CN113128462A - Greenhouse plant canopy structure identification method based on LIDAR - Google Patents
Greenhouse plant canopy structure identification method based on LIDAR Download PDFInfo
- Publication number
- CN113128462A CN113128462A CN202110493489.0A CN202110493489A CN113128462A CN 113128462 A CN113128462 A CN 113128462A CN 202110493489 A CN202110493489 A CN 202110493489A CN 113128462 A CN113128462 A CN 113128462A
- Authority
- CN
- China
- Prior art keywords
- crown
- plant
- highest
- tomato plant
- canopy
- 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.)
- Pending
Links
- 238000000034 method Methods 0.000 title claims abstract description 19
- 241000196324 Embryophyta Species 0.000 claims abstract description 30
- 238000004364 calculation method Methods 0.000 claims abstract description 9
- 230000012010 growth Effects 0.000 claims abstract description 6
- 238000010586 diagram Methods 0.000 claims abstract description 5
- 240000003768 Solanum lycopersicum Species 0.000 claims description 39
- 238000001514 detection method Methods 0.000 claims description 7
- 238000004458 analytical method Methods 0.000 claims description 6
- 239000000284 extract Substances 0.000 claims description 4
- 239000000178 monomer Substances 0.000 claims description 4
- 238000001914 filtration Methods 0.000 claims description 3
- 241000227653 Lycopersicon Species 0.000 abstract 6
- 235000007688 Lycopersicon esculentum Nutrition 0.000 description 3
- 238000005516 engineering process Methods 0.000 description 2
- 238000000605 extraction Methods 0.000 description 2
- 238000007792 addition Methods 0.000 description 1
- 230000007547 defect Effects 0.000 description 1
- 230000005484 gravity Effects 0.000 description 1
- 230000001788 irregular Effects 0.000 description 1
- 238000012986 modification Methods 0.000 description 1
- 230000004048 modification Effects 0.000 description 1
- 230000002093 peripheral effect Effects 0.000 description 1
- 230000008635 plant growth Effects 0.000 description 1
- 230000001737 promoting effect Effects 0.000 description 1
- 238000006467 substitution reaction Methods 0.000 description 1
- 230000001360 synchronised effect Effects 0.000 description 1
- 230000000007 visual effect Effects 0.000 description 1
Images
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
- G06V20/00—Scenes; Scene-specific elements
- G06V20/10—Terrestrial scenes
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F18/00—Pattern recognition
- G06F18/20—Analysing
- G06F18/25—Fusion techniques
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
- G06V10/00—Arrangements for image or video recognition or understanding
- G06V10/20—Image preprocessing
- G06V10/25—Determination of region of interest [ROI] or a volume of interest [VOI]
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
- G06V20/00—Scenes; Scene-specific elements
- G06V20/35—Categorising the entire scene, e.g. birthday party or wedding scene
- G06V20/36—Indoor scenes
Landscapes
- Engineering & Computer Science (AREA)
- Theoretical Computer Science (AREA)
- Physics & Mathematics (AREA)
- General Physics & Mathematics (AREA)
- Multimedia (AREA)
- Data Mining & Analysis (AREA)
- Artificial Intelligence (AREA)
- Evolutionary Biology (AREA)
- Evolutionary Computation (AREA)
- Computer Vision & Pattern Recognition (AREA)
- General Engineering & Computer Science (AREA)
- Bioinformatics & Computational Biology (AREA)
- Bioinformatics & Cheminformatics (AREA)
- Life Sciences & Earth Sciences (AREA)
- Length Measuring Devices By Optical Means (AREA)
Abstract
The invention relates to a plant canopy structure identification method, in particular to a greenhouse plant canopy structure identification method based on LIDAR; the method comprises the following steps: step 1, scanning the growth condition of a plant group in a greenhouse by an unmanned aerial vehicle with a radar; step 2, constructing a three-dimensional model of a plant group in the greenhouse; step 3, generating a reference diagram of tomato plant group distribution and height information; step 4, extracting the top point (highest point) of the canopy of the highest tomato plant; step 5, constructing a stem three-dimensional graph of the highest tomato plant; step 6, constructing a three-dimensional map of the branch and stem of the highest tomato plant; step 7, acquiring the crown-shaped outline of the highest tomato plant; step 8, obtaining a crown-shaped boundary recognition result of the tomato plant; and 9, combining the identification result of the top point of the canopy and the boundary of the canopy, and generating a single canopy volume distribution map by a canopy volume calculation method based on the ratio of the telescopic circle to the canopy height.
