CN105548124A - Method and device for detecting citrus canker - Google Patents

Method and device for detecting citrus canker Download PDF

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Publication number
CN105548124A
CN105548124A CN201610068533.2A CN201610068533A CN105548124A CN 105548124 A CN105548124 A CN 105548124A CN 201610068533 A CN201610068533 A CN 201610068533A CN 105548124 A CN105548124 A CN 105548124A
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fluorescence
disease
citrus
image
tangerines
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CN105548124B (en
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岑海燕
翁海勇
高大海
刘飞
何勇
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Zhejiang University ZJU
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Zhejiang University ZJU
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    • GPHYSICS
    • G01MEASURING; TESTING
    • G01NINVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N21/00Investigating or analysing materials by the use of optical means, i.e. using sub-millimetre waves, infrared, visible or ultraviolet light
    • G01N21/62Systems in which the material investigated is excited whereby it emits light or causes a change in wavelength of the incident light
    • G01N21/63Systems in which the material investigated is excited whereby it emits light or causes a change in wavelength of the incident light optically excited
    • G01N21/64Fluorescence; Phosphorescence
    • G01N21/6486Measuring fluorescence of biological material, e.g. DNA, RNA, cells
    • GPHYSICS
    • G01MEASURING; TESTING
    • G01NINVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N21/00Investigating or analysing materials by the use of optical means, i.e. using sub-millimetre waves, infrared, visible or ultraviolet light
    • G01N21/84Systems specially adapted for particular applications
    • GPHYSICS
    • G01MEASURING; TESTING
    • G01NINVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N21/00Investigating or analysing materials by the use of optical means, i.e. using sub-millimetre waves, infrared, visible or ultraviolet light
    • G01N21/17Systems in which incident light is modified in accordance with the properties of the material investigated
    • G01N2021/1765Method using an image detector and processing of image signal
    • GPHYSICS
    • G01MEASURING; TESTING
    • G01NINVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N21/00Investigating or analysing materials by the use of optical means, i.e. using sub-millimetre waves, infrared, visible or ultraviolet light
    • G01N21/84Systems specially adapted for particular applications
    • G01N2021/8466Investigation of vegetal material, e.g. leaves, plants, fruits

Abstract

The invention relates to a method for detecting citrus canker. The method comprises the following steps: carrying out dark adaptation treatment, obtaining fluorescence information and an RGB (Red, Green and Blue) image by using a chlorophyll fluorescence imager and an RGB camera, and computing chlorophyll fluorescence parameters, color features and textural features; distinguishing whether citrus is infected with a disease or not by utilizing a PLS (Partial Least Squares) discriminant analysis model; reading a fluorescence image of a to-be-detected citrus which is infected with the disease, analyzing and computing the area of the disease by applying a Gaussian mixture model, and realizing quantitative analysis on infecting degree. The invention also relates to a device for detecting the citrus canker. According to the method and the device for detecting the citrus canker, disclosed by the invention, citrus fruit canker in different growing periods of a young fruit period, a fruit greening period and a fruit ripening period and in different infecting degrees can be continuously and automatically detected by blending a chlorophyll fluorescence imaging technology with an RGB imaging technology.

Description

A kind of detection method of citrus bacterial canker disease and device
Technical field
The present invention relates to the detection field of plant canker, be specifically related to a kind of detection method and device of citrus bacterial canker disease.
Background technology
Citrus bacterial canker disease is one of the most serious bacterial disease of oranges and tangerines, and therefore orchard worker suffers serious economic loss, in commerce and trade activity, be listed in mandatory quarantinable disease.Under field conditions (factors), this germ can be propagated with wind and rain, be spread, main infection way is pore, hole skin or wound, the blade of plant, base of leaf, branch and fruit can be infected, cause the weak and withered of plant, can cause when serious that plant is fallen leaves in a large number, shedding, even complete stool is dead; Even if catch an illness, fruit does not come off, and can form cracking at its epidermis yet, scab shape ulceration, greatly reduces the outward appearance of fruit, product phase, causes harmful effect to its sale and outlet.And this pathogen transmission ability is strong, once occur in new district, then needs a large amount of manpower and materials to prevent and treat, cause very large economic loss.
