KR20180086776A - Method Tagging Images with Plant Identifier Using a Tagging Application, Mobile Smart Device Comprising The Same, And Plant Growth Information Analysis System - Google Patents

Abstract

The present invention relates to a method to tag and analyze plant identification information by using a tagging application, a portable smart device executing the same, and a plant growth information analysis system including the same. According to the present invention, the portable smart device comprises: a camera to acquire an image; a memory unit to store a tagging application for tagging plant identification information to a plant image; an application control unit to execute the tagging application; a display unit to display a user interface screen in accordance with execution of the tagging application; and a communication unit to communicate with the outside. The tagging application comprises: an identification information recognition unit to recognize identification information of a plant; an image acquisition unit to activate the camera to acquire the image of the plant; a tagging unit to tag identification information of the plant to the image information of the plant; and a transmission unit to transmit image information of the plant tagged with the identification information to an analysis server. Accordingly, particulars of each portion of an individual plant are photographed as an image, and the identification information of the individual plant is tagged to be transmitted to an analysis server, thereby being able to simply add growth data of the plant.

Description

FIELD OF THE INVENTION [0001] The present invention relates to a method for tagging and analyzing plant identification information using a tagging application, a portable smart device for executing the same, and a plant growth information analysis system including the method. Plant Growth Information Analysis System}

The present invention relates to a method for tagging and analyzing plant identification information using a tagging application, a portable smart device for executing the same, and a plant growth information analysis system including the same. More particularly, Tagging identification information together with an image of the plant, and analyzing the plant image to extract the growth information of the plant.

Plant breeding involves the analysis of the characteristics of individual individuals within a variety of plant genetic resources, plant selection, selection of superior individuals within a population for plant breeding, and identification of specific mutants within a plant genetic modification or anthropogenic mutant population Analysis, and selection.

Plant phenotypic analysis was performed by directly measuring the plant height, the number of leaves, color and shape, or chemically analyzing a part of the plant. However, analysis based on the human eye requires a lot of air and work time, and it can be analyzed differently for each person, so that reliability and accuracy are degraded.

To solve these problems, a system for automatically analyzing the growth data of a large number of plants has been developed and utilized by seed companies and breeding research institutes.

Conventionally, a system for automatically analyzing plant growth data utilizes a method of acquiring and analyzing the image of a plant by attaching identification means to each of the plant containers and sequentially moving the same through the transfer equipment to the inspection chamber.

However, since the inspection chamber for obtaining plant imaging acquires an image of the whole plant and analyzes it, even if there is a singular point in a part of a stem or a leaf of a plant, it is easy to overlook, and even if a plant is identified, There is a lack of detailed data on the analysis, which makes analysis difficult.

In such a case, it is necessary to acquire an image of a plant in which the researcher or the worker has found a specific matter that needs analysis, and separately store the image in the growth data analysis DB. However, in order to perform such work, it is necessary to store the plant image acquired by the researcher or the worker as additional identification information of each plant, and it is also difficult for the operator to individually memorize and input the identification information of the plant that images the image, Inputting the image or data into the analysis DB is also very cumbersome.

In addition, there is a problem that it is difficult to guarantee the reliability of data because each researcher or worker acquires the image of the plant, the camera operation skill, the camera image pickup condition, and the camera operation method are different.

In particular, the phenotype data of a plant is very important to analyze the size and color of the plant. Since the distance between the camera and the plant and the imaging conditions of the camera such as white balance are different for each researcher or operator, There is a problem that it is not possible to compare itself.

In order to solve the above-mentioned problems, in the present invention, it is possible to add plant growth data by simply photographing specific plant-specific information of each plant, tagging identification information of individual plants together, A method for tagging plant identification information using a tagging application, and a portable smart device for executing the method.

In addition, a machine learning model of the growth information is constructed through machine learning using the collected plant image DB, and the plant image captured by the portable smart device is analyzed and processed based on the machine learning model, , A fruit, an egg, and the like, a growth information such as an area, a color, and the like is calculated, thereby providing a reliable analysis even if the photographer or the photographing apparatus is different.