Description
Technical Field
The invention relates to a plant canopy structure identification method, in particular to a greenhouse canopy structure identification method based on LIDAR.
Background
Remote sensing as a novel earth observation technology has the advantages of large-area synchronous coverage, real-time continuity, economy, effectiveness and the like. The multi-source remote sensing data such as high-resolution remote sensing, laser radar and the like provide a new visual angle and a new research direction for space detection. The full-automatic and high-precision stereoscopic scanning technology owned by the LiDAR enables rapid and direct acquisition of terrain surface models, is particularly suitable for acquisition of information which has a three-dimensional space structure and is irregular in stereoscopic form, such as vegetation and the like, and gradually becomes an important carrier for promoting the urban green land research to be expanded to the stereoscopic mode.
At present, in the research on vegetation based on LiDAR at home and abroad, monomer vegetation information extraction is mainly used, multi-source data is fused, but the research on the three-dimensional information extraction of greenhouse vegetation is less, and the traditional peripheral scanning cannot extract the plant growth condition in a greenhouse, so that an attempt is made to establish a set of greenhouse plant canopy structure identification method based on LIDAR for providing technical reference for canopy structure information in the planting process of tomatoes in the greenhouse.
Disclosure of Invention
The invention aims to overcome the defects and provide a method for identifying canopy structures of greenhouse plants based on LIDAR (light detection and ranging) for detecting the growth conditions of the canopy structures in the growth process of tomatoes in a temperature measuring chamber.
In order to achieve the purpose, the invention adopts the following technical scheme:
a greenhouse plant canopy structure identification method based on LIDAR comprises the following steps: s01, enabling the unmanned aerial vehicle with the radar to fly along the planting direction of the tomato plants, scanning the growth conditions of plant groups in the greenhouse through the radar, and sending the scanning results to the controller;
s02, the controller constructs a three-dimensional model of the plant population in the greenhouse according to the scanning result cloud data of the radar;
s03, automatically filtering vegetation information of non-tomato plants in the three-dimensional model of the plant population by the analysis processor to obtain a reference diagram containing distribution and height information of only tomato plant populations;
s04, the analysis processor extracts the canopy top point (highest point) of the highest tomato plant from the reference map;
s05, constructing a main stem three-dimensional graph of the highest tomato plant on the basis of the canopy top point of the highest tomato plant and the reference graph;
s06, constructing a branch-stem three-dimensional graph of the highest tomato plant according to the main-stem three-dimensional graph and the reference graph;
SO7, constructing a leaf of the highest tomato plant according to the main stem three-dimensional graph, the reference graph and the branch stem three-dimensional graph, thereby obtaining the crown-shaped outline of the highest tomato plant;
s08, separating the individual plants according to the crown-shaped outline of the highest tomato plant and determining the boundary positions of the respective crown-shaped outlines to obtain a tomato plant crown-shaped boundary identification result;
s09, generating a monomer crown volume distribution map by combining the recognition result of the crown layer vertex and the crown shape boundary based on a crown shape volume calculation method of the ratio of the telescopic circle to the crown height; the specific method comprises the following steps: a. on the basis of the crown-shaped boundary identification result, acquiring parameters of a long half shaft and a short half shaft of an ellipsoid-shaped structure by using a telescopic circle algorithm; b. calculating by combining the height information of the canopy vertex detection result and a crown height ratio concept to obtain a polar radius parameter; c. finally obtaining the estimated quantity of the tomato plant volume through an ellipsoid volume calculation formula.
