CN102102988B - Method, system and device for measuring crop yield information in real time - Google Patents

Method, system and device for measuring crop yield information in real time Download PDF

Info

Publication number
CN102102988B
CN102102988B CN 200910259379 CN200910259379A CN102102988B CN 102102988 B CN102102988 B CN 102102988B CN 200910259379 CN200910259379 CN 200910259379 CN 200910259379 A CN200910259379 A CN 200910259379A CN 102102988 B CN102102988 B CN 102102988B
Authority
CN
China
Prior art keywords
crops
summit
cloud terrace
angle
client
Prior art date
Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
Expired - Fee Related
Application number
CN 200910259379
Other languages
Chinese (zh)
Other versions
CN102102988A (en
Inventor
武永峰
宋吉青
刘布春
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
Institute of Environment and Sustainable Development in Agriculturem of CAAS
Original Assignee
Institute of Environment and Sustainable Development in Agriculturem of CAAS
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by Institute of Environment and Sustainable Development in Agriculturem of CAAS filed Critical Institute of Environment and Sustainable Development in Agriculturem of CAAS
Priority to CN 200910259379 priority Critical patent/CN102102988B/en
Publication of CN102102988A publication Critical patent/CN102102988A/en
Application granted granted Critical
Publication of CN102102988B publication Critical patent/CN102102988B/en
Expired - Fee Related legal-status Critical Current
Anticipated expiration legal-status Critical

Links

Images

Landscapes

  • Image Processing (AREA)
  • Length Measuring Devices By Optical Means (AREA)

Abstract

The invention discloses a method, a system and a device for measuring crop yield information in real time, relates to a signal acquisition front-end device and a data processing device which are arranged in a crop field, and also relates to a remote server and/or a client. The method comprises the following steps that: the signal acquisition front-end device is controlled by the remote server and/or the client through a centralized control command; a trigger tripod head, and a video sensor and a distance-measuring sensor which are integrated on the tripod head coordinately work; and the distance of a crop object measured by the distance-measuring sensor, the angle of the crop object measured and calculated by the tripod head, and a video image per unit area shot by the video sensor are packaged into a yield information packet through the data processing device and the yield information packet is remotely transmitted to the remote server and/or the client. By hardware highly integration, the measuring accuracy of yield information such as crop height, the planting distance, density and the like is improved, and particularly the yield of high-density crops can be accurately measured and calculated.

