whether paddy rice to be measured catches an illness, so as to realize
The automatic detection of field rice mildew.
Paddy rice mildew includes the diseases as caused by mould such as downymildewofrice, head blight, gray mold.
The automatic detection time to field rice mildew is night.
Claims (10)
1. a kind of field rice mildew automatic detection device based on fluorescence imaging, it is characterised in that including：
Detection platform, bottom is provided with walking mechanism, and the walking mechanism is controlled by control module；
Locating module, on platform, obtains the positional information of detection means and is sent to control module in real time；
Fluorescence imaging module, on platform, gathers the fluoroscopic image of field rice and is sent to data processing module；
Data processing module, extracts the characteristic parameter of the fluoroscopic image, judges the health status of field rice；
Control module, according to default detection parameter and using being spaced, controls the sampling of fluorescence imaging module；Positioning is received simultaneously
The positional information of module acquisition is simultaneously analyzed, and generates travel commands with reference to default walking path, and travel commands are sent
To the walking mechanism.
2. the field rice mildew automatic detection device according to claim 1 based on fluorescence imaging, it is characterised in that
Described locating module includes integrated positioning system.
3. the field rice mildew automatic detection device according to claim 2 based on fluorescence imaging, it is characterised in that
Described integrated positioning system includes：
GPS positioning system, obtains absolute location coordinates, course heading and the travel speed of automatic detection device；
Machine vision alignment system, gathers the image information in front of automatic detection device and is handled, and obtains automation inspection
Survey the image coordinate information of device.
4. the field rice mildew automatic detection device according to claim 1 based on fluorescence imaging, it is characterised in that
Described fluorescence imaging module includes：
Excitation source, excites field rice to be measured to send fluorescence,
Phosphorimager, for gathering the fluoroscopic image of field rice and being sent to data processing module.
5. the field rice mildew automatic detection device according to claim 4 based on fluorescence imaging, it is characterised in that
Described excitation source includes the lumiere blue diode array equidistantly arranged by Back Word type.
6. a kind of field rice mildew automated detection method based on fluorescence imaging, it is characterised in that including：
(1) using field by the paddy rice of row plantation as object to be measured, operating distance, detection parameter to fluorescence imaging module and
Image acquisition interval is configured；
(2) walking mechanism is controlled by control module, is walked according to default walking path self-navigation；
(3) in the process of walking, fluorescence imaging module gathers the fluoroscopic image of paddy rice to be measured and is sent to data processing module；
(4) data processing module extracts the characteristic parameter of the fluoroscopic image, judges the health status of paddy rice to be measured.
7. the field rice mildew automated detection method according to claim 6 based on fluorescence imaging, it is characterised in that
The self-navigation of step (2) includes：
(i) machine vision alignment system obtains the image of detection means forward path, and leading line is extracted by image processing techniques
Position of the characteristic point in image coordinate；Meanwhile, GPS positioning system obtains the absolute location coordinates of detection means, course in real time
Angle and travel speed；
(ii) detection that the positional information and GPS positioning system of the navigation line feature point obtained to machine vision alignment system are obtained
The positional information of device carries out Coordinate Conversion and filtering process, obtains final navigate line feature point and the coordinate letter of detection means
Breath, is navigated according to default walking path.
8. the field rice mildew automated detection method according to claim 7 based on fluorescence imaging, it is characterised in that
In step (i), machine vision alignment system obtains the image of detection means forward path, is extracted and navigated by image processing techniques
Position of the line feature point in image coordinate, including：
(i-1) the path image information in front of detection means is acquired；
(i-2) grey linear transformation is carried out to gathered path image, to strengthen the contrast of paddy rice and field；
(i-3) using paddy rice as area-of-interest to be extracted, the gray level image obtained after conversion is entered using fixed threshold method
Row segmentation；
(i-4) noise is removed using morphology opening operation and closed operation to the image after segmentation；
(i-5) it will be led using Hough transform algorithm to obtaining leading line except the paddy rice row in the image after making an uproar carries out fitting a straight line
Course line midpoint as delegated path information navigation line feature point.
9. the field rice mildew automated detection method according to claim 7 based on fluorescence imaging, it is characterised in that
In step (ii), described filtering process is using global multi tate expanded Kalman filtration algorithm.
10. the field rice mildew automated detection method according to claim 6 based on fluorescence imaging, its feature exists
In in step (4), described characteristic parameter is the average gray value and textural characteristics of each fluoroscopic image, the textural characteristics
Including standard deviation, smoothness, third moment, uniformity and entropy.
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| CN112408428A (en) * | 2020-12-08 | 2021-02-26 | 大连盐化集团有限公司 | Salt field slag breaking method |
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