Further, by setting the ROI of the plant, it is possible to provide a method of tagging the plant identification information that provides information so as to clearly analyze the plant specific information at the time of the later image analysis, A portable smart device and a growth information analysis system.

The object is achieved by a camera for acquiring an image; A memory unit storing a tagging application for tagging plant identification information on a plant image; An application control unit for executing the tagging application; A display unit for displaying a user interface screen according to execution of the tagging application; And a communication unit for communicating with the outside; The tagging application includes an identification information recognizing unit for recognizing the identification information of the plant, an image acquiring unit for acquiring an image of the plant by activating the camera, a tagging unit for tagging the identification information of the plant to image information of the plant, And a transmitting unit for transmitting the image information of the plant tagged with the identification information to the analysis server.

Here, the image obtaining unit may include a region of interest setting unit that can input or select a region of interest of the plant; And an information storage unit for storing information about a region of interest of the plant in the image information of the plant when the image of the plant is acquired.

In addition, the identification information recognizing unit may include at least one of RFID, QR code, and bar code recognition unit.

In addition, the tagging application may further include a user input unit for inputting a specific item of the plant from a user.

Further, the tagging application may include an information requesting unit for transmitting identification information of the plant to the analysis server to request individual information on the plant, and object information about the plant transmitted from the analysis server Wherein the individual information on the plant includes at least one of genetic information of the plant, 2D or 3D image information of the plant, cultivation environment information of the plant, growth information of the plant, and phenotype information of the plant .

The tagging application may further include a growth information calculating unit for calculating a growth characteristic information of a plant by analyzing an image of the plant acquired through the image obtaining unit using a machine learning model, Characteristic information may be stored in the image information of the plant.

The growth characteristics information of the plant may include leaf size, stem, branch or fruit size, area, and color information of the plant.

The above object is also achieved by a portable smart device for recognizing identification information of a plant using identification information recognition means, acquiring an image of the plant, and transmitting the image of the plant to the analysis server together with the identification information; And a growth information calculation unit for calculating a growth characteristic information of the plant by analyzing the image of the plant transmitted from the portable smart device using a machine learning model unit constructed through machine learning Can also be achieved by a growth information analysis system.

Here, the growth information calculating unit extracts areas of leaves, stems, fruits, or branches from the images of the plants using the model constructed through machine learning, and performs matching with the reference model to determine the leaves, stems, The size, area, and color information of branches or fruits can be calculated.

According to another aspect of the present invention, there is provided a method for tagging and analyzing plant identification information using a tagging application, the method comprising: executing the tagging application in a smart device; Recognizing the identification information of the plant using the identification information recognition means; Obtaining an image of the plant using a camera of the smart device; Tagging the identification information of the plant to the image information of the plant; And analyzing the image of the plant through a machine learning model to calculate the growth characteristics information of the plant.

The step of calculating the growth characteristics information includes extracting leaf, stem, fruit, or branch regions from the image of the plant using a model constructed through machine learning; And a step of calculating size, area, and color information of leaves, stems, branches or fruits of plants by performing matching with the reference model.

In addition, the step of acquiring the image of the plant may include inputting or selecting a region of interest of the plant, and storing information about the region of interest of the plant in the image information of the plant when the image of the plant is acquired Step < / RTI >

Transmitting identification information of the plant to the analysis server to request individual information about the plant; And displaying entity information on the plant transmitted from the analysis server by item; The individual information on the plant may include at least one of genetic information of the plant, 2D or 3D image information of the plant, cultivation environment information of the plant, growth information of the plant, and phenotype information of the plant.

As described above, the method for tagging the plant identification information according to the present invention and the portable smart device for executing the method according to the present invention take an image of the specific matters of each plant and tag the identification information of the individual plants together and transmit them to the analysis server The growth data of the plant can be simply added.