Description

Crop yield information real-time measuring method, system and device
Technical field
The present invention relates to the agricultural land information real time monitoring, relate in particular to crop yield information real-time measuring method, system and device.
Background technology
For a long time, obtaining of crop yield information mainly leans on traditional agriculture meteorological observation method to realize.This method utilize manual type in the farmland on-the-spot fixed point periodic sampling, and information reported to relevant departments step by step.Obtain the mode of crop yield information through the scene; Although can obtain a large amount of firsthand information; But expend human, financial, and material resources power, and the ageing and objectivity that information is transmitted is relatively poor, can't adapts to modern agriculture meteorological observation professional informationization and digitizing demand.Along with the fast development of sensor technology, automatic weather station and satellite remote sensing are widely used in the agrometeorological observation field, but its ability of obtaining crop yield information is obviously not enough.What automatic weather station was observed mainly is farm environment key elements such as precipitation, aerial temperature and humidity, wind speed and direction, solar radiation, soil temperature and humidity, does not have special determination techniques to crop yield information.Satellite remote sensing technology can quantitatively be portrayed the large tracts of land crops growth of cereal crop seedlings and growing way etc. through the spectrum inversion principle; But powerless to the mensuration of field yardstick crop yield information, and its measure precision with the time mutually resolution etc. all require to have gap greatly with precision agriculture is information-based.
Compare with above various observation technologies; The crops observation technology of video image Network Based is through the on-the-spot video monitoring equipment of installing in the farmland; Utilize the cross-regional restriction of network technology, the video image information of gathering is in real time in time transmitted go back to Surveillance center, make the user in time understand the crop growth situation; Give sensation on the spot in person, this is that automatic weather station and satellite remote sensing technology are incomparable; Moreover, this technology also has great advantage at the aspects such as ageing and objectivity of observation.This has brought important enlightenment for the informationization of modern agriculture meteorological observation.
After a literature search of prior art at home and abroad found that Japan has two related patent applications: (1) Patent Application No. PCT/JP2004/007531, patented name for autonomous operation control system (self-regulatory system of imperial Occupancy cis Te Rousseau); (2) patent Application No. 2000-377551, patent name for the remote agricultural support system (distant land agricultural support cis Te Rousseau).The maximum innovation part of this patent is, crops video frequency graphic monitoring function is introduced agricultural weather observe the field automatically, can check the crops field conditions at any time through remote service end and/or client.But this technological user only is that the crop growth situation has been seen on visual pattern ground, still is in a kind of aspect of qualitative technology, and is difficult to from the video image of passing back, realize the dose of crop yield information such as plant height, distance between rows and hills, density.
Domestic correlative study exists following problem when realizing the dose of crop yield information based on video image:
(1) integrated level of front-end collection equipment or device is low, causes the degree of accuracy of crop yield information measurement to reduce greatly;
(2) adopt the equipment or the device of discrete control to realize, increased the complexity in the control, and reduced the reliability of control the plant height of crops and the measurement of spacing in the rows;
(3) need carry out manual operation through Terminal Server Client and/or service end to the measurement of spacing in the rows etc. and aim at point distance measurement,, prolong the unnecessary running time because the reliability in the control is low;
(4) only be applicable to the low closeness crop that spacing in the rows is bigger, and powerless to the higher crop of closeness.
Summary of the invention
Technical matters to be solved by this invention provides a kind of crop yield information real-time measuring method, system and device, can calculate accurately the output of high density crops.
In order to solve the problems of the technologies described above, the invention provides a kind of crop yield information real-time measuring system, comprising: information acquisition fore device, data processing equipment, electric supply installation and remote service end and/or client, wherein:
The information acquisition fore device; Be used for remote service end and/or client mutual; Under the controlling of collection control order; Trigger this The Cloud Terrace and the video sensor and the co-ordination of distance measuring sensor that are integrated on this The Cloud Terrace, the distance signal of the crops object that distance measuring sensor is measured, the angle signal of the crops object of The Cloud Terrace measuring and calculating and the video signal of the unit area that video sensor is taken output to data processing equipment;
Data processing equipment is used for the video signal processing of distance signal, angle signal and the unit area imported is packaged into the production information bag, sends to remote service end and/or client; And/or will resolve to collection control instruction from the steering order bag that remote service end and/or client receive and export to the information acquisition fore device;
Electric supply installation is used for to information acquisition fore device and said data processing equipment working power being provided respectively;
Remote service end and/or client are used for that collection control instruction is packaged into the steering order bag and send to data processing equipment; Parse the video image of distance parameter, angle parameter and the unit area of crops object from the production information bag that receives, calculate and preserve plant height, line-spacing and/or the spacing in the rows production information of crops thus.
Preferably,
The crops object angle parameter of The Cloud Terrace measuring and calculating comprises the horizontal swing angle parameter between the distance of angle of pitch parameter and/or different crops object of crops object;
Remote service end and/or client are according to the high computational of distance parameter, angle of pitch parameter and the The Cloud Terrace of resolving and the plant height of preservation crops.
Preferably,
Remote service end and/or client demarcate the summit of the first crops object for some A, according to the distance parameter (L of this A 1), angle of pitch parameter (α 1) calculate from this A and move to unit length (L 0) summit B and the angle of pitch theoretical value (α between the The Cloud Terrace of the second crops object 2), according to α 2The remote control The Cloud Terrace moves to summit B, demarcates summit B thus and is a B; According to L 1, α 1Calculate from this A and move to L along the direction vertical with AB 0Summit C and the angle of pitch theoretical value (α between the The Cloud Terrace of the 3rd crops object 3), calculate the theoretical value (α of the horizontal swing angle of The Cloud Terrace when moving to summit C simultaneously by a B 4), according to α 3, α 4The remote control The Cloud Terrace moves to this summit C, demarcates summit C thus and is a C; According to L 1, α 1Calculate from a B and move to L along the direction vertical with AB 0Summit D and the angle of pitch theoretical value (α between the The Cloud Terrace of the 4th crops object 5), calculate the theoretical value (α of the horizontal swing angle of The Cloud Terrace when moving to summit D simultaneously by a B 6), according to α 5, α 6The remote control The Cloud Terrace moves to this summit D, demarcates summit D thus and is a D; Behind tie point A, some B, some C and the some D, then obtain the calibration zone (L of unit area 0* L 0).
Preferably,
Remote service end and/or client remote control The Cloud Terrace; Make video sensor move to the summit B ' and the aligning of another adjacent crops object from the summit A of crops object; Trigger distance measuring sensor thus and measure that A moves to the horizontal swing angle of summit B ' with the angle of pitch of the distance of this summit B ' and The Cloud Terrace measuring and calculating summit B ' with from the summit, and obtain the parameter of measurement; According to the distance parameter that obtains, angle of pitch parameter and horizontal swing angle parameter and use the trigonometric function principle to calculate spacing in the rows or the spacing in the rows of crops.
Preferably
The Cloud Terrace is rotation and/or mobile under the control of collection control order; The crops object that video sensor is aimed in the calibration zone is taken corresponding video image, and the information acquisition fore device sends to remote service end and/or client with the video signal in the calibration zone of video sensor shooting through data processing equipment;
Remote service end and/or client are carried out image recognition according to the production information that calculates and/or to the video image in the calibration zone; Further identification unit of account area crop growth density; Obtain crops each growing stage upgrowth situation and growing way, and specific yield and/or the per mu yield of calculating crops.
Preferably,
Remote service end and/or client are further measured proportion of crop planting density in the calibration zone to the crops different growing; Wherein, in the seedling stage for the do not tiller crop and the crop that tillers, estimate proportion of crop planting density through said spacing in the rows and the said line-spacing of measuring crops in the calibration zone; For the tillering of the crop that tillers, jointing and heading stage, carry out image recognition through crops video signal to calibration zone, dose goes out the total stem number of unit area, the number of productive ear of the crops in the calibration zone, and then obtains the proportion of crop planting density information.
Preferably,
The information acquisition fore device is also under the control of collection control order; The depth of parallelism through between a collimating apparatus control of video sensor and the distance measuring sensor object lens axis is in the predetermined error range, to guarantee that the projection centre of said distance measuring sensor emitted light beams on this target overlaps with the video image center of formation when the target of the crops object of locking in the coverage.
