CN104732564B - A kind of Estimating Leaf Area In Maize dynamic nondestructive monitoring device and method - Google Patents

A kind of Estimating Leaf Area In Maize dynamic nondestructive monitoring device and method Download PDF

Info

Publication number
CN104732564B
CN104732564B CN201510157959.0A CN201510157959A CN104732564B CN 104732564 B CN104732564 B CN 104732564B CN 201510157959 A CN201510157959 A CN 201510157959A CN 104732564 B CN104732564 B CN 104732564B
Authority
CN
China
Prior art keywords
image
maize
information
blade
leaf
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.)
Active
Application number
CN201510157959.0A
Other languages
Chinese (zh)
Other versions
CN104732564A (en
Inventor
张永恩
庄家煜
高利伟
王盛威
许世卫
李干琼
王东杰
陈威
李灯华
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.)
Agricultural Information Institute of CAAS
Original Assignee
Agricultural Information Institute 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 Agricultural Information Institute of CAAS filed Critical Agricultural Information Institute of CAAS
Priority to CN201510157959.0A priority Critical patent/CN104732564B/en
Publication of CN104732564A publication Critical patent/CN104732564A/en
Application granted granted Critical
Publication of CN104732564B publication Critical patent/CN104732564B/en
Active legal-status Critical Current
Anticipated expiration legal-status Critical

Links

Landscapes

  • Image Analysis (AREA)
  • Image Processing (AREA)

Abstract

The invention discloses a kind of Estimating Leaf Area In Maize dynamic nondestructives to monitor system and method, the present invention takes the method that multidimensional positions Image Acquisition and image analysis is combined, equipment is light, operation is simple, can in field quick, aspect lossless acquisition Estimating Leaf Area In Maize multidimensional image;By later image integrated treatment, the parameters such as the blade dimensional posture that can export 3 plants of corns, plant height, greenery area, withered and yellow leaf area are handled each time;It is able to record corresponding position information, can ensure multiple measurement object as same sample, and have multiple correction and Quality Control Function, can realize the long-term dynamics monitoring of Estimating Leaf Area In Maize;Image capture module and image processing module realize separation, and pass through wireless transmission information, are operated on the spot convenient for field;Dynamic, comprehensive information are provided for corn Growing state survey and management.