Drawings
In order to more clearly illustrate the detailed description of the invention or the technical solutions in the prior art, the drawings that are needed in the detailed description of the invention or the prior art will be briefly described below. Throughout the drawings, like elements or portions are generally identified by like reference numerals. In the drawings, elements or portions are not necessarily drawn to scale.
Fig. 1 is a method step diagram of a LIDAR greenhouse plant canopy structure-based identification method.
Detailed Description
Referring to fig. 1, the embodiment provides a method for identifying canopy structures of greenhouse plants based on LIDAR, which includes the following steps: s01, enabling the unmanned aerial vehicle with the radar to fly along the planting direction of the tomato plants, scanning the growth conditions of plant groups in the greenhouse through the radar, and sending the scanning results to the controller;
s02, the controller constructs a three-dimensional model of the plant population in the greenhouse according to the scanning result cloud data of the radar;
s03, automatically filtering vegetation information of non-tomato plants in the three-dimensional model of the plant population by the analysis processor to obtain a reference diagram containing distribution and height information of only tomato plant populations;
s04, the analysis processor extracts the canopy top point (highest point) of the highest tomato plant from the reference map; in this embodiment, the canopy apex (highest point) of a plant is generally the highest point of vegetation within a certain clustering range, and it is assumed that there is a certain correlation between canopy diameter and plant height. Firstly, equally dividing an image into grids of N multiplied by N, randomly selecting any tomato strain from each grid in sequence, and measuring the average value and the maximum height value of the diameter and the length of the transverse and longitudinal crowns. Along with the increase of the plant height, the crown-shaped diameter is enlarged, and the plant height and the crown-shaped diameter basically present a linear relation, so that a plant height-crown diameter relation model is established. This model will be used to determine the search range during a pixel-by-pixel traversal.
S05, constructing a main stem three-dimensional graph of the highest tomato plant on the basis of the canopy top point of the highest tomato plant and the reference graph;
s06, constructing a branch-stem three-dimensional graph of the highest tomato plant according to the main-stem three-dimensional graph and the reference graph;
SO7, constructing a leaf of the highest tomato plant according to the main stem three-dimensional graph, the reference graph and the branch stem three-dimensional graph, thereby obtaining the crown-shaped outline of the highest tomato plant;
s08, separating the individual plants according to the crown-shaped outline of the highest tomato plant and determining the boundary positions of the respective crown-shaped outlines to obtain a tomato plant crown-shaped boundary identification result;
s09, generating a monomer crown volume distribution map by combining the recognition result of the crown layer vertex and the crown shape boundary based on a crown shape volume calculation method of the ratio of the telescopic circle to the crown height; the specific method comprises the following steps: a. on the basis of the crown-shaped boundary identification result, acquiring parameters of a long half shaft and a short half shaft of an ellipsoid-shaped structure by using a telescopic circle algorithm; b. calculating by combining the height information of the canopy vertex detection result and a crown height ratio concept to obtain a polar radius parameter; c. finally obtaining the estimated quantity of the tomato plant volume through an ellipsoid volume calculation formula;
in the embodiment, the telescopic circle algorithm generates detection circles Cr with different radius lengths r from small to large by taking the center of gravity of a crown-shaped projection polygon as the center of a circle on the basis of the crown-shaped boundary identification result; when the radius r of the detection circle starts from 1 and a single pixel is taken as a step length to accumulate, when Si occurs for the first time, the corresponding r1 value is the minor semi-axis b of the ellipsoid; when the first occurrence happens, the corresponding r2 value is the major semi-axis a of the ellipsoid; traversing all the crown shape boundary recognition results in sequence, and generating a series of ellipse long and short semi-axis values corresponding to the crown shape; the crown height ratio is the ratio of crown height to plant height. Assuming that the geometric shape of the crown conforms to the characteristics of an ellipsoid, namely the maximum value of the ellipsoid cut area appears at one half of the height of the crown, the boundary of the ellipsoid is the boundary of the crown, the average value hc of the pixel heights falling on the boundary point is known, and the polar radius c of the ellipsoid can be calculated and solved by combining the geometric relationship between the height of the boundary point and the height ht of the top point of the crown layer through the formula c-ht-hc; and finally substituting the volume of the ellipsoid into a calculation formula V of 4 pi abc/3 to obtain the space geometric volume occupied by the crown.