In order to solve the problems of the technologies described above, the invention provides a kind of information acquisition fore device that the crop yield information real-time is measured that is used for, this device becomes one video sensor, distance measuring sensor and The Cloud Terrace, wherein:
The Cloud Terrace; Be used under the control of remote control order in vertical direction and/or horizontal direction rotation; Come the mobile video sensor; And the angle of pitch of the crops subject object point of measuring and calculating video sensor aligning, and/or calculate the horizontal swing angle that moves to another impact point from an impact point, and the angle of pitch signal and/or the horizontal swing angle signal of output measuring and calculating;
Video sensor is used under the control that remote control is ordered, and based on the action adjustment of The Cloud Terrace and the distance and the angle of crops object, when aiming at the impact point of this crops object, triggers the capture video image, and exports the video signal of taking;
Distance measuring sensor is used under the control of remote control order, when video sensor is aimed at the impact point of crops object, triggers the distance of measuring this impact point, and exports the distance signal of measuring.
Preferably,
The Cloud Terrace comprises the common The Cloud Terrace of digital The Cloud Terrace and integrated angle measurement function, wherein should be integrated with the photoelectric encoder of being with the angle measurement function by the numeral The Cloud Terrace, to realize measuring and calculating angle function; The integrated vertical and horizontal direction angular measurement sensor of this common The Cloud Terrace is used to realize side calculation angle function;
Distance measuring sensor comprises one or more in laser range finder, ultrasonic range finder and the infrared range-measurement system;
Video sensor comprises analog video camera and/or digital camera.
Preferably,
The information acquisition fore device also is integrated with collimating apparatus; The depth of parallelism that is used between control of video sensor and the distance measuring sensor object lens axis is in the predetermined error range, to guarantee that the projection centre of distance measuring sensor emitted light beams on this target overlaps with the video image center of formation when the target of the crops object of locking in the coverage.
In order to solve the problems of the technologies described above, the invention provides a kind of crop yield information real-time measuring method, relate to the information acquisition fore device and the data processing equipment that are installed in the crops scene, also relate to remote service end and/or client, this method comprises:
The information acquisition fore device is controlled through collection control order by remote service end and/or client; Trigger The Cloud Terrace and the video sensor and the co-ordination of distance measuring sensor that are integrated on this The Cloud Terrace; Distance signal, the crops object angle signal of The Cloud Terrace measuring and calculating and the video signal of the unit area that video sensor is taken of the crops object that distance measuring sensor is measured are packaged into the production information bag through data processing equipment, and remote transmission is to remote service end and/or client.
Preferably,
Remote service end and/or client parse the video image of distance parameter, angle parameter and the unit area of crops object from the production information bag that receives, and calculate the production information of crops thus.
Preferably, angle parameter comprises the horizontal swing angle parameter between the distance of angle of pitch parameter and/or different crops object of crops object;
Remote service end and/or client specifically comprise according to the distance parameter of crops object, the calibration zone that angle parameter obtains unit area:
It is a some A that the summit of the first crops object is demarcated;
Distance parameter (L according to this A 1), angle of pitch parameter (α 1) calculate from this A and move to unit length (L 0) summit B and the angle of pitch theoretical value (α between the The Cloud Terrace of the second crops object 2), calculation of alpha 2Formula be: α 2 = Arctan ( L 0 + L 1 Sin α 1 L 1 × Cos α 1 ) ; According to α 2The remote control The Cloud Terrace moves to summit B, demarcates summit B thus and is a B;
According to L 1, α 1Calculate from this A and move to L along the direction vertical with AB 0Summit C and the angle of pitch theoretical value (α between the The Cloud Terrace of the 3rd crops object 3), calculation of alpha 3Formula do α 3 = Arccos ( L 1 × Cos α 1 L 0 2 + L 1 2 ) ; Calculate the theoretical value (α of the horizontal swing angle of The Cloud Terrace when moving to summit C simultaneously by a B 4), calculation of alpha 4Formula do α 4 = Arctan ( L 0 L 1 × Sin α 1 ) ; According to α 3, α 4The remote control The Cloud Terrace moves to this summit C, demarcates summit C thus and is a C;
According to L 1, α 1Calculate from a B and move to L along the direction vertical with AB 0Summit D and the angle of pitch theoretical value (α between the The Cloud Terrace of the 4th crops object 5), calculation of alpha 5Formula do α 5 = Arccos ( L 1 × Cos α 1 L 0 2 + L 1 2 ) , Calculate the theoretical value (α of the horizontal swing angle of The Cloud Terrace when moving to summit D simultaneously by a B 6), calculation of alpha 6Formula do α 6 = Arctan ( L 0 L 1 × Sin α 1 ) ; According to α 5, α 6The remote control The Cloud Terrace moves to this summit D, demarcates said summit D thus and is a D;
Behind tie point A, some B, some C and the some D, then obtain the calibration zone (L of unit area 0* L 0).
Preferably, remote service end and/or client are calculated the production information of crops, specifically comprise:
According to the distance parameter L that resolves 1, angle of pitch parameter alpha 1And the height h of The Cloud Terrace calculates and preserves the plant height h of crops 0, computing formula is h 0=h-L 1* cos α 1
Remote service end and/or client remote control The Cloud Terrace make video sensor from summit B ' and aligning that the summit A of this crops object moves to another adjacent crops object, trigger the distance (L that distance measuring sensor is measured this summit B ' thus 2) and the angle of pitch α of The Cloud Terrace measuring and calculating summit B ' 2With A moves to the horizontal swing angle (α of summit B ' from the summit 4), and obtain the parameter of measurement; According to the L that obtains 2, α 2And α 4L by formula AB '=f (L 1* sin α 1, L 2* sin α 2, α 4) calculate spacing in the rows or the spacing in the rows of crops, L in the formula AB 'Be spacing in the rows or the spacing in the rows of calculating.
Preferably,
The Cloud Terrace is rotation and/or mobile under the control of collection control order; The crops object that video sensor is aimed in the calibration zone is taken corresponding video image, and the information acquisition fore device sends to remote service end and/or client with the video signal in the calibration zone of video sensor shooting through data processing equipment;
Remote service end and/or client according to the plant height that calculates, line-spacing and or spacing in the rows production information and/or the video image in the calibration zone carried out image recognition; Further identification unit of account area crop growth density; Obtain crops each growing stage upgrowth situation and growing way, and specific yield and/or the per mu yield of calculating crops.
Preferably,
Remote service end and/or client are further measured proportion of crop planting density in the calibration zone to the crops different growing; Wherein:
In seedling stage for the do not tiller crop and the crop that tillers, estimate proportion of crop planting density through spacing in the rows and the line-spacing of measuring crops in the calibration zone;
For the tillering of the crop that tillers, jointing and heading stage, carry out image recognition through video signal to calibration zone, dose goes out the total stem number of unit area, the number of productive ear of the crops in the calibration zone, and then obtains the proportion of crop planting density information.
Preferably,
Remote service end and/or client are carried out image recognition to the video image in the calibration zone, specifically comprise:
Video image is carried out pre-service, and pre-service comprises one or more processing in image smoothing, image transformation, figure image intensifying, image recovery and the image filtering;
From through extracting the production information characteristic the pretreated image, the production information characteristic comprises based on color characteristic, based on morphological feature and based in the textural characteristics one or more;
According to the production information characteristic of extracting and combine expertise solution bank data to carry out categorised decision, pass judgment on out the eigenwert of crucial puberty of crops, number of productive ear, grain number per spike Isoquant information.
The present invention is through integrated with the height of functions such as video sensing, range finding sensing, angle measurement sensing, cradle head control, direction finding collimation, improved the accuracy and the reliability of crops height, spacing in the rows, density Isoquant information measurement greatly; Realized accurate measurement through pitching and horizontal angle measurement technique, and accurate hardware controls technology helps fast, accurately and easily navigates to desired location to highly dense intensity crop.The present invention is suitable for the measuring and calculating of the crop yield of any kind, particularly can calculate accurately for the specific yield of highdensity crops, really realizes effectively sharing of agricultural land information thus.
Description of drawings
Fig. 1 is the structured flowchart of crop yield information real-time measuring system embodiment of the present invention;
Fig. 2 is that configuration schematic diagram is installed at the scene of system shown in Figure 1 embodiment;
Fig. 3 obtains the geometric representation of unit area calibration zone alternately for remote service end of the present invention and/or client and information acquisition fore device;
Fig. 4 is the process flow diagram that obtains the embodiment of unit area calibration zone in the crop yield information real-time measuring method of the present invention;
Fig. 5 is the geometric representation that the crop yield information real-time is measured of the present invention;