Description

A kind of Estimating Leaf Area In Maize dynamic nondestructive monitoring device and method
Technical field
The present invention relates to reading intelligent agriculture technical field, more particularly to a kind of Estimating Leaf Area In Maize dynamic nondestructive monitoring device with Method.
Background technology
Leaf area is to weigh the important indicator of crop growth situation and production capacity.Corn is important grain work Object, the measurement to Estimating Leaf Area In Maize are always one of important process content of agricultural research staff.It is long that each blade is measured respectively Degree and width, then the traditional measurement method estimated with empirical equation, time-consuming and laborious, accuracy is low, and easily to the leaf of corn Piece damages, and then influences photosynthetic capacity.Part leaf area instrument calculates leaf area, one using leaf image is scanned piecewise Determine to improve acquisition precision in degree, but up to 30 or so, the blade of corn, blade height reaches as high as 3 meters, and blade Base portion is the circle around stalk, and base portion and middle part are shallow " V " type, it is not easy to be scanned operation, and be easily damaged blade.
In the patent measured in leaf area, it is mainly the following, patent CN201410201645 discloses one kind and passes through The method of model remote sensing monitoring wheat leaf area index that experimental data is combined with remotely-sensed data, can realize large area wheat leaf The estimation of area index, but indoor test is needed to be combined, accuracy is relatively low.Patent CN201410229812.3 discloses one kind Leaf area index measuring method and system, realize the accuracy of measurement, but need to sample by destructive, by blade from plant It picks and is scanned in strain, comparativity is poor between the data of acquisition, and is difficult to realize the dynamic monitoring of leaf area.Patent CN201010231726.8 discloses a kind of method of hemisphere photographing rice LAI, but is difficult to efficient application and exists The tall and big Estimating Leaf Area In Maize of plant measures, and this method converts the image into binary grayscale image, it is impossible to identify corn Withered and yellow blade area is difficult to apply in the fertility middle and later periods.Patent CN201320029088.0 discloses a kind of measurement crop blade face Long-pending system is acquired the image of each blade using quadrangle support assorted blank, the area of each blade is obtained by processing, by Big (per acre 5000 plants or so) in plant high (usually at 2 meters or so), density, this method is fitted when acquiring Estimating Leaf Area In Maize Answering property is poor, and when operation is easily blocked and causes physical damnification to plant.
Invention content
(1) technical problems to be solved
The technical problem to be solved by the present invention is to:A kind of Estimating Leaf Area In Maize dynamic nondestructive monitoring device and method are provided, it is real Dynamic monitoring now is carried out to maize leaf field growing, while maize leaf is not damaged, improves the convenient of leaf area monitoring Property and monitoring accuracy.
(2) technical solution
In order to solve the above technical problem, the present invention provides a kind of Estimating Leaf Area In Maize dynamic nondestructives to monitor system, including Image capture module, information transmission modular and image processing module;Above-mentioned image capture module is planted for acquiring corn to be monitored The multidimensional image in 8 sites of strain, acquired image is sent to image processing module by information transmission modular, by image processing module It calculates and obtains Estimating Leaf Area In Maize to be monitored;
Described image acquisition module includes location information collecting unit, location information determination unit, image acquisition units, figure As quality control unit and image storage unit;The location information determination unit is used to determine the position of Image Acquisition point, position Put the location information of information acquisition unit acquisition image capture module and the location information of Image Acquisition point, image acquisition units root The maize leaf Image Acquisition in 8 sites is carried out according to identified Image Acquisition point, picture quality control unit is to acquiring figure The position of picture and quality carry out inspection confirmation, and image storage unit stores satisfactory image;
Described image processing module includes color recognition unit, shape recognition unit, angle correction unit, range measurement list Member and area computing unit;The color of acquired maize leaf is identified in color recognition unit, determines fresh and alive maize leaves Panel region, vein region, withered and yellow maize leaf region, sundries region;Shape recognition unit is marked according to color recognition result The vein of maize leaf and sideline, and to wherein carrying out extension benefit according to front and rear section is blocked by the part that other blades block Together;According to vein state recognition blade 3 d pose, length, width and the deviation horizontal direction angle of each maize leaves of segmentation markers Degree;For angle correction unit according to the image in multiple sites, it is vertical direction that by maize leaf, uniformly correction, which is front,;Range measurement The information such as the height of unit according to the angle of image information collecting point, with the distance of plant, from the ground calculate picture size With the scaling of actual size, width, length, the three-dimensional digital information of height and the plant height information of blade are measured;Area Computing unit is calculated per the area of a piece of greenery and dead leaf area, and it is the greenery area of single plant corn and dead leaf face to sum it up Product.