The specific embodiments described herein are merely illustrative of the spirit of the invention. Various modifications, additions and substitutions for the described embodiments may be made by those skilled in the art without departing from the scope and spirit of the invention as defined by the accompanying claims.
Claims (1)
1. A greenhouse plant canopy structure identification method based on LIDAR is characterized in that: the method comprises the following steps:
s01, enabling the unmanned aerial vehicle with the radar to fly along the planting direction of the tomato plants, scanning the growth conditions of plant groups in the greenhouse through the radar, and sending the scanning results to the controller;
s02, the controller constructs a three-dimensional model of the plant population in the greenhouse according to the scanning result cloud data of the radar;
s03, automatically filtering vegetation information of non-tomato plants in the three-dimensional model of the plant population by the analysis processor to obtain a reference diagram containing distribution and height information of only tomato plant populations;
s04, the analysis processor extracts the canopy top point (highest point) of the highest tomato plant from the reference map;
s05, constructing a main stem three-dimensional graph of the highest tomato plant on the basis of the canopy top point of the highest tomato plant and the reference graph;
s06, constructing a branch-stem three-dimensional graph of the highest tomato plant according to the main-stem three-dimensional graph and the reference graph;
SO7, constructing a leaf of the highest tomato plant according to the main stem three-dimensional graph, the reference graph and the branch stem three-dimensional graph, thereby obtaining the crown-shaped outline of the highest tomato plant;
s08, separating the individual plants according to the crown-shaped outline of the highest tomato plant and determining the boundary positions of the respective crown-shaped outlines to obtain a tomato plant crown-shaped boundary identification result;
s09, generating a monomer crown volume distribution map by combining the recognition result of the crown layer vertex and the crown shape boundary based on a crown shape volume calculation method of the ratio of the telescopic circle to the crown height; the specific calculation method comprises the following steps: a. on the basis of the crown-shaped boundary identification result, acquiring parameters of a long half shaft and a short half shaft of an ellipsoid-shaped structure by using a telescopic circle algorithm; b. calculating by combining the height information of the canopy vertex detection result and a crown height ratio concept to obtain a polar radius parameter; c. finally obtaining the estimated quantity of the tomato plant volume through an ellipsoid volume calculation formula.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202110493489.0A CN113128462A (en) | 2021-05-07 | 2021-05-07 | Greenhouse plant canopy structure identification method based on LIDAR |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202110493489.0A CN113128462A (en) | 2021-05-07 | 2021-05-07 | Greenhouse plant canopy structure identification method based on LIDAR |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN113128462A true CN113128462A (en) | 2021-07-16 |
Family
ID=76781561
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202110493489.0A Pending CN113128462A (en) | 2021-05-07 | 2021-05-07 | Greenhouse plant canopy structure identification method based on LIDAR |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN113128462A (en) |
Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN103942835A (en) * | 2014-04-22 | 2014-07-23 | 浙江省农业科学院 | Method for building oilseed-rape group model |
| CN104463164A (en) * | 2014-09-03 | 2015-03-25 | 中国科学院遥感与数字地球研究所 | Tree canopy structure information extraction method based on rib method and crown height ratio |
| CN109816680A (en) * | 2018-12-19 | 2019-05-28 | 黑龙江八一农垦大学 | A kind of high-throughput calculation method of crops plant height |