Fig. 6 is for obtaining the method embodiment process flow diagram of plant height, line-spacing and the spacing in the rows of crops in the crop yield information real-time measuring method of the present invention;
Fig. 7 is the method embodiment process flow diagram that the unit area video image is carried out image recognition of the present invention.
Embodiment
Below in conjunction with accompanying drawing and preferred embodiment technical scheme of the present invention is at length set forth.The embodiment that below gives an example only is used for explanation and explains the present invention, and does not constitute the restriction to technical scheme of the present invention.
As shown in Figure 1, be the structure of the real-time measurement system embodiment of crop yield information provided by the invention, Fig. 2 is each the Unit Installation synoptic diagram of scene in this system.System embodiment shown in Figure 1 comprises information acquisition fore device, data processing equipment, electric supply installation and remote service end and/or client, wherein:
The information acquisition fore device; Be used for carrying out information interaction with remote service end and/or client; Under the controlling of collection control order; Trigger The Cloud Terrace and the video sensor and the co-ordination of distance measuring sensor that are integrated on the The Cloud Terrace, the distance signal of the crops object that distance measuring sensor is measured, the angle signal of the crops object of The Cloud Terrace measuring and calculating and the video signal of the unit area that video sensor is taken output to data processing equipment;
Data processing equipment is used for being packaged into the production information bag after the video signal processing with distance signal, angle signal and the unit area imported, sends to remote service end and/or client; Perhaps, will resolve to collection control instruction from the steering order bag of remote service end and/or client reception and export to the information acquisition fore device;
Electric supply installation is used for to information acquisition fore device and data processing equipment working power being provided respectively;
Remote service end and/or client are used for that collection control instruction is packaged into the steering order bag and send out to data processing equipment; The production information bag that receives is parsed the video image of distance parameter, angle parameter and the unit area of crops object, calculate and preserve plant height, line-spacing and/or the spacing in the rows production information of these crops thus.
In the information acquisition fore device, the crops object angle parameter of The Cloud Terrace measuring and calculating comprises the horizontal swing angle between the distance of the angle of pitch and/or different crops object of crops object;
Remote service end and/or client are according to the distance parameter L of the crops object of resolving 1, angle of pitch parameter alpha 1And the height h of The Cloud Terrace calculates and preserves the plant height h of crops 0, please with reference to Fig. 3.
Remote service end and/or client demarcate the summit of the first crops object for some A, according to the distance parameter (L of this A 1), angle of pitch parameter (α 1) calculate from this A and move to unit length (L 0) summit B and the angle of pitch theoretical value (α between the The Cloud Terrace of the second crops object 2), according to α 2The remote control The Cloud Terrace moves to summit B, demarcates summit B thus and is a B; According to L 1, α 1Calculate from this A and move to L along the direction vertical with AB 0Summit C and the angle of pitch theoretical value (α between the The Cloud Terrace of the 3rd crops object 3), calculate the theoretical value (α of the horizontal swing angle of The Cloud Terrace when moving to summit C simultaneously by a B 4), according to α 3, α 4The remote control The Cloud Terrace moves to this summit C, demarcates summit C thus and is a C; According to L 1, α 1Calculate from a B and move to L along the direction vertical with AB 0Summit D and the angle of pitch theoretical value (α between the The Cloud Terrace of the 4th crops object 5), calculate the theoretical value (α of the horizontal swing angle of The Cloud Terrace when moving to summit D simultaneously by a B 6), according to α 5, α 6The remote control The Cloud Terrace moves to this summit D, demarcates summit D thus and is a D; Behind tie point A, B, C, the D, then obtain unit area (L 0* L 0) calibration zone.
Remote service end and/or client remote control The Cloud Terrace; Make video sensor move to the summit B ' and the aligning of another adjacent crops object from the summit A ' of a crops object; Trigger distance measuring sensor thus and measure that A ' moves to the horizontal swing angle of summit B ' with the angle of pitch of the distance of this summit B ' and The Cloud Terrace measuring and calculating summit B ' with from the summit, and obtain the parameter of measurement; According to the distance parameter that obtains, angle of pitch parameter and horizontal swing angle parameter and use the trigonometric function principle to calculate spacing in the rows or the line-spacing of crops.
The Cloud Terrace is rotation and/or mobile under the control of collection control order; The crops object that video sensor is aimed in the above-mentioned calibration zone is taken corresponding video image, sends to remote service end and/or client after the video signal that the information acquisition fore device is taken video sensor is handled through data processing equipment;
Remote service end and/or client are carried out image recognition according to the production information that calculates and/or to the video image in the calibration zone; Further identification unit of account area crop growth density; Obtain crops each growing stage upgrowth situation and growing way, and specific yield and/or the per mu yield of calculating crops.
Remote service end and/or client are further measured proportion of crop planting density in the calibration zone to the crops different growing; Wherein, in the seedling stage for the do not tiller crop and the crop that tillers, estimate proportion of crop planting density through spacing in the rows and the line-spacing of measuring crops in the calibration zone; For the tillering of the crop that tillers, jointing and heading stage, carry out image recognition through crops video image to calibration zone, dose goes out the total stem number of unit area, the number of productive ear of the crops in the calibration zone, and then obtains the proportion of crop planting density information.
Built-in scale in length and breadth, grid coordinates and video image central cross line are drawn in the video sensor, are applicable to through Terminal Server Client and/or service end intuitively to distinguish, measure image distance, identification crops morphological feature surely.
The information acquisition fore device also is used under the control of collection control order; The depth of parallelism through between collimating apparatus control of video sensor and the distance measuring sensor object lens axis is in the predetermined error range, to guarantee that the projection centre of distance measuring sensor emitted light beams on this target overlaps with the video image center of formation when the target of the crops object of locking in the coverage.
The information acquisition fore device is realized the synchronous accurate heart point of collimating apparatus calibration range sensor and video sensor and the trinity of The Cloud Terrace angle measurement function.
The present invention is directed to said system and also correspondingly propose crop yield information real-time measuring method embodiment, comprise the steps:
Remote service end and/or client are installed in the on-the-spot information acquisition fore device of crops object through collection control order control; Trigger video sensor and the distance measuring sensor be integrated on the The Cloud Terrace and cooperate in harmony through controlling The Cloud Terrace, the angle signal of the crops object of and distance signal crops object, The Cloud Terrace measuring and calculating that measure with distance measuring sensor and the video signal of the unit area that video sensor is taken are packaged into production information bag remote transmission;
Remote service end and/or client parse the video image of distance parameter, angle parameter and the unit area of crops object with the production information bag that receives, and calculate plant height, line-spacing and/or the spacing in the rows production information of crops thus.
Remote service end and/or client are carried out image recognition according to the production information that calculates and/or to the video image of unit area, further calculate the density of unit area crops, extrapolate the specific yield of crops thus.
As shown in Figure 4, be the flow process of the method embodiment of remote service end of the present invention and/or the client collection control information acquisition fore device calibration zone of obtaining unit area, comprise the steps:
101: remote service end and/or client are controlled The Cloud Terrace, make video sensor aim at the summit of first crops, trigger the distance L that distance measuring sensor is measured this summit thus 1, and The Cloud Terrace is measured the angle of pitch α on this summit 1, and the parameter of return measurement;
Video sensor is aimed at the summit of crops, is meant the video sensor cross curve is drawn a bit that central point is aimed at this crop plant top blade face.
102: remote service end and/or client are received the distance L on this summit 1, angle of pitch α 1After the parameter, demarcate this summit and be an A;
1 A on blade face, crop plant top among the summit of first crops such as Fig. 3.
103: according to distance parameter L 1, angle of pitch parameter alpha 1Calculate from this A and move to unit length L 0Summit and the The Cloud Terrace of the second crops object between angle of pitch theoretical value α 2
α 2Computing formula following:
α 2 = arctan ( L 0 + L 1 × sin α 1 L 1 × cos α 1 ) - - - ( 1 )
104: according to this theoretical value α 2The remote control The Cloud Terrace moves to the summit of this second crops object, demarcates this summit thus and is a B;
1 B on blade face, crop plant top among the summit of second crops such as Fig. 3.
105: according to distance parameter L 1, angle of pitch parameter alpha 1Calculate from this A and move to unit length L along the direction vertical with AB 0Summit and the The Cloud Terrace of the 3rd crops object between angle of pitch theoretical value α 3Calculate simultaneously by a B and move to the horizontal swing angle theoretical value of this summit The Cloud Terrace α 4
α 3Computing formula following:
α 3 = arccos ( L 1 × cos α 1 L 0 2 + L 1 2 ) - - - ( 2 )