Wherein, the location information collecting unit includes gps position indicators, gyroscope and accelerometer, and gps position indicators are used for The longitude and latitude and altitude information of Image Acquisition point are acquired, gyroscope is used to acquire movement angle and the track of image capture module, Accelerometer is used to acquire the speed and distance of image capture module movement.
Wherein, the location information determination unit includes two parts of position instruction and position alignment, position instruction part Indicate that 8 Image Acquisition sites carry out Image Acquisition, and are displayed on the screen according to the requirement of Image Acquisition;Position alignment part Image Acquisition frame is aligned with position instruction frame according to position instruction guiding photographing person.
Wherein, described information transmission module includes wireless transmission unit, radio receiving unit and completeness check unit, nothing The information of acquisition is converted into radio signal, and send by wireless frequency modulation mode by line transmitting element;Radio receiving unit leads to It crosses wireless frequency modulation mode and receives information, and the radio signal of reception is converted into digital information;Completeness check unit passes through The information characteristics sent and received are compared, it is ensured that transmit errorless and information completely.
The present invention also provides a kind of Estimating Leaf Area In Maize dynamic nondestructive monitoring methods, include the following steps:
Step 1:Acquire multi-angle, the various dimensions image of 8 different locis of maize leaf to be monitored:
Determine the geographical location information in 8 different locis and each site;Corresponding each site, acquires piece image, institute Acquire the corresponding location information of image and the quality parameter information of image and the geographical location information and image in identified site Quality requirement information is consistent, then stores image;
Step 2:Acquired image information is sent to image processing module, calculates Estimating Leaf Area In Maize:
The color of acquired maize leaf is identified first, determines fresh and alive maize leaf region, vein region, withered Yellow maize leaf area, sundries region;According to color recognition result, vein and the sideline of maize leaf are marked, and to wherein Extension polishing is carried out according to front and rear section is blocked by the part that other blades block;According to vein state recognition blade three-dimensional appearance State, length, width and the deviation horizontal direction angle of each maize leaves of segmentation markers;According to the image in 8 sites, by maize leaves It is vertical direction that the unified correction of piece, which is front,;According to the angle of image information collecting point, with the distance of plant, from the ground The information such as height calculate the scaling of picture size and actual size, measure the width of blade, length, height 3-dimensional digital Information is calculated per the area of a piece of greenery and dead leaf area, and it is the greenery area of single plant corn and dead leaf area to sum it up.
Wherein, in the step 2, the process that the color of acquired maize leaf is identified is:According to color spy Sign, identification green is fresh and alive maize leaf, canescence is vein, and yellow is withered and yellow maize leaf, and other is sundries;To maize leaves Panel region is identified and marks, and marks fresh and alive maize leaf region, vein region, withered and yellow maize leaf region, sundries area Domain;The identity element in different images is marked and identified simultaneously, avoids repeating;According to corncob it is conical the characteristics of, Distinguish maize leaves and corncob.
Wherein, in the step 2, the length of each maize leaves of segmentation markers, width and when deviateing horizontal direction angle, The identical region of blade posture is same section, and the different region of posture marks respectively.
Wherein, it is that the process that front is vertical direction is by the unified correction of maize leaf in the step 2:Correction is divided into Wherein longitudinal correction width of blade is constant, length of blade is adjusted according to angle for the correction of blade longitudinal direction and laterally two steps of correction, Calculation formula is the length of blade that y ˊ=y/sin α, y ˊ are after correction, and y surveys length of blade for figure, and α is blade offset level direction Angle;Laterally correction length of blade is constant, adjusts width of blade according to angle, calculation formula is strong for x ˊ=x/sin α, x ˊ Width of blade after just, x survey width of blade for figure, and α is the angle in blade offset level direction.
(3) advantageous effect
Above-mentioned technical proposal has the following advantages that:Take positioning Image Acquisition and the method that is combined of image analysis, equipment It is light, operation is simple, can in field quick, aspect lossless acquisition Estimating Leaf Area In Maize image;By later image General Office Reason, the parameters such as the blade posture per treatment that can export 3 plants of corns, plant height, greenery area, withered and yellow leaf area;It is able to record Corresponding position information, it is same sample that can ensure multiple measurement object, and has multiple correction and Quality Control Function, can Realize the long-term dynamics monitoring of Estimating Leaf Area In Maize;Image capture module and image processing module realize separation, and pass through and wirelessly pass Defeated information, operates on the spot convenient for field;Dynamic, comprehensive information are provided for corn Growing state survey and management.
Description of the drawings
Fig. 1 is the functional block diagram of Estimating Leaf Area In Maize of embodiment of the present invention dynamic nondestructive monitoring system.
Fig. 2 is the flow chart of Estimating Leaf Area In Maize dynamic nondestructive monitoring method of the embodiment of the present invention.
Specific embodiment