At present, the lossless detection method of citrus bacterial canker disease mainly comprises RGB imaging technique, thermal infrared imaging and high light spectrum image-forming technology, and detected object mainly concentrates on the fruit in Citrus leaf and maturity stage, the research of catching an illness to young fruit period and Chinese olive phase citrusfruit is less.RGB imaging detection technology is only applicable to after disease manifests, but now late to the control of the state of an illness; The accuracy rate of thermal infrared imaging detection technique is easily subject to the impact of external environment (as weather conditions, Measuring Time and temperature etc.); The high light spectrum image-forming combine with technique advantage of traditional images technology and spectral technique, spatial information and the spectral information of sample can be obtained simultaneously, but because the data volume of high spectrum image is huge, data redundancy serious, be mainly used in the off-line analysis in laboratory at present.
Oranges and tangerines are subject to canker when coercing, and its photosynthesis can be affected, and chlorophyll fluorescence, as the probe of photosynthesis of plant, can follow the tracks of catching, transmit and utilizing of luminous energy in photosynthesis of plant process.Imaging-PAM technology can the metabolism state of visual plant, also can analyze the heterogeneity of photosynthesis of plant activity under different conditions.Chinese invention patent (CN104034710A) discloses a kind of plant disease detection method based on chlorophyll fluorescence and imaging technique and device.This device is positioned in lighting box, blue led lamp is as excitation source, in equilateral triangle structure, the illumination of stable and uniform can be realized, for exciting the chlorophyll fluorescence of plant leaf blade, colored high speed camera and the preposition Red lightscreening plate of adjustable camera lens, for filtering stray light, gather chlorophyll fluorescence image.By steps such as Image semantic classification, Iamge Segmentation and feature extractions, can by blade and background separation, obtain the subimage of the pixel region of position centered by main lobe arteries and veins, and calculate textural characteristics and the vein characteristic parameter of blade, finally by classifier calculated, it can be healthy by plant classification and disease two class.Plant classification can only qualitative analysis be healthy and disease two class by this preparation method, and can not continue to realize the quantitative test of degree of disease and the accurate location at disease position further.Plant disease pick-up unit simultaneously, can not realize full-automatic measurement.
Summary of the invention
The object of the invention is to for the deficiencies in the prior art, a kind of detection method and device of citrus bacterial canker disease are provided, by merging imaging-PAM technology and RGB imaging technique, the citrusfruit canker of the different growing stages such as young fruit period, Chinese olive phase and maturity stage and different diseases degree can be detected continuous and automatic.
In order to achieve the above object, the technical solution used in the present invention is: a kind of detection method of citrus bacterial canker disease, comprises the steps:
1) oranges and tangerines to be measured are carried out dark adatpation process;
2) to the oranges and tangerines to be measured through dark adatpation process, use imaging-PAM instrument to obtain fluorescence information, continue to use RGB camera to gather RGB image;
3) by fluorescence information and RGB image, chlorophyll fluorescence parameters, color characteristic and textural characteristics is calculated;
4) using the chlorophyll fluorescence parameters of above-mentioned calculating gained, color characteristic and the textural characteristics input variable as model, set up partial least squares discriminant analysis model, and distinguish oranges and tangerines with this model and whether catch an illness;
5) fluoroscopic image is read to the oranges and tangerines to be measured of catching an illness, import MATLAB software, wavelet soft-threshold is utilized to carry out noise reduction process to the fluoroscopic image of gained, application gauss hybrid models carries out cluster analysis to the fluoroscopic image chlorophyll fluorescence parameters value often put corresponding to pixel and carries out the Threshold segmentation of image, generate oranges and tangerines to be measured to catch an illness the visual image of degree, calculate the area of disease.
Canker germ invades from host's pore, hole skin or wound, and at oranges and tangerines diseased tissue place, histocyte inevitably can suffer dissociating and destroying of canker bacterium, causes the fluorescence intensity of this regional organization's cell and texture and color characteristic to change.Therefore, by conjunction with imaging-PAM technology and RGB imaging technique, the accuracy of detection of citrus bacterial canker disease can effectively be improved.Chlorophyll fluorescence parameters, color characteristic and textural characteristics are set up discrimination model analysis by partial least squares discriminant analysis method, the differentiation whether oranges and tangerines catch canker can not only be realized, and application gauss hybrid models carries out cluster analysis to the fluoroscopic image chlorophyll fluorescence parameters value often put corresponding to pixel and carries out the Threshold segmentation of image further, realize the quantitative test of degree of disease and the accurate location at disease position, finally realize the Fast nondestructive evaluation of citrus bacterial canker disease.