In addition, by analyzing and processing plant images photographed by a portable smart device on the basis of a machine learning model, the information such as the size, area, and color of leaves, stems, fruits, Reliable analysis can be assured even if different.

Further, by setting the ROI of the plant, it is possible to provide additional information so that the analysis of the plant image can be clearly analyzed without overlooking the plant characteristics.

1 is a schematic diagram of a plant growth information analysis system for tagging and analyzing plant identification information using a tagging application according to an embodiment of the present invention.
2 is a control block diagram of a portable smart device in which a tagging application according to an embodiment of the present invention is stored and executed.
3 is a schematic diagram of a tagging application in accordance with an embodiment of the present invention.
4 is a schematic diagram of an image acquisition unit according to an embodiment of the present invention.
5 is an example of a region-of-interest setting screen according to an embodiment of the present invention.
FIG. 6 is a schematic diagram of an internal configuration of an analysis server in the plant growth information analysis system of FIG. 1;
7 is a schematic diagram of a plant information verification application according to an embodiment of the present invention.
FIGS. 8 to 12 show an example of an item-specific implementation screen of the plant information confirmation application.
13 is a flowchart of a method of tagging plant identification information using a tagging application according to an embodiment of the present invention.
14 is a flowchart for explaining the process of calculating the growth information of a plant by analyzing the image of the plant.

Hereinafter, specific embodiments of the present invention will be described with reference to the drawings.

1 is a schematic diagram of a system for tagging plant identification information using a tagging application 100 according to an embodiment of the present invention. 1, a plant entity information tagging system using a tagging application 100 according to an embodiment of the present invention includes a portable smart device 1 and an analysis server 2 as a tagging application 100 .

The portable smart device 1 refers to a portable device in which the camera 10 is installed. The portable smart device 1 can be any type of portable smart device 1 that can download and execute applications, for example, a smart phone, a tablet PC, And the like. However, the present invention is not limited thereto and may include other devices as long as it is a portable device having a communication function and a camera 10 function.

When the tagging application 100 is executed in the portable smart device 1, identification information corresponding to the identification information of the plant or the plant attached to the periphery of the plant, for example, RFID tag, QR code, Identifies the identification information, obtains the image of the plant, tags the identification information of the plant in the image information of the plant, and transmits the tag information to the analysis server 2.

The analysis server 2 is a server for storing and analyzing information on the growth data of plant individuals. In addition to the individual plant growth data DB obtained through the image chamber of the mass analysis platform system by automatic transfer of plants, The image data of each individual plant transmitted through the tagging application 100 is further stored and used for the phenotype analysis.

 As described above, while the image chamber acquiring the plant imaging obtains the image of the whole plant, the tagging application 100 according to the present invention can be used not only for the whole image but also for the user or the researcher, Which can be obtained by separately acquiring the specific region of the mass analysis platform system.

FIG. 2 is a control block diagram of a portable smart device 1 in which a tagging application 100 according to an embodiment of the present invention is stored and executed. 2, the portable smart device 1 according to an exemplary embodiment of the present invention includes a camera 10, a memory unit 20, an application control unit 30, a display unit 40, and a communication unit 50 .

The camera 10 is for capturing an image of a plant, and in some cases, can be utilized as an image pickup means for image recognition such as identification information of a plant, for example, a bar code system or a QR code.

The memory unit 20 stores a tagging application 100 for tagging plant identification information on a plant image and may store various applications necessary for operation and operation of the portable smart device 1. [

The application control unit 30 is a module for controlling operations related to application management and application execution, and may be implemented by a microprocessor, a microcontroller, a microchip, or the like in which a series of execution codes and execution codes operate.

The display unit 40 is a module for displaying the user interface screen 41 according to the execution of the tagging application 100 and can be applied to various display panels such as LCD, LED, OLED, AMOLED, and IPS.

The communication unit 50 is capable of communicating with the analysis server 2 using modules such as 3G communication, WIFI, Bluetooth, NFC (Near Field Communication) and RFID, and uses an NFC (RFID tag) The NFC (RFID tag) of the communication unit 50 can be utilized as an identification means.