With reference to the accompanying drawings and examples, the specific embodiment of the present invention is described in further detail.Implement below Example is used to illustrate the present invention, but be not limited to the scope of the present invention.
With reference to shown in Fig. 1, the present embodiment Estimating Leaf Area In Maize dynamic nondestructive monitoring system includes image capture module, information passes 3 parts of defeated module and image processing module.
Specifically, image capture module is image processing module for acquiring satisfactory multidimensional plant image Basic information is provided.Image capture module include location information collecting unit, location information determination unit, image acquisition units, 5 units such as picture quality control unit and image storage unit.
Location information collecting unit includes gps position indicators, gyroscope and accelerometer, and gps position indicators are used to acquire image The location informations such as longitude and latitude, the height above sea level of collection point, gyroscope are used to acquire movement angle and the track of image capture module, accelerate Degree counts the speed and distance for acquiring image capture module movement.
Location information determination unit includes two parts of position instruction and position alignment, and position instruction part is adopted according to image The requirement of collection indicates that 8 Image Acquisition sites carry out Image Acquisition, and are displayed on the screen;Position alignment part refers to according to position Image Acquisition frame is aligned by the person that shows guiding photographing with position instruction frame, ensures shooting orientation, height, the accuracy of angle.
Image acquisition units are made of cmos image sensor, camera lens etc., for being specified according to location information determination unit Position and angle, according to specified resolution ratio, shoot the coloured image of plant, corresponding each plant obtains 8 Image, and be stored in image storage unit.
Picture quality control unit is used for information such as the acquisition position of the image collected, angle, resolution ratio, clarity It is proofreaded with the information of location information determination unit, it is up-to-standard, Image Acquisition next time is carried out, it is off quality then former Position resurveys information, until qualification.
Image storage unit preserves the latitude and longitude information of Image Acquisition, orientation letter simultaneously for storing the image of acquisition Breath and image sequence information.
Information transmission modular mainly includes three wireless transmission, wireless receiving and completeness check units, in information collection Module and image processing module both ends are laid respectively, for information acquisition module is acquired information completely, be inerrably transferred to Image processing module.Wherein, the information of acquisition is converted into radio signal, and pass through wireless frequency modulation mode by wireless transmission unit It sends;Radio receiving unit receives information, and the radio signal of reception is converted into digital information by wireless frequency modulation mode; Completeness check unit is by being compared the information characteristics sent and received, it is ensured that transmits errorless and information completely.
Image processing module passes through the multivariate analysis of multidimensional plant image information that is acquired to image capture module, comprehensive Conjunction is handled, and the results such as the leaf area of corn are calculated;Specifically include color recognition unit, shape recognition unit, angle correction Five units such as unit, distance measuring unit, areal calculation unit.
Color recognition unit is used to identify fresh and alive maize leaf (green), vein (canescence) withered and yellow jade according to color characteristic Rice blade (yellow) and other sundries;Maize leaf region is identified and marked, it is maize leaves to identify which pixel region It is withered and yellow maize leaf, which pixel region is other sundries that piece, which pixel region, which are vein, which pixel region,;Simultaneously Identity element in different images is marked and identified, avoids repeating, and feeds back information to form recognition unit.
Shape recognition unit receives the information of color recognition unit transmission, according to the flat belt-like feature of maize leaf, knows Not and mark vein and the sideline of maize leaf, and to wherein by the part that other blades block according to block front and rear section into Row extension polishing.According to vein state recognition blade 3 d pose, length, width and the deviation water of each maize leaves of segmentation markers Flat orientation angle, the identical region of blade posture are same section, and the different region of posture marks respectively.According to corncob circular cone The characteristics of shape, distinguishes maize leaves and corncob.
Angle correction unit corrects the state of maize leaf according to the information that 8 images provide, according to deviation water Square to angle, by the unified correction of blade be front be vertical direction, convenient for sampling and measuring.Correction is divided into blade and longitudinally rectifys Just (angle at correction blade base and top) and laterally two steps of correction (angles of correction blade both sides), wherein longitudinal direction is rectified Positive width of blade is constant, and length of blade is adjusted according to angle, and specific formula for calculation is blade that y ˊ=y/sin α, y ˊ be after correcting Length, y survey length of blade for figure, and α is the angle in blade offset level direction;Laterally correction length of blade is constant, according to angle Width of blade is adjusted, specific formula for calculation is the width of blade that x ˊ=x/sin α, x ˊ are after correction, and x surveys width of blade, α for figure Angle for blade offset level direction.