α 4Computing formula following:
α 4 = arctan ( L 0 L 1 × sin α 1 ) - - - ( 3 )
106: according to theoretical value α 3, α 4The remote control The Cloud Terrace moves to the summit of the 3rd crops object, demarcates this summit thus and is a C;
1 C on blade face, crop plant top among the summit of the 3rd crops such as Fig. 3.
107: use the method identical to calculate angle of pitch theoretical value α between summit and the The Cloud Terrace of the 4th crops object with step 105 5With move to the horizontal swing angle theoretical value of this summit The Cloud Terrace α by a B 6
108: according to theoretical value α 5, α 6The remote control The Cloud Terrace moves to the summit of the 4th crops object, demarcates this summit thus and is a D;
1 D on blade face, crop plant top among the summit of the 4th crops such as Fig. 3.
109: then obtain unit area (L behind tie point A, B, C, the D 0* L 0) calibration zone.
Remote service end and/or client are further measured the crops density in this calibration zone to the crops different growing.
Wherein,, spacing in the rows and the line-spacing of crops in the calibration zone be can measure through native system, thereby the plants stems number of unit area, i.e. proportion of crop planting density estimated in seedling stage for the crop that do not tiller; For the crop that tillers, in seedling stage: can measure spacing in the rows and the line-spacing of crops in the calibration zone through native system, to estimate proportion of crop planting density; Tiller, jointing and heading stage: the crops video image through to this calibration zone is discerned, and dose goes out the total stem number of unit area, the number of productive ear of the crops in the calibration zone, and then obtains the actual density of crops.
Below in conjunction with the present invention shown in Figure 5 geometric representation to the measurement of crop yield information real-time; Explain out the method embodiment flow process that remote service end and/or client collection control information acquisition fore device obtain plant height, line-spacing and the spacing in the rows of crops; As shown in Figure 6, comprise the steps:
210: Terminal Server Client and/or service end are controlled The Cloud Terrace, make video sensor aim at the summit of a crops object, trigger the distance L that distance measuring sensor is measured this summit thus 1, and The Cloud Terrace is measured the angle of pitch α on this summit 1, and the parameter of return measurement;
1 A on the blade face, crop plant top that the summit of crops object is as shown in Figure 6.
220: Terminal Server Client and/or service end are tried to achieve the plant height h of crops object according to the parameter that receives 0
h 0Computing formula following:
h 0=h-L 1×cosα 1 (4)
H is the height of The Cloud Terrace in the formula.
230: the remote control The Cloud Terrace, make video sensor move to the summit B of another crop object that summit A closes on, trigger the video image that video sensor is taken B place, summit thus, trigger simultaneously that distance measuring sensor is measured and the distance L of this summit B 2, and the angle of pitch α of digital The Cloud Terrace measuring and calculating summit B 2With A moves to the horizontal swing angle α of summit B from the summit 4, and obtain the parameter of measurement;
240: utilization trigonometric function principle calculates the distance between summit A and the B, i.e. the spacing in the rows L of crops AB
Spacing in the rows L ABComputing formula following:
L AB=f(L AO,L BO,α 4)=f(L 1×sinα 1,L 2×sinα 2,α 4) (5)
250: Terminal Server Client and/or service end continue to control The Cloud Terrace; B moves to the summit C of another crop object from the summit with video sensor; And CB and AB meet at right angles, and trigger the video image that video sensor is taken summit C thus, trigger the distance L of distance measuring sensor measurement and summit C simultaneously 3, and the angle of pitch α of digital The Cloud Terrace measuring and calculating summit C 3With B moves to the horizontal swing angle α of summit C from the summit 5, and obtain the parameter of measurement;
260: utilization trigonometric function principle calculates the distance between the BC of summit, i.e. the line-spacing L of crops BC
Line-spacing L BCComputing formula following:
L BC=f(L CO,L BO,α 5)=f(L 3×sinα 3,L 2×sinα 2,α 5) (6)
In the present embodiment, be that Terminal Server Client and/or service end are controlled The Cloud Terrace, B moves to the summit C of another crop object from the summit with video sensor, and according to the calculation of parameter trip distance of measuring thus.In fact the method for measuring line-spacing and measuring spacing in the rows is identical, that is Terminal Server Client and/or service end control The Cloud Terrace A moves to the summit C of another crop object from the summit with video sensor, and still can calculate line-spacing according to the parameter of measurement thus.
As shown in Figure 7 be remote service end and/or client according to the method embodiment flow process that the video image of unit area is carried out image recognition, comprise the steps:
310: the video image to obtaining carries out pre-service;
Before extracting production information; In order to be extruded with effective information more and to remove disturbing factor; Need carry out pre-service to video image, comprise that image smoothing, image transformation (gray processing, binaryzation etc.), figure image intensifying, image recover and image filtering (medium filtering, gaussian filtering etc.).
320: from the pretreated image of process, extract the production information characteristic;
Mainly comprise based on color characteristic, extract based on morphological feature and based on the production information of textural characteristics, specifically:
Extract based on the production information of color characteristic and to be meant: use color model (commonly used is RGB model and HIS model) to distinguish the difference of external interference factors such as output element information and Soil Background, weeds, natural lighting, with the influence of factors such as elimination Soil Background, weeds and natural lighting; This color model also capable of using is being optimized image information aspect lightness and the saturation degree, makes it more can reflect people's visual characteristic.
Production information extraction based on morphological feature is meant: partly be difficult to distinguish under the situation of color for crop yield element information and other like leaf, stem etc.; The production information that needs to replenish based on morphological feature extracts, and main morphological feature index such as leaf area, fringe shape size fractionation, blade be axial ratio or the like in length and breadth.
Production information extraction based on textural characteristics is meant: if still be difficult to distinguish production information and other disturbing factor based on color characteristic and morphological feature, then replenish the extraction of textural characteristics.Mainly be divided three classes: the first kind is a statistical analysis method, like gray level co-occurrence matrixes; Second type is structured analysis method, puts forth effort to find out the primitive of texture, forms from structure and seeks rule; The 3rd type of analytic approach that is based on frequency spectrum is like correlation method, LC model parameter method etc.
330: according to the production information characteristic of extracting and combine expertise solution bank data to carry out categorised decision;
To output related information based on color characteristic, morphological feature and texture feature extraction; Compare with the judgment criteria of forming by expertise solution bank and Standard Colors, form and texture criterion storehouse, pass judgment on out the eigenwert of crucial puberty of crops, number of productive ear, grain number per spike Isoquant information.
340: export crop yield information such as crucial puberty of crops, number of productive ear and grain number per spike according to the categorised decision result.
The structure that is used for the information acquisition fore device embodiment of crop yield information real-time measurement as can be seen from Figure 1 of the present invention, it is a device that video sensor, distance measuring sensor and The Cloud Terrace are integrated in one, wherein:
The Cloud Terrace; Be used under the control of remote control order in vertical direction and/or horizontal direction rotation; Come the mobile video sensor; And the angle of pitch of the crops subject object point of measuring and calculating video sensor aligning, and/or calculate the horizontal swing angle that moves to another impact point from an impact point, and the angle of pitch signal and/or the horizontal swing angle signal of output measuring and calculating;
Video sensor is used under the control that remote control is ordered, and according to the action adjustment of The Cloud Terrace and the distance and the angle of crops object, when aiming at the impact point of crops object, triggers the capture video image, and exports the video signal of taking;
Distance measuring sensor is used under the control of remote control order, when video sensor is aimed at the impact point of crops object, triggers the distance of measuring this impact point, and exports the distance signal of measuring.
Above-mentioned information acquisition fore device also is integrated with collimating apparatus; The depth of parallelism that is used between control of video sensor and the distance measuring sensor object lens axis is in the predetermined error range; To guarantee that when the target of the crops object of locking in the coverage, the projection centre of distance measuring sensor emitted light beams on this target overlaps with the video image center of formation.
Above-mentioned The Cloud Terrace comprises the common The Cloud Terrace of digital The Cloud Terrace and integrated angle measurement function.Wherein digital The Cloud Terrace is integrated with the photoelectric encoder of band angle measurement function, is used to realize the angle measurement function; The integrated vertical and horizontal direction angular measurement sensor of common The Cloud Terrace is used to realize the side angle function.
Above-mentioned distance measuring sensor comprises one or more in laser range finder, ultrasonic range finder and the infrared range-measurement system.
Above-mentioned video sensor comprises analog video camera and/or digital camera.
The above is merely preferred embodiment of the present invention, is not to be used to limit the scope that comprises of the present invention.All any modifications of within spirit of the present invention and principle, being done, be equal to alternative, improvement etc., all should be included within protection scope of the present invention.