3 is a schematic diagram of a tagging application 100 in accordance with an embodiment of the present invention. 3, the tagging application 100 according to an exemplary embodiment of the present invention includes an identification information recognition unit 110, an image acquisition unit 120, a tagging unit 130, and a transmission unit 140 . The tagging application 100 includes a series of software program codes that operate on a processor or the like.

The identification information recognizing unit 110 is a module for recognizing plant identification information and may include at least one or more modules for recognizing and reading NFC, RFID, bar code, QR code and the like.

The image obtaining unit 120 is a module for activating the camera 10 to obtain an image of a desired plant, which will be described later with reference to FIG.

The tagging unit 130 is a module for tagging the identification information of the plant to the image information of the plant. The identification information of the plant is included in the image information of the plant, so that in the analysis server 2, Based on the information, the phenotype analysis and analysis results can be DB.

The transmitting unit 140 is for transmitting the image information of the plant tagged with the identification information of the plant to the analysis server 2. The transmitting unit 140 analyzes the image information of the plant through the communication unit 50 And transmitted to the server 2.

4 is a schematic diagram of an image acquisition unit 120 according to an embodiment of the present invention. 4, an image obtaining unit 120 according to an exemplary embodiment of the present invention includes a scale setting unit 121, a scale adjusting unit 122, an information storing unit 123, and a region of interest setting unit 124 .

The scale setting unit 121 is capable of selecting or adjusting a scale relating to the size of a plant, and means a menu that allows selection of a reduction or enlargement ratio of a screen.

The scale adjusting unit 122 enlarges or reduces the screen of the plant by adjusting the focal distance of the camera 10 at a scale corresponding to a user's input or selection.

The information storage unit 123 stores the scale information of the plant and the screen in the image information of the plant. The information storage unit 123 may include a scale screen when the image is acquired, or may be attached to the image as separate data.

The region-of-interest setting unit 124 can input or select a part of a stem, a leaf, or the like of a plant as a region of interest, and can be set by clicking on a screen or drawing an area of the user.

In addition, the information storage unit 123 stores the information about the interest area of the plant in the image information of the plant when the image of the plant is acquired, and stores the information of interest in the analysis server 2 in the analysis server 2 So that you can find it. At this time, the information about the ROI may be added in the form of a screen in which the ROI is displayed directly on the image, or may be added to the ROI regarding the ROI.

5 is an example of a region-of-interest setting screen according to an embodiment of the present invention. Referring to FIG. 5, a user can set a region in which a specific feature of a leaf part can be seen, such as an operation in which a user draws a circle in a corresponding area on a display screen. Information about an area of interest is included in image information, .

Referring again to FIG. 3, the tagging application 100 according to an exemplary embodiment of the present invention may further include a user input unit 150.

The user input unit 150 allows the user to input specific information related to the plant in which the image is acquired by text or the like. A text input window may be separately provided at the time of image acquisition, or may be input directly to the image of the plant using a touch pen You may.

For example, if the user wants to further comment on the state of the unknown plant on the image, the user inputs the comment in the input window or the image and includes it in the image information, .

FIG. 6 is a schematic view schematically showing the internal configuration of the analysis server 2 in the plant growth information system of FIG. 1; Referring to FIG. 6, the analysis server 2 includes a plant database 210 and a growth information calculation unit 220.

The plant database part 210 is constructed of a database of the growth information of the plant. The plant database part 210 is information on the growth depending on the type of plant, and includes morphology, color (foreground / Background), geometry, texture, and the like are stored in a database. The plant database is structured in various ways according to the types of plants and the growth periods, and can also be constructed by identification information of plants.

The growth information calculating unit 220 includes a machine learning model unit 221 constructed by analyzing a plant image to calculate growth characteristics information of the plant and constructed by machine learning.

The machine learning model unit 221 is an image analysis algorithm constructed through machine learning of a plant growth information DB. The machine learning model unit 221 stores information on the size, color, and area of leaves, branches, stems, .