Distance measuring unit is used for the distance of the angle according to image information collecting point and plant, height from the ground The information such as degree calculate the scaling of picture size and actual size, measure the width of blade, length, height 3-dimensional digital letter Breath.
The information that areal calculation unit is provided according to distance measuring unit is calculated per the area of a piece of greenery and dead leaf face Product sums it up the leaf area of as single plant corn.
Structure and principle based on above-mentioned monitoring device, the Estimating Leaf Area In Maize dynamic nondestructive monitoring method of the present embodiment include Following steps:
Step 1:The multiple image in multiple and different sites of maize leaf to be monitored is acquired, detailed process is as follows:
It determines multiple and different sites, and the geographical location information in each site is determined, the quantity in site and specific The image that comprehensive can collect maize leaf to be monitored is subject in position;Corresponding each site acquires piece image, and will The quality parameter information of location information and image corresponding to image and the geographical location information in identified site and image matter Amount require information is compared, it is ensured that acquires image qualification, is then retaken until qualification when unqualified;Then by image into Row storage.
Step 2:Acquired image information is sent to image processing module, calculates Estimating Leaf Area In Maize, detailed process is such as Under:
The color of acquired maize leaf is identified first, determines fresh and alive maize leaf region, vein region, withered Yellow maize leaf area, sundries region;According to color recognition result, vein and the sideline of maize leaf are marked, and to wherein Extension polishing is carried out according to front and rear section is blocked by the part that other blades block;According to vein state recognition blade three-dimensional appearance State, length, width and the deviation horizontal direction angle of each maize leaves of segmentation markers;According to the image in multiple sites, by corn It is vertical direction that the unified correction of blade, which is front,;According to the angle of image information collecting point, with the distance of plant, from the ground The information such as height calculate the scaling of picture size and actual size, measure the width of blade, length, height three dimensions Word information is calculated per the area of a piece of greenery and dead leaf area, and it is the greenery area of single plant corn and dead leaf area to sum it up. Processing can acquire and monitor simultaneously the parameters such as the leaf area of 3 plants of corns each time, available for result comparison and weighted average.
More specific details is described in the structure and principle of system in above-mentioned steps, does not do further go to live in the household of one's in-laws on getting married herein It states.Below with a specific example, with reference to Fig. 2, vivider explanation is carried out to the present invention.
In view of plant is high, density is big, but mostly using wide-narrow row planting, spacing in the rows is small and line space is big, wide row into Row Image Acquisition has suitable space.8 sites is used (to choose 4 sides clockwise in 45° angle with corn row in Image Acquisition To horizontal distance corn is the wide row line-spacing of corn, and vertical range is two height of 0.8m and 1.5m from the ground) horizontal bat respectively 8 images are taken the photograph, every image request includes the complete image of 3 plants of corns, and records photographing longitude and latitude, height, angle etc. simultaneously After first image information collecting point acquires image information, school is carried out by picture quality control unit to the information of image for information It is right.Confirmation message is complete, it is errorless after, storage to image storage unit.Next shooting point is determined by location information determination unit Position, and indicate viewfinder alignment shooting, confirm it is errorless after start to shoot the 3rd image, until 8 image takings are completed.
After the completion of image taking, image processing module is transmitted to by information transmission modular.It is identified by color, shape is known Not, 5 angle correction, range measurement and areal calculation steps, each entire flow can calculate the leaf area of 3 plants of corns.
When dynamic measures, it can continue by location information determination unit in the same position of formulation, site, angle acquisition image Information, and it is automatically associated with history metrical information.
As can be seen from the above embodiments, the present invention takes positioning Image Acquisition and the method that is combined of image analysis, if It is standby it is light, operation is simple, can in field quick, aspect lossless acquisition Estimating Leaf Area In Maize image;It is integrated by later image Processing, being capable of the parameters such as output blade posture, leaf area, plant height, stem thick, leaf color, withered and yellow leaf area;It is able to record corresponding position Information can ensure multiple measurement object as same sample, and have multiple correction and Quality Control Function, can realize corn The long-term dynamics monitoring of leaf area;Image capture module and image processing module realize separation, and pass through wireless transmission information, just It is operated on the spot in field;Dynamic, comprehensive information are provided for corn Growing state survey and management.
The above is only the preferred embodiment of the present invention, it is noted that for the ordinary skill people of the art For member, without departing from the technical principles of the invention, several improvement and replacement can also be made, these improve and replace Also it should be regarded as protection scope of the present invention.