Claims (17)

1. crop yield information real-time measuring system comprises: information acquisition fore device, data processing equipment, electric supply installation and remote service end and/or client, wherein:
Said information acquisition fore device; Be used for said remote service end and/or client mutual; Under the controlling that the collection control of said remote service end and/or client is ordered; Trigger The Cloud Terrace and the video sensor and the co-ordination of distance measuring sensor that are integrated on this The Cloud Terrace, the distance signal of the crops object that said distance measuring sensor is measured, the angle signal of the crops object of said The Cloud Terrace measuring and calculating and the video signal of the unit area that said video sensor is taken output to said data processing equipment;
Said data processing equipment is used for the video signal processing of said distance signal, said angle signal and the said unit area imported is packaged into the production information bag, sends to said remote service end and/or client; And/or will resolve to said collection control instruction from the steering order bag that said remote service end and/or client receive and export to said information acquisition fore device;
Said electric supply installation is used for to said information acquisition fore device and said data processing equipment working power being provided respectively;
Said remote service end and/or client are used for that said collection control instruction is packaged into said steering order bag and send to said data processing equipment; Parse the video image of distance parameter, angle parameter and the unit area of crops object from the said production information bag that receives, calculate and preserve plant height, line-spacing and/or the spacing in the rows production information of said crops thus.
2. according to the described system of claim 1, it is characterized in that,
The crops object angle parameter of said The Cloud Terrace measuring and calculating comprises the angle of pitch parameter alpha of crops object 1And/or the horizontal swing angle between the distance of different crops objects;
Said remote service end and/or client are according to the distance parameter L that resolves 1, angle of pitch parameter alpha 1And the high computational of The Cloud Terrace and the plant height of preserving crops.
3. according to the described system of claim 2, it is characterized in that,
Said remote service end and/or client demarcate the summit of the first crops object for some A, according to the said distance parameter L of this A 1, said angle of pitch parameter alpha 1Calculate from this A and move to unit length L 0Summit B and the angle of pitch theoretical value α between the said The Cloud Terrace of the second crops object 2, according to said α 2The said The Cloud Terrace of remote control moves to said summit B, demarcates said summit B thus and is a B; According to said L 1, said α 1Calculate from this A and move to said L along the direction vertical with AB 0Summit C and the angle of pitch theoretical value α between the said The Cloud Terrace of the 3rd crops object 3, calculate the theoretical value α of the horizontal swing angle of said The Cloud Terrace when moving to said summit C simultaneously by said some B 4, according to said α 3, said α 4The said The Cloud Terrace of remote control moves to this summit C, demarcates said summit C thus and is a C; According to said L 1, said α 1Calculate from said some B and move to said L along the direction vertical with AB 0Summit D and the angle of pitch theoretical value α between the said The Cloud Terrace of the 4th crops object 5, calculate the theoretical value α of the horizontal swing angle of said The Cloud Terrace when moving to said summit D simultaneously by said some B 6, according to said α 5, said α 6The said The Cloud Terrace of remote control moves to this summit D, demarcates said summit D thus and is a D; After connecting said some A, said some B, said some C and said some D, then obtain the calibration zone L of said unit area 0* L 0
4. according to the described system of claim 3, it is characterized in that,
Said remote service end and/or the said The Cloud Terrace of client remote control; Make said video sensor move to the summit B ' and the aligning of another adjacent crops object from the summit A of said crops object; Trigger said distance measuring sensor thus and measure that A moves to the horizontal swing angle of summit B ' with the angle of pitch of the distance of this summit B ' and said The Cloud Terrace measuring and calculating summit B ' with from the summit, and obtain the parameter of measurement; According to the distance parameter that obtains, angle of pitch parameter and horizontal swing angle parameter and use the trigonometric function principle to calculate spacing in the rows or the spacing in the rows of crops.
5. according to the described system of claim 4, it is characterized in that,
Said The Cloud Terrace is rotation and/or mobile under the control of collection control order; The crops object that said video sensor is aimed in the said calibration zone is taken corresponding video image, and said information acquisition fore device sends to said remote service end and/or client with the video signal in the said calibration zone of said video sensor shooting through said data processing equipment;
Said remote service end and/or client are carried out image recognition according to the said production information that calculates and/or to the video image in the said calibration zone; Further identification unit of account area crop growth density; Obtain crops each growing stage upgrowth situation and growing way, and specific yield and/or the per mu yield of calculating crops.
6. according to the described system of claim 5, it is characterized in that,
Said remote service end and/or client are further measured proportion of crop planting density in the said calibration zone to the crops different growing; Wherein, in the seedling stage for the do not tiller crop and the crop that tillers, estimate said proportion of crop planting density through said spacing in the rows and the said line-spacing of measuring crops in the said calibration zone; For the tillering of the said crop that tillers, jointing and heading stage; Crops video signal through to said calibration zone carries out image recognition; Dose goes out total stem number of unit area and the number of productive ear of the crops in the said calibration zone, and then obtains the proportion of crop planting density information.
7. according to each described system of claim 1 to 6, it is characterized in that,
Said information acquisition fore device is also under the control of said collection control order; The depth of parallelism of controlling between said video sensor and the said distance measuring sensor object lens axis through a collimating apparatus is in the predetermined error range, to guarantee that the projection centre of said distance measuring sensor emitted light beams on this target overlaps with the video image center of formation when the target of the crops object of locking in the coverage.
8. one kind is used for the information acquisition fore device that the crop yield information real-time is measured, and it is characterized in that said device becomes one video sensor, distance measuring sensor and The Cloud Terrace, wherein:
Said The Cloud Terrace; Be used under the control of remote control order in vertical direction and/or horizontal direction rotation; Come the mobile video sensor; And the angle of pitch of the crops subject object point of measuring and calculating video sensor aligning, and/or calculate the horizontal swing angle that moves to another impact point from an impact point, and the angle of pitch signal and/or the horizontal swing angle signal of output measuring and calculating;
Said video sensor; Be used under the control of remote control order; According to the action adjustment of said The Cloud Terrace and the distance and the angle of said crops object, when aiming at the impact point of this crops object, trigger the capture video image, and export the video signal of taking;
Distance measuring sensor is used under the control of remote control order, when said video sensor is aimed at the impact point of crops object, triggers the distance of measuring this impact point, and exports the distance signal of measuring.
9. according to the described device of claim 8, it is characterized in that,