Described step 2) in obtain the method for fluorescence information: first open measurement radiant, now by basic fluorescence F when obtaining dark adatpation o; Then open saturated light light source, now measured is maximum fluorescence F after dark adatpation m; Then open Sources of actinic light again, measure steady-state fluorescence F during photopia s, then close Sources of actinic light; Finally open far red light light source, measure the minimum fluorescence F after photopia o'.
Described step 3) in calculate chlorophyll fluorescence parameters refer to: the maximum photochemistry quantum efficiency F of lightsystemⅡ v/ F m=(F m-F o)/F m, initial fluorescence F o, non-actinic light coefficient NPQ=F m/ F s-1.
Described step 3) in the color characteristic of RGB image refer to first moment, second moment and third moment, textural characteristics refers to variance, homogeney, contrast, entropy, second moment and correlativity.
The present invention also provides a kind of pick-up unit of citrus bacterial canker disease, comprise testing agency, control gear, travelling belt and computing machine, wherein, described control gear comprises central control system and control panel, control panel is connected with central control system respectively with travelling belt, and central control system is connected with computing machine; Described testing agency is separated into the first sealed internal chamber and the second sealed internal chamber, and arrange intermediate feed overhead door between two sealed internal chamber, the first sealed internal chamber is provided with charging overhead door, and the second sealed internal chamber is provided with discharging overhead door; Described travelling belt runs through charging overhead door, intermediate feed overhead door and discharging overhead door; Be provided with hoistable platform in the second described sealed internal chamber, described hoistable platform be provided with successively distance measuring sensor, imaging-PAM instrument and RGB camera; The position of described distance measuring sensor, imaging-PAM instrument and RGB camera vertical projection is on a moving belt respectively equipped with primary importance sensor, second place sensor and the 3rd position transducer; Distance measuring sensor and three position transducers are connected with central control system respectively, and computing machine is connected with imaging-PAM instrument and RGB camera respectively, for data transmission and analysis.
In technique scheme, central control system can control the Push And Release of conveyer belt and three overhead doors.Initiation parameter and the distance between distance measuring sensor and oranges and tangerines to be measured can be set by control panel simultaneously, utilize central control system control pick-up unit and adjust the height of hoistable platform.Wherein, primary importance sensor can trigger distance measuring sensor, by the height of the distance adjustment hoistable platform of control panel initial setting up; Second place sensor can trigger computing machine and open the collection that imaging-PAM instrument carries out fluorescence information and fluoroscopic image; 3rd position transducer can trigger computing machine and open the collection that RGB camera carries out RGB image.Computing machine can accept the data transmission of imaging-PAM instrument and RGB camera, by setting up data model analysis data, judges whether oranges and tangerines catch an illness and calculate the area of disease.
As improvement, described travelling belt end is provided with the 4th position transducer and retracting device.4th position transducer can trigger retracting device and reclaim oranges and tangerines to be measured, completes the testing process of robotization.
As preferably, described imaging-PAM instrument has the light supply apparatus of the terrace with edge shape to lower convexity, and LED light source is arranged in light supply apparatus.As preferred further, described LED light source comprises measures radiant, Sources of actinic light, saturated light light source and far red light light source.
As preferably, described central control system is middle control core with single-chip microprocessor MCU.
Compared with the existing technology, beneficial effect of the present invention is embodied in:
(1) method of the present invention and device can be applied to the detection of the citrusfruit canker of different growing stages and different diseases degree;
(2) method of the present invention and device only need set primary parameter just can measure batch, full-automatic measurement can be realized;
(3) method of the present invention and device can not only realize the differentiation whether oranges and tangerines catch canker, application gauss hybrid models (Gaussianmixturemodel, GMM) cluster analysis carried out to the fluoroscopic image chlorophyll fluorescence parameters value often put corresponding to pixel and carry out the Threshold segmentation of image, realize the quantitative test of degree of disease and the accurate location at disease position, finally realize the Fast nondestructive evaluation of citrus bacterial canker disease.
Accompanying drawing explanation
Fig. 1 is the structural representation of the pick-up unit of citrus bacterial canker disease in embodiment;
Fig. 2 is the position view of each sensor on hoistable platform in embodiment;
Fig. 3 is the inventive method process flow diagram.
Wherein, 1, charging overhead door; 2, travelling belt; 3, oranges and tangerines to be measured; 4, intermediate feed overhead door; 5, primary importance sensor; 6, second place sensor; 7, the 3rd position transducer; 8, discharging overhead door; 9, retracting device; 10, the 4th position transducer; 11, RGB camera; 12, hoistable platform; 13, the second sealed internal chamber; 14, imaging-PAM instrument; 15, distance measuring sensor; 16, computing machine; 17, the first sealed internal chamber; 18, far red light light source; 19, radiant is measured; 20, saturated light light source; 21, Sources of actinic light.