Claims (8)

1. a kind of Estimating Leaf Area In Maize dynamic nondestructive monitors system, which is characterized in that including image capture module, information transmission modular And image processing module;Above-mentioned image capture module is used to acquire the multidimensional image in 8 sites of plant to be monitored, and information passes Acquired image is sent to image processing module by defeated module, is calculated by image processing module and is obtained Estimating Leaf Area In Maize to be monitored;
Described image acquisition module includes location information collecting unit, location information determination unit, image acquisition units, image matter Measure control unit and image storage unit;The location information determination unit is used to determine the position of Image Acquisition point, institute's rheme It puts information determination unit and includes two parts of position instruction and position alignment, position instruction part refers to according to the requirement of Image Acquisition Show that 8 Image Acquisition sites carry out Image Acquisition, and are displayed on the screen, position alignment part is according to position instruction guiding photographing Image Acquisition frame is aligned by person with position instruction frame;Location information collecting unit acquires the location information and figure of image capture module As the location information of collection point, image acquisition units carry out the maize leaf figure in 8 sites according to identified Image Acquisition point As acquisition, image acquisition units are made of cmos image sensor, camera lens, for the position specified according to location information determination unit It puts with angle, according to specified resolution ratio, shoots the coloured image of plant, corresponding each plant obtains 8 figures Picture, and be stored in image storage unit;Picture quality control unit to the position of acquired image and quality check really Recognize, image storage unit stores satisfactory image;
Described image processing module include color recognition unit, shape recognition unit, angle correction unit, distance measuring unit and Areal calculation unit;The color of acquired maize leaf is identified in color recognition unit, determines fresh and alive maize leaves section Domain, vein region, withered and yellow maize leaf region, sundries region;Shape recognition unit marks corn according to color recognition result The vein of blade and sideline, and to wherein carrying out extension polishing according to front and rear section is blocked by the part that other blades block;Root According to vein state recognition blade 3 d pose, length, width and the deviation horizontal direction angle of each maize leaves of segmentation markers;Angle Image of the correcting unit according to multiple sites is spent, it is vertical direction that uniformly correction, which is front, by maize leaf;Distance measuring unit Picture size and reality are calculated according to the angle of image information collecting point, the elevation information with the distance of plant, from the ground The scaling of size measures width, length, the three-dimensional digital information of height and the plant height information of blade;Areal calculation list Member is calculated per the area of a piece of greenery and dead leaf area, and it is the greenery area of single plant corn and dead leaf area to sum it up.
2. Estimating Leaf Area In Maize dynamic nondestructive as described in claim 1 monitors system, which is characterized in that the location information acquisition Unit includes gps position indicators, gyroscope and accelerometer, and gps position indicators are used to acquire the longitude and latitude and height above sea level of Image Acquisition point Information, gyroscope are used to acquire movement angle and the track of image capture module, and accelerometer is used to acquire image capture module The speed and distance of movement.
3. Estimating Leaf Area In Maize dynamic nondestructive as described in claim 1 monitors system, which is characterized in that the location information determines Unit includes two parts of position instruction and position alignment, and position instruction part indicates 8 images according to the requirement of Image Acquisition Collection point carries out Image Acquisition, and is displayed on the screen;Position alignment part is according to position instruction guiding photographing person by image Acquisition frame is aligned with position instruction frame.
4. Estimating Leaf Area In Maize dynamic nondestructive as described in claim 1 monitors system, which is characterized in that described information transmission module Including wireless transmission unit, radio receiving unit and completeness check unit, the information of acquisition is converted by wireless transmission unit Radio signal, and sent by wireless frequency modulation mode;Radio receiving unit receives information by wireless frequency modulation mode, and will connect The radio signal of receipts is converted into digital information;Completeness check unit is by comparing the information characteristics sent and received It is right, it is ensured that transmit errorless and information completely.
5. a kind of Estimating Leaf Area In Maize dynamic nondestructive monitoring method, which is characterized in that include the following steps:
Step 1:Acquire multi-angle, the various dimensions image of 8 different locis of maize leaf to be monitored:
Determine the geographical location information in 8 different locis and each site;Corresponding each site, acquires piece image, is acquired The quality parameter information of the corresponding location information of image and image and the geographical location information and picture quality in identified site Require information is consistent, then stores image;
Step 2:Acquired image information is sent to image processing module, calculates Estimating Leaf Area In Maize parameter:
The color of acquired maize leaf is identified first, determines fresh and alive maize leaf region, vein region, withered and yellow jade Rice leaf area, sundries region;According to color recognition result, vein and the sideline of maize leaf are marked, and to wherein by it The part that its blade blocks carries out extension polishing according to front and rear section is blocked;According to vein state recognition blade 3 d pose, divide Length, width and the deviation horizontal direction angle of each maize leaves of segment mark;According to the image in 8 sites, maize leaf is united It is vertical direction that one correction, which is front,;According to the angle of image information collecting point, distance, height from the ground with plant Information calculates the scaling of picture size and actual size, measure the width of blade, length, height three-dimensional digital information, It calculates per the area of a piece of greenery and dead leaf area, it is the greenery area of single plant corn and dead leaf area to sum it up.
6. Estimating Leaf Area In Maize dynamic nondestructive monitoring method as claimed in claim 5, which is characterized in that right in the step 2 The process that the color of acquired maize leaf is identified is:According to color characteristic, it is fresh and alive maize leaf that identification is green, greyish white Color is vein, and yellow is withered and yellow maize leaf, and other is sundries;Maize leaf region is identified and marked, is marked fresh Work maize leaf region, vein region, withered and yellow maize leaf region, sundries region;Simultaneously to the identity element in different images It is marked and identifies, avoid repeating;According to corncob it is conical the characteristics of, distinguish maize leaves and corncob.
7. Estimating Leaf Area In Maize dynamic nondestructive monitoring method as claimed in claim 6, which is characterized in that in the step 2, point The length of each maize leaves of segment mark, width and when deviateing horizontal direction angle, the identical region of blade posture is same section, The different region of posture marks respectively.
8. Estimating Leaf Area In Maize dynamic nondestructive monitoring method as claimed in claim 7, which is characterized in that, will in the step 2 The unified correction of maize leaf is that the process that front is vertical direction is:Correction is divided into blade longitudinally two steps of correction and lateral correction Suddenly, wherein longitudinal direction correction width of blade is constant, length of blade is adjusted according to angle, calculation formula is strong for y ˊ=y/sin α, y ˊ Length of blade after just, y survey length of blade for figure, and α is the angle in blade offset level direction;Laterally correct length of blade not Become, width of blade is adjusted according to angle, calculation formula is the width of blade that x ˊ=x/sin α, x ˊ are after correction, and x surveys blade for figure Width, α are the angle in blade offset level direction.
CN201510157959.0A 2015-04-03 2015-04-03 A kind of Estimating Leaf Area In Maize dynamic nondestructive monitoring device and method Active CN104732564B (en)