Said The Cloud Terrace comprises the common The Cloud Terrace of digital The Cloud Terrace and integrated angle measurement function, and wherein said digital The Cloud Terrace is integrated with the photoelectric encoder of band angle measurement function, to realize measuring and calculating angle function; The integrated vertical and horizontal direction angular measurement sensor of said common The Cloud Terrace is used to realize side calculation angle function;
Said distance measuring sensor comprises one or more in laser range finder, ultrasonic range finder and the infrared range-measurement system;
Said video sensor comprises analog video camera and/or digital camera.
10. according to claim 8 or 9 described devices, it is characterized in that,
Said information acquisition fore device also is integrated with collimating apparatus; The depth of parallelism that is used to control between said video sensor and the said distance measuring sensor object lens axis is in the predetermined error range, to guarantee that the projection centre of said distance measuring sensor emitted light beams on this target overlaps with the video image center of formation when the target of the crops object of locking in the coverage.
11. a crop yield information real-time measuring method relates to the information acquisition fore device and the data processing equipment that are installed in the crops scene, also relates to remote service end and/or client, this method comprises:
Said information acquisition fore device is controlled through collection control order by said remote service end and/or client; Trigger The Cloud Terrace and the video sensor and the co-ordination of distance measuring sensor that are integrated on this The Cloud Terrace; Distance signal, the crops object angle signal of said The Cloud Terrace measuring and calculating and the video signal of the unit area that said video sensor is taken of the crops object that said distance measuring sensor is measured are packaged into the production information bag through said data processing equipment, and remote transmission is given said remote service end and/or client.
12. according to the described method of claim 11, it is characterized in that,
Said remote service end and/or client parse the video image of distance parameter, angle parameter and the unit area of crops object from the said production information bag that receives, and calculate the production information of crops thus.
13., it is characterized in that said angle parameter comprises the angle of pitch parameter alpha of crops object according to the described method of claim 12 1And/or the horizontal swing angle parameter between the distance of different crops objects;
Said remote service end and/or client specifically comprise according to the distance parameter of said crops object, the calibration zone that angle parameter obtains said unit area:
It is a some A that the summit of the first crops object is demarcated;
Said distance parameter L according to this A 1, said angle of pitch parameter alpha 1Calculate from this A and move to unit length L 0Summit B and the angle of pitch theoretical value α between the said The Cloud Terrace of the second crops object 2, calculate said α 2Formula be:
Figure FSB00000881851300041
According to said α 2The said The Cloud Terrace of remote control moves to said summit B, demarcates said summit B thus and is a B;
According to said L 1, said α 1Calculate from this A and move to said L along the direction vertical with AB 0Summit C and the angle of pitch theoretical value α between the said The Cloud Terrace of the 3rd crops object 3, calculate said α 3Formula do
Figure FSB00000881851300042
Calculate the theoretical value α of the horizontal swing angle of said The Cloud Terrace when moving to said summit C simultaneously by said some B 4, calculate said α 4Formula do
Figure FSB00000881851300043
According to said α 3, said α 4The said The Cloud Terrace of remote control moves to this summit C, demarcates said summit C thus and is a C;
According to said L 1, said α 1Calculate from said some B and move to said L along the direction vertical with AB 0Summit D and the angle of pitch theoretical value α between the said The Cloud Terrace of the 4th crops object 5, calculate said α 5Formula do
Figure FSB00000881851300051
Calculate the theoretical value α of the horizontal swing angle of said The Cloud Terrace when moving to said summit D simultaneously by said some B 6, calculate said α 6Formula do
Figure FSB00000881851300052
According to said α 5, said α 6The said The Cloud Terrace of remote control moves to this summit D, demarcates said summit D thus and is a D;
After connecting said some A, said some B, said some C and said some D, then obtain the calibration zone L of said unit area 0* L 0
14., it is characterized in that said remote service end and/or client are calculated the production information of crops, specifically comprise according to the described method of claim 13:
According to the said distance parameter L that resolves 1, said angle of pitch parameter alpha 1And the height h of said The Cloud Terrace calculates and preserves the plant height h of said crops 0, computing formula is h 0=h-L 1* cos α 1
Said remote service end and/or the said The Cloud Terrace of client remote control; Make said video sensor from summit B ' and aligning that the summit A of said crops object moves to another adjacent crops object, trigger the distance L that said distance measuring sensor is measured this summit B ' thus 2And the angle of pitch α of said The Cloud Terrace measuring and calculating summit B ' 2With A moves to the horizontal swing angle α of summit B ' from the summit 4, and obtain the parameter of measurement; According to the said L that obtains 2, said α 2And said α 4L by formula AB '=f (L 1* sin α 1, L 2* sin α 2, α 4) calculate spacing in the rows or the spacing in the rows of crops, L in the formula AB 'Be spacing in the rows or the spacing in the rows calculated, said f is a functional symbol.
15. according to the described method of claim 14, it is characterized in that,
Said The Cloud Terrace is rotation and/or mobile under the control of collection control order; The crops object that said video sensor is aimed in the said calibration zone is taken corresponding video image, and said information acquisition fore device sends to said remote service end and/or client with the video signal in the said calibration zone of said video sensor shooting through said data processing equipment;
Said remote service end and/or client according to the said plant height that calculates, line-spacing and or spacing in the rows production information and/or the video image in the said calibration zone carried out image recognition; Further identification unit of account area crop growth density; Obtain crops each growing stage upgrowth situation and growing way, and specific yield and/or the per mu yield of calculating crops.
16. according to the described method of claim 15, it is characterized in that,
Said remote service end and/or client are further measured proportion of crop planting density in the said calibration zone to the crops different growing; Wherein:
In seedling stage for the do not tiller crop and the crop that tillers, estimate said proportion of crop planting density through said spacing in the rows and the said line-spacing of measuring crops in the said calibration zone;
For the tillering of the said crop that tillers, jointing and heading stage; Video signal through to said calibration zone carries out image recognition; Dose goes out total stem number of unit area and the number of productive ear of the crops in the said calibration zone, and then obtains the proportion of crop planting density information.
17. according to claim 15 or 16 described methods, it is characterized in that,
Said remote service end and/or client are carried out image recognition to the video image in the said calibration zone, specifically comprise:
Said video image is carried out pre-service, and said pre-service comprises one or more processing in image smoothing, image transformation, figure image intensifying, image recovery and the image filtering;
From through extracting the production information characteristic the said pretreated image, said production information characteristic comprises based on color characteristic, based on morphological feature and based in the textural characteristics one or more;
According to the said production information characteristic of extracting and combine expertise solution bank data to carry out categorised decision, pass judgment on out the eigenwert of crucial puberty of crops, number of productive ear and these three kinds of production informations of grain number per spike.
CN 200910259379 2009-12-22 2009-12-22 Method, system and device for measuring crop yield information in real time Expired - Fee Related CN102102988B (en)