Embodiment
Below in conjunction with drawings and Examples, the invention will be further described.
As shown in Figure 1, a pick-up unit for citrus bacterial canker disease, comprise testing agency, control gear, travelling belt 2 and computing machine 16, control gear comprises central control system and control panel, control panel is connected with central control system respectively with travelling belt 2, and central control system is connected with computing machine 16; Testing agency is separated into and arranges intermediate feed overhead door 4, first sealed internal chamber 17 between the first sealed internal chamber 17 and the second sealed internal chamber 13, two sealed internal chamber and be provided with charging overhead door 1, second sealed internal chamber 13 and be provided with discharging overhead door 8; Travelling belt 2 runs through charging overhead door 1, intermediate feed overhead door 4 and discharging overhead door 8; Be provided with hoistable platform 12 in second sealed internal chamber 13, hoistable platform 12 be provided with successively distance measuring sensor 15, imaging-PAM instrument 14 and RGB camera 11; The position of distance measuring sensor 15, imaging-PAM instrument 14 and RGB camera 11 vertical projection is on conveyor belt 2 respectively equipped with primary importance sensor 5, second place sensor 6 and the 3rd position transducer 7; Distance measuring sensor 15 and three position transducers are connected with central control system respectively, and computing machine 16 is connected with imaging-PAM instrument 14 and RGB camera 11 respectively, for data transmission and analysis.Travelling belt 2 end is provided with the 4th position transducer 10 and retracting device 9.
Oranges and tangerines 3 to be measured as shown in Figure 3, are put on conveyor belt 2 by the concrete testing process of citrus bacterial canker disease, and oranges and tangerines 3 to be measured are transported to the first sealed internal chamber 17 by travelling belt, close charging overhead door 1, guarantee not light leak.Control panel inputs dark adaptation time 20min, press beginning dark adatpation button and start countdown; Set the initiation parameter of imaging-PAM instrument 14 and the distance between distance measuring sensor 15 and oranges and tangerines to be measured 3 simultaneously, because testing sample size diameter is different, therefore needs to preset testing distance, finally preserve set initiation parameter.
After dark adaptation time terminates, central control system controls intermediate feed overhead door 4 and opens, and oranges and tangerines 3 to be measured are transported to measuring position by startup travelling belt 2 simultaneously.First, after primary importance sensor 5 detects oranges and tangerines 3 to be measured, the current distance between distance measuring sensor 15 survey sensor to oranges and tangerines 3 to be measured, according to the distance preset, suitable position adjusted to by hoistable platform 12.Then, second place sensor 6 and the 3rd position transducer 7 detect oranges and tangerines 3 to be measured successively, produce a trigger pip respectively, by central control system to computing machine 16 signal transmission; Computing machine 16 starts the data acquisition of imaging-PAM instrument 14 and RGB camera 11 successively according to signal transmission, and central control system is middle control core with single-chip microprocessor MCU.
As shown in Figure 2, described imaging-PAM instrument 14 has the light supply apparatus of the terrace with edge shape to lower convexity, and LED light source is arranged in light supply apparatus.LED light source comprises measures radiant 19, Sources of actinic light 21, saturated light light source 20 and far red light light source 18.Imaging-PAM instrument 14 obtains the method for fluorescence information: first open and measure radiant 19, now by basic fluorescence F when obtaining dark adatpation o; Then open saturated light light source 20, now measured is maximum fluorescence F after dark adatpation m; Then open Sources of actinic light 21 again, measure steady-state fluorescence F during photopia s, then close Sources of actinic light 21; Finally open far red light light source 18, measure the minimum fluorescence F after photopia o'.Imaging-PAM instrument 14 obtains corresponding fluorescence information, and after completing, far red light light source 18 is closed, and imaging-PAM instrument 14 stops sampling, and travelling belt 2 is moved to the left, until after the 3rd position transducer 7 detects sample, travelling belt 2 suspends mobile.
Oranges and tangerines 3 to be measured arrive the position of RGB camera 11 correspondence, and RGB camera 11 starts to gather RGB image.After completing, RGB camera 11 stops sampling, and travelling belt 2 continues to be moved to the left, until after the 4th position transducer 10 detects oranges and tangerines 3 to be measured, produces and reclaims signal, utilize retracting device 9 recovery sample.