| CN110046613A (en) * | 2019-05-16 | 2019-07-23 | 北京农业信息技术研究中心 | A kind of crop canopies growth in situ phenotype monitoring device and three-dimensional rebuilding method |
-
2021
- 2021-05-07 CN CN202110493489.0A patent/CN113128462A/en active Pending
Patent Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN103942835A (en) * | 2014-04-22 | 2014-07-23 | 浙江省农业科学院 | Method for building oilseed-rape group model |
| CN104463164A (en) * | 2014-09-03 | 2015-03-25 | 中国科学院遥感与数字地球研究所 | Tree canopy structure information extraction method based on rib method and crown height ratio |
| CN109816680A (en) * | 2018-12-19 | 2019-05-28 | 黑龙江八一农垦大学 | A kind of high-throughput calculation method of crops plant height |
| CN110046613A (en) * | 2019-05-16 | 2019-07-23 | 北京农业信息技术研究中心 | A kind of crop canopies growth in situ phenotype monitoring device and three-dimensional rebuilding method |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN106815847B (en) | Trees dividing method and single tree extracting method based on laser radar point cloud | |
| CN104463164B (en) | It is a kind of based on umbrella frame method and crown height than trees canopy structure information extracting method | |
| CN112819830B (en) | Single tree crown segmentation method based on deep learning and airborne laser point cloud | |
| CN106204547B (en) | The method that rod-shaped atural object spatial position is automatically extracted from Vehicle-borne Laser Scanning point cloud | |
| CN107273902B (en) | A method of pylon point cloud is automatically extracted from on-board LiDAR data | |
| CN107085710A (en) | A kind of single wooden extraction method based on multispectral LiDAR data | |
| CN106815850A (en) | The method that canopy density forest reserves very high is obtained based on laser radar technique | |
| CN106529469A (en) | Unmanned aerial vehicle airborne LiDAR point cloud filtering method based on adaptive gradient | |
| CN106383998B (en) | A kind of tree breast-height diameter automatic calculating method based on ground laser radar scanning | |
| CN104484882A (en) | City region power line detection method based on airborne LiDAR (light detection and ranging) data | |
| JP6347064B2 (en) | Laser measurement result analysis system | |
| CN104048618B (en) | A kind of damage building detection method | |
| CN114119863B (en) | Method for automatically extracting street tree targets and forest attributes thereof based on vehicle-mounted laser radar data | |
| CN115063555B (en) | Vehicle-mounted LiDAR point cloud street tree extraction method for Gaussian distribution area growth | |
| CN104318611A (en) | Three-dimensional tree re-establishing method based on laser scanning point cloud | |
| CN114065339A (en) | High tower construction site selection method based on three-dimensional visual model | |
| CN113269825B (en) | Forest breast diameter value extraction method based on foundation laser radar technology | |
| CN115641412B (en) | Three-dimensional semantic map generation method based on hyperspectral data | |
| CN109407177A (en) | Dense fog identifying system and methods for using them based on machine learning and conventional meteorological observation | |
| CN109766824A (en) | Main passive remote sensing data fusion classification method based on Fuzzy Evidence Theory | |
| CN109002418A (en) | Tree breast-height diameter automatic calculating method based on Voxels growing and ground laser point cloud | |
| CN117409322B (en) | Regional forest natural resource ecological estimation method and system based on air-ground remote sensing combination | |
| CN110569805B (en) | Artificial forest stand wood extraction and standing quality evaluation method based on unmanned aerial vehicle image point cloud | |
| CN106023178B (en) | Method for detecting single tree in remote sensing data based on gradient direction clustering | |
| CN107993242B (en) | Method for extracting boundary of missing area based on airborne LiDAR point cloud data |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| RJ01 | Rejection of invention patent application after publication |
Application publication date: 20210716 |
|
| RJ01 | Rejection of invention patent application after publication |