Priority Applications (1)

Application Number Priority Date Filing Date Title
CN 200910259379 CN102102988B (en) 2009-12-22 2009-12-22 Method, system and device for measuring crop yield information in real time

Applications Claiming Priority (1)

Application Number Priority Date Filing Date Title
CN 200910259379 CN102102988B (en) 2009-12-22 2009-12-22 Method, system and device for measuring crop yield information in real time

Publications (2)

Publication Number Publication Date
CN102102988A CN102102988A (en) 2011-06-22
CN102102988B true CN102102988B (en) 2012-12-26

Family

ID=44155925

Family Applications (1)

Application Number Title Priority Date Filing Date
CN 200910259379 Expired - Fee Related CN102102988B (en) 2009-12-22 2009-12-22 Method, system and device for measuring crop yield information in real time

Country Status (1)

Country Link
CN (1) CN102102988B (en)

Families Citing this family (30)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN102589426A (en) * 2012-01-13 2012-07-18 同济大学 Geology photographing system and method capable of automatically calibrating size
CN102927916B (en) * 2012-11-29 2015-05-20 中国农业大学 Method and device of monitoring height of corn plants in wild environment
CN103309310B (en) * 2013-05-21 2015-03-25 江苏大学 Method for monitoring operation of plug seedling transplanting robot based on laser scanning
CN103363952A (en) * 2013-06-03 2013-10-23 长春理工大学 Vehicle-mounted photoelectric measuring device and method for target sizes and interval between electric transmission line and target
CN104200193A (en) * 2014-08-05 2014-12-10 北京农业信息技术研究中心 Fruit tree yield estimation method and device
CN104567824A (en) * 2015-01-15 2015-04-29 河海大学 Bridge support inspection recording instrument
CN104914828A (en) * 2015-04-22 2015-09-16 柳州易农科技有限公司 Intelligent system for agriculture
CN104836948A (en) * 2015-05-11 2015-08-12 国家电网公司 Follow-up camera and real-time ranging method
CN104810749A (en) * 2015-05-11 2015-07-29 国家电网公司 Real-time transmission-line live working safety control system and working monitoring method
CN105157782B (en) * 2015-08-26 2018-05-22 西南交通大学 Material heap level measuring system based on laser ranging technique
CN105115450A (en) * 2015-09-16 2015-12-02 安庆市宜秀区永兴农机农艺综合发展专业合作社 Agricultural machinery operation area measuring instrument
CN105510242B (en) * 2015-12-28 2019-06-04 南京农业大学 A kind of crop growth monitoring method and device based on multi-rotor unmanned aerial vehicle platform
CN106210670A (en) * 2016-09-08 2016-12-07 贵州大学 A kind of supervisory device for agricultural pest control
EP3343170A1 (en) * 2016-12-27 2018-07-04 Yara International ASA Device and method for determining a height of an agricultural product
CN106871799B (en) * 2017-04-10 2019-11-12 淮阴工学院 A kind of full-automatic crops plant height measurement method and device
CN107044846A (en) * 2017-04-14 2017-08-15 深圳市瑞荣创电子科技有限公司 Corn plants high-altitude measuring system and measuring method
CN107314759B (en) * 2017-06-05 2020-03-31 江苏大学 Wheat field yield estimation method and device based on multi-angle shooting of unmanned aerial vehicle
CN107339948B (en) * 2017-06-28 2023-07-07 沈阳工业大学 Equipment and method for detecting distance between spray boom and crop plant
CN107194616A (en) * 2017-06-29 2017-09-22 惠国征信服务股份有限公司 Enterprise's production capacity statistical system and method
CN108240792A (en) * 2018-01-11 2018-07-03 刘小勇 Crop maturity judgment means and method
CN108592832B (en) * 2018-05-11 2020-05-22 朱芃嘉 Agricultural experimental apparatus that grows seedlings based on physics ultrasonic detection
CN109035209A (en) * 2018-07-03 2018-12-18 广西壮族自治区气象减灾研究所 Sugarcane tillering stage automatic observation process
CN110163138B (en) * 2019-05-13 2022-03-11 河南科技大学 Method for measuring and calculating wheat tillering density based on multispectral remote sensing image of unmanned aerial vehicle
CN112733582A (en) * 2019-10-28 2021-04-30 广州极飞科技有限公司 Crop yield determination method and device and nonvolatile storage medium
CN111426347A (en) * 2020-04-15 2020-07-17 河北冀云气象技术服务有限责任公司 Crop growth condition characteristic acquisition system and method
CN111707783A (en) * 2020-05-12 2020-09-25 五邑大学 Crop growth monitoring method and device and storage medium
CN112614147B (en) * 2020-12-24 2024-03-22 中国农业科学院作物科学研究所 Crop seedling stage plant density estimation method and system based on RGB image
CN112881343A (en) * 2021-01-12 2021-06-01 吉林工程技术师范学院 Rice monitoring equipment based on characteristic spectrogram video image
CN117172505B (en) * 2023-09-27 2024-08-09 广东省农业科学院农业经济与信息研究所 Crop planting state monitoring method and system based on Internet of things
CN117664878B (en) * 2024-01-31 2024-04-19 北京市农林科学院信息技术研究中心 Crop acre spike number measuring system and method

Citations (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN2906683Y (en) * 2005-08-18 2007-05-30 上海皓维电子有限公司 PTZ and lens positioning device
CN101169627A (en) * 2007-11-27 2008-04-30 中国水利水电科学研究院 On-line crop water stress irrigation decision monitoring system
CN201116980Y (en) * 2007-11-27 2008-09-17 中国水利水电科学研究院 On-line crop canopy-air temperature difference irrigation decision monitoring system

Patent Citations (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN2906683Y (en) * 2005-08-18 2007-05-30 上海皓维电子有限公司 PTZ and lens positioning device
CN101169627A (en) * 2007-11-27 2008-04-30 中国水利水电科学研究院 On-line crop water stress irrigation decision monitoring system
CN201116980Y (en) * 2007-11-27 2008-09-17 中国水利水电科学研究院 On-line crop canopy-air temperature difference irrigation decision monitoring system

Also Published As

Publication number Publication date
CN102102988A (en) 2011-06-22

Similar Documents

Publication Publication Date Title
CN102102988B (en) Method, system and device for measuring crop yield information in real time
Hall et al. Optical remote sensing applications in viticulture‐a review
CN112418188B (en) Crop growth whole-course digital evaluation method based on unmanned aerial vehicle vision
CN111767865A (en) Method for inverting mangrove forest biomass by using aerial image and laser data
CN113177744A (en) Urban green land system carbon sink amount estimation method and system
JP2008079549A (en) Method for evaluating tree growth
Zheng et al. Spatial variability of terrestrial laser scanning based leaf area index
Hale et al. Impact of topographic normalization on land-cover classification accuracy
CN102088839A (en) Method for diagnosing growth of crop and system for diagnosing growth
Ahongshangbam et al. Drone‐based photogrammetry‐derived crown metrics for predicting tree and oil palm water use
Gong et al. Photo ecometrics for forest inventory
Korpela et al. Backscattering of individual LiDAR pulses from forest canopies explained by photogrammetrically derived vegetation structure
Gottfried et al. First examples from the RIEGL VUX-SYS for forestry applications
CN103424366A (en) Intelligent fertilization implementation method based on multi-spectral accurate recognition
Hama et al. Examination of appropriate observation time and correction of vegetation index for drone-based crop monitoring
Pauly Applying conventional vegetation vigor indices to UAS-derived orthomosaics: issues and considerations
CN212861863U (en) Plant community statistics monitoring system based on unmanned aerial vehicle
Gunnula et al. Evaluating sugarcane growth and maturity using ground-based measurements and remote sensing data.
CN110135385A (en) A kind of construction method of Hills structuring vegetation index model
CN214622342U (en) Plant phenotype measuring system
Cheng et al. Improving UAV-Based LAI Estimation for Forests Over Complex Terrain by Reducing Topographic Effects on Multispectral Reflectance
CN117951469B (en) Day-air-ground integrated carbon sink monitoring system and method for vineyard ecosystem
Morsdorf et al. The potential of discrete return, small footprint airborne laser scanning data for vegetation density estimation
CN111623706B (en) Caragana microphylla stubble leveling machine information acquisition method
Chun et al. Biomass estimation of Gwangneung catchment area with Landsat ETM+ image

Legal Events

Date Code Title Description
C06 Publication
PB01 Publication
C10 Entry into substantive examination
SE01 Entry into force of request for substantive examination
C14 Grant of patent or utility model
GR01 Patent grant
CF01 Termination of patent right due to non-payment of annual fee

Granted publication date: 20121226

Termination date: 20181222

CF01 Termination of patent right due to non-payment of annual fee