Chlorophyll fluorescence parameters is calculated, the maximum photochemistry quantum efficiency F of lightsystemⅡ according to fluorescence information v/ F m=(F m-F o)/F m, initial fluorescence F o, non-actinic light coefficient NPQ=F m/ F s-1.Secondly, calculate color characteristic and textural characteristics according to RGB image, color characteristic refers to first moment, second moment and third moment, and textural characteristics refers to variance, homogeney, contrast, entropy, second moment and correlativity.Using the color characteristic of the chlorophyll fluorescence parameters measured by above-mentioned calculating, RGB image and textural characteristics as mode input, be input to partial least squares discriminant analysis method (partialleastsquaresdiscriminantanalysis, PLS-DA) discrimination model whether to catch an illness to distinguish oranges and tangerines 3 to be measured.
Fluoroscopic image is read for the oranges and tangerines to be measured 3 of catching an illness, import MATLAB software, wavelet soft-threshold is utilized to carry out noise reduction process to the image of gained, application gauss hybrid models (Gaussianmixturemodel, GMM) the fluoroscopic image chlorophyll fluorescence parameters value often put corresponding to pixel is carried out cluster analysis and is carried out the Threshold segmentation of image, generate oranges and tangerines to catch an illness the visual image of degree, calculate the area of disease, and preserve.Measurement and analysis is complete, and next sample repeats above-mentioned steps.
Apply the canker of method and apparatus of the present invention to oranges and tangerines Chinese olive phase fruit to detect, the chlorophyll fluorescence parameters value scope that normal sample is corresponding is: F v/ F m=0.80 ~ 0.85, F o=170 ~ 190, NPQ=0.55 ~ 0.65; The chlorophyll fluorescence parameters value scope that sample of catching an illness is corresponding is: F v/ F m< 0.8, F o=280 ~ 320, NPQ=0.9 ~ 0.95.
First three rank color moment of RGB tri-passages of normal sample image, first moment: R μ=0.21 ~ 0.72, G μ=0.36 ~ 0.79, B μ=0.11 ~ 0.71; Second moment: R σ=0.01 ~ 0.06, G σ=0.01 ~ 0.06, B σ=0.01 ~ 0.12; Third moment: R θ=-0.06 ~ 0.05, G θ=-0.07 ~ 0.04, B θ=-0.04 ~ 0.11; To catch an illness first three rank color moment of RGB tri-passages of sample image, first moment: R μ=0.13 ~ 0.47, G μ=0.13 ~ 0.47, B μ=0.14 ~ 0.60; Second moment: R σ=0.03 ~ 0.09, G σ=0.03 ~ 0.10, B σ=0.03 ~ 0.14; Third moment: R θ=-0.06 ~ 0.07, G θ=-0.06 ~ 0.09, B θ=-0.07 ~ 0.14.Textural characteristics variable based on gray level co-occurrence matrixes: the variance (8.91 ~ 36.04) of normal sample image, homogeney (0.93 ~ 0.99), contrast (0.002 ~ 0.13), entropy (0.01 ~ 1.14), second moment (0.38 ~ 0.96) and correlativity (0.26 ~ 0.89); To catch an illness the variance (3.9 ~ 20) of sample image, homogeney (0.83 ~ 0.98), contrast (0.03 ~ 0.35), entropy (0.19 ~ 1.96), second moment (0.18 ~ 0.93) and correlativity (0.18 ~ 0.85).Above-mentioned chlorophyll fluorescence parameters, color characteristic and textural characteristics are input to partial least squares discriminant analysis method (partialleastsquaresdiscriminantanalysis, PLS-DA) discrimination model, whether model catches an illness to 174 samples differentiates, differentiates that accuracy reaches 91.3%.
Fluoroscopic image is imported MATLAB, adopts wavelet soft-threshold to remove picture noise.Application gauss hybrid models (Gaussianmixturemodel, GMM) carries out cluster analysis, for the citrusfruit of catching an illness, at F to the chlorophyll fluorescence parameters value corresponding to each some pixel v/ F mduring < 0.3, it is slough; 0.3 < F v/ F mduring < 0.58, it is withered tissue; 0.58 < F v/ F mduring < 0.80, it is slight affected tissue; 0.80 < F v/ F mit is health tissues during < 0.85.Finally carry out Iamge Segmentation, calculate disease area and the ratio accounting for the total area.Reach the object of the degree of catching an illness of quantitative test oranges and tangerines.