Priority Applications (1)

Application Number Priority Date Filing Date Title
CN201510157959.0A CN104732564B (en) 2015-04-03 2015-04-03 A kind of Estimating Leaf Area In Maize dynamic nondestructive monitoring device and method

Applications Claiming Priority (1)

Application Number Priority Date Filing Date Title
CN201510157959.0A CN104732564B (en) 2015-04-03 2015-04-03 A kind of Estimating Leaf Area In Maize dynamic nondestructive monitoring device and method

Publications (2)

Publication Number Publication Date
CN104732564A CN104732564A (en) 2015-06-24
CN104732564B true CN104732564B (en) 2018-06-19

Family

ID=53456432

Family Applications (1)

Application Number Title Priority Date Filing Date
CN201510157959.0A Active CN104732564B (en) 2015-04-03 2015-04-03 A kind of Estimating Leaf Area In Maize dynamic nondestructive monitoring device and method

Country Status (1)

Country Link
CN (1) CN104732564B (en)

Families Citing this family (9)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN105004327A (en) * 2015-07-09 2015-10-28 北京师范大学 Intelligent terminal-based vegetation leaf area index information automatic measurement system
CN107966944B (en) * 2017-11-30 2020-12-08 贵州财经大学 Intelligent greenhouse partition control system and partition picking method
CN108871235A (en) * 2018-04-27 2018-11-23 江南大学 The information acquisition method and plant leaf information acquisition system of plant leaf
CN109784685B (en) * 2018-12-27 2021-10-08 固安京蓝云科技有限公司 Crop growth analysis method and device
CN110332909B (en) * 2019-07-09 2024-05-31 河海大学 Portable leaf area meter
CN113063704B (en) * 2020-12-04 2022-03-11 湖北沛丰生物科技股份有限公司 Particle fullness analysis platform and method
CN113197035A (en) * 2021-04-21 2021-08-03 宁夏红双赢粮油食品有限公司 Seedling breeding method, device and system for selenium-enriched rice
CN114241033B (en) * 2021-12-17 2022-07-22 贵州省山地资源研究所 Ectopic acquisition method for plant leaf area vertical structure
CN116740704B (en) * 2023-06-16 2024-02-27 安徽农业大学 Wheat leaf phenotype parameter change rate monitoring method and device based on deep learning

Citations (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN101324427A (en) * 2008-07-31 2008-12-17 华中科技大学 Device and method for automatically measuring greenery area
CN102778212A (en) * 2012-08-02 2012-11-14 浙江大学 Method and device for utilizing digital camera to obtain rice canopy leaf area index
CN103530611A (en) * 2013-09-30 2014-01-22 南京林业大学 Object recognition system and recognition method thereof
CN104006760A (en) * 2014-05-12 2014-08-27 上海交通大学 Device and method for continuously monitoring three-dimensional geometrical morphology of growth and development of plant