The foregoing is only specific embodiment of the present invention, all changes of doing according to the present patent application the scope of the claims and modification, all should belong to covering scope of the present invention.

Claims (9)

1. a detection method for citrus bacterial canker disease, is characterized in that, comprises the steps:
1) oranges and tangerines to be measured are carried out dark adatpation process;
2) to the oranges and tangerines to be measured through dark adatpation process, use imaging-PAM instrument to obtain fluorescence information, continue to use RGB camera to gather RGB image;
3) by fluorescence information and RGB image, chlorophyll fluorescence parameters, color characteristic and textural characteristics is calculated;
4) using the chlorophyll fluorescence parameters of above-mentioned calculating gained, color characteristic and the textural characteristics input variable as model, set up partial least squares discriminant analysis model, and distinguish oranges and tangerines with this model and whether catch an illness;
5) fluoroscopic image is read to the oranges and tangerines to be measured of catching an illness, import MATLAB software, wavelet soft-threshold is utilized to carry out noise reduction process to the fluoroscopic image of gained, application gauss hybrid models carries out cluster analysis to the fluoroscopic image chlorophyll fluorescence parameters value often put corresponding to pixel and carries out the Threshold segmentation of image, generate oranges and tangerines to be measured to catch an illness the visual image of degree, calculate the area of disease.
2. the detection method of citrus bacterial canker disease according to claim 1, is characterized in that, described step 2) in obtain the method for fluorescence information: first open measurement radiant, now by basic fluorescence F when obtaining dark adatpation o; Then open saturated light light source, now measured is maximum fluorescence F after dark adatpation m; Then open Sources of actinic light again, measure steady-state fluorescence F during photopia s, then close Sources of actinic light; Finally open far red light light source, measure the minimum fluorescence F after photopia o'.
3. the detection method of citrus bacterial canker disease according to claim 2, is characterized in that, described step 3) in calculate chlorophyll fluorescence parameters refer to: the maximum photochemistry quantum efficiency F of lightsystemⅡ v/ F m=(F m-F o)/F m, initial fluorescence F o, non-actinic light coefficient NPQ=F m/ F s-1.
4. the detection method of citrus bacterial canker disease according to claim 1, it is characterized in that, described step 3) in the color characteristic of RGB image refer to first moment, second moment and third moment, textural characteristics refers to variance, homogeney, contrast, entropy, second moment and correlativity.
5. the pick-up unit of a citrus bacterial canker disease, comprise testing agency, control gear, travelling belt (2) and computing machine (16), it is characterized in that, described control gear comprises central control system and control panel, control panel is connected with central control system respectively with travelling belt (2), and central control system is connected with computing machine (16); Described testing agency is separated into the first sealed internal chamber (17) and the second sealed internal chamber (13), intermediate feed overhead door (4) is set between two sealed internal chamber, first sealed internal chamber (17) is provided with charging overhead door (1), and the second sealed internal chamber (13) is provided with discharging overhead door (8); Described travelling belt (2) runs through charging overhead door (1), intermediate feed overhead door (4) and discharging overhead door (8); Be provided with hoistable platform (12) in described the second sealed internal chamber (13), described hoistable platform (12) be provided with successively distance measuring sensor (15), imaging-PAM instrument (14) and RGB camera (11); Described distance measuring sensor (15), imaging-PAM instrument (14) and RGB camera (11) are respectively equipped with primary importance sensor (5), second place sensor (6) and the 3rd position transducer (7) on the position of the upper vertical projection of travelling belt (2); Distance measuring sensor (15) and three position transducers are connected with central control system respectively, computing machine (16) is connected with imaging-PAM instrument (14) and RGB camera (11) respectively, for data transmission and analysis.
6. the pick-up unit of citrus bacterial canker disease according to claim 5, is characterized in that, described travelling belt (2) end is provided with the 4th position transducer (10) and retracting device (9).
7. the pick-up unit of citrus bacterial canker disease according to claim 5, is characterized in that, described imaging-PAM instrument (14) has the light supply apparatus of the terrace with edge shape to lower convexity, and LED light source is arranged in light supply apparatus.
8. the pick-up unit of citrus bacterial canker disease according to claim 7, it is characterized in that, described LED light source comprises measures radiant (19), Sources of actinic light (21), saturated light light source (20) and far red light light source (18).
9. the pick-up unit of citrus bacterial canker disease according to claim 5, is characterized in that, described central control system is middle control core with single-chip microprocessor MCU.
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