Family Cites Families (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
KR20140147343A (en) * 2013-06-19 2014-12-30 한국전자통신연구원 System for collecting growth information of crop in greenhouse

Patent Citations (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN101324427A (en) * 2008-07-31 2008-12-17 华中科技大学 Device and method for automatically measuring greenery area
CN102778212A (en) * 2012-08-02 2012-11-14 浙江大学 Method and device for utilizing digital camera to obtain rice canopy leaf area index
CN103530611A (en) * 2013-09-30 2014-01-22 南京林业大学 Object recognition system and recognition method thereof
CN104006760A (en) * 2014-05-12 2014-08-27 上海交通大学 Device and method for continuously monitoring three-dimensional geometrical morphology of growth and development of plant

Also Published As

Publication number Publication date
CN104732564A (en) 2015-06-24

Similar Documents

Publication Publication Date Title
CN104732564B (en) A kind of Estimating Leaf Area In Maize dynamic nondestructive monitoring device and method
CN109470299A (en) A kind of plant growth information monitoring system and method based on Internet of Things
JP5020444B2 (en) Crop growth measuring device, crop growth measuring method, crop growth measuring program, and computer-readable recording medium recording the crop growth measuring program
US20210345567A1 (en) Method and system for plant stress determination and irrigation based thereon
CN112418188B (en) Crop growth whole-course digital evaluation method based on unmanned aerial vehicle vision
Nielsen et al. Vision-based 3D peach tree reconstruction for automated blossom thinning
CN110213376B (en) Information processing system and method for insect pest prevention
US20170042081A1 (en) Systems, methods and apparatuses associated with soil sampling
CN102778212A (en) Method and device for utilizing digital camera to obtain rice canopy leaf area index
CN102331244A (en) Method of acquiring leaf area index (LAI) of rice canopy by using common digital camera
JP6996560B2 (en) Crop cultivation support device
CN102256102A (en) Agricultural condition information real-time monitoring method and system based on remote monitoring
CN107367300A (en) A kind of crop growth environment monitoring system based on unmanned plane
CN109270952A (en) A kind of agricultural land information acquisition system and method
CN109598215A (en) Orchard modeling analysis system and method based on positioning shooting of unmanned aerial vehicle
CN211477203U (en) Refined monitoring equipment system based on high-resolution remote sensing image
KR102479284B1 (en) Vegetation index acquisition unit and apparatus for monitoring plant comprising the same
CN105181632B (en) NDVI measuring device is imaged in network-type various dimensions plant
Waine et al. Towards improving the accuracy of opium yield estimates with remote sensing
CN104730981A (en) Multi-parameter crop growth recording instrument device
CN108871235A (en) The information acquisition method and plant leaf information acquisition system of plant leaf
KR20180086832A (en) Image-based crop growth data measuring mobile app. and device therefor
CN111814585A (en) Unmanned aerial vehicle near-ground-to-air crop seedling condition remote sensing monitoring method and device and storage medium
CN110728205A (en) AI cloud computing-based portable intelligent rice seed test system
Feng et al. Developing an image processing pipeline to improve the position accuracy of single UAV images

Legal Events

Date Code Title Description
C06 Publication
PB01 Publication
C10 Entry into substantive examination
SE01 Entry into force of request for substantive examination
CB03 Change of inventor or designer information

Inventor after: Zhang Yongen

Inventor after: Zhuang Jiayu

Inventor after: Gao Liwei

Inventor after: Wang Shengwei

Inventor after: Xu Shiwei

Inventor after: Li Ganqiong

Inventor after: Wang Dongjie

Inventor after: Chen Wei

Inventor after: Li Denghua

Inventor before: Zhang Yongen

Inventor before: Li Ganqiong

Inventor before: Wang Dongjie

Inventor before: Chen Wei

Inventor before: Zhuang Jiayu

Inventor before: Li Denghua

CB03 Change of inventor or designer information
GR01 Patent grant
GR01 Patent grant
EE01 Entry into force of recordation of patent licensing contract

Application publication date: 20150624

Assignee: Foshan lelian Technology Co.,Ltd.

Assignor: Agricultural Information Institute of CAAS

Contract record no.: X2023980032298

Denomination of invention: A Nondestructive Dynamic Monitoring Device and Method for Maize Leaf Area

Granted publication date: 20180619

License type: Common License

Record date: 20230216

EE01 Entry into force of recordation of patent licensing contract