The machine learning model unit 221 analyzes the image of the plant transmitted from the portable smart device and extracts the plant area by separating the foreground and the background area. Then, leaves, branches, stems, and fruit regions of plants are extracted from the plant area.

Then, size, area, and color information are extracted by matching the leaf, branch, stem, and fruit area of the extracted plant with the reference model calculated through machine learning through geometric transformation.

For example, by analyzing the shape, shape, color, and texture of the leaves extracted from the plant area, it is possible to find a model having the most similar shape and to calculate the size and color thereof.

In addition, if the plant image information includes the leaf information of the leaf or the leaf information can be analyzed from the plant image, the matching range may be reduced according to the leaf information.

Further, in the present invention, since the plant identification information is tagged in the plant image information, the plant growth information and the plant characteristic information corresponding to the identification information are extracted from the plant database unit 210 and photographed by the portable smart device The information such as the size, area, and color of a leaf, stem, branch, or fruit can be calculated.

For example, in the plant database part 210 of the present invention, information on the growth characteristics (leaf, stem, branch, or fruit size, angle, color, texture, etc.) of each plant is stored Therefore, it is possible to accurately analyze the size, color, and area of each composition of a plant photographed with a portable smart device by performing comparison with the most recently analyzed information on the growth characteristics of the corresponding plant.

A support vector machine (SVM) or a least squares support vector machine (LS-SVM) may be applied to the machine learning model applied to the present invention.

FIG. 7 is a schematic diagram of a plant information confirmation application 100 'according to an embodiment of the present invention. The plant information confirmation application 100 'is installed in the portable smart device 1 and is operated by requesting the plant entity information from the analysis server 2 and remotely verifying the plant information through the portable smart device 1.

Conventionally, if a researcher wonders about object information or phenotypic analysis information of a particular plant among the plants cultivated by the researcher, the identification information is recorded, and then, the analysis server 2 goes to the analysis server 2 and inputs individual identification information of the plant, However, according to the present invention, when the plant is wondering while observing the plant, only the identification information of the plant is tagged and transmitted using the portable smart device 1, so that it is very convenient to confirm the individual information of the plant on the spot.

Referring to FIG. 7, the plant information confirmation application 100 'according to an embodiment of the present invention includes an identification information recognition unit 110, an information request unit 170, and an information display unit 180.

The identification information recognizing unit 160 has the same configuration as the identification information recognizing unit 110 of the above-described tagging application 100, and a description thereof will be omitted.

The information requesting unit 170 sends identification information of the plant recognized by the identification information recognizing unit 160 to the analysis server 2 to request individual information of the plant, And displays plant information of the plant transferred from the plant on a screen by item.

Here, the individual information of the plant displayed by the information display unit 180 may include genetic information of the plant, 2D or 3D image information of the plant, information on the cultivation environment of the plant, information on the growth of the plant, and / have.

8 to 12 show an example of an itemized screen for each item of the plant information confirmation application 100 '. 8, there are icons of home screen, OI, IMG, GC, EI items.

The home screen is a screen for identifying plant information, OI is individual information of the plant, IMG is the image information of the plant, GC is the growth environment information of the plant, and EI is the phenotype information of the plant.

The home screen of FIG. 8 is a screen displayed after recognizing the RFID tag, QR code, bar code, etc. of the plant through the communication module or the camera 10. When the 'Tag Reading' button is clicked in FIG. 8, the identification information of the corresponding plant is transmitted to the analysis server 2 to request individual information of the corresponding plant.

 FIG. 9 is a screen for displaying the OI icon, that is, the plant information of the plant, transmitted from the analysis server 2. When the user clicks on the OI, the plant information of the plant is displayed on the screen.

FIG. 10 is a screen on which an IMG icon, that is, image information of a plant, is displayed. A 2D image or a 3D image of a plant is displayed on the screen.

FIG. 11 is a screen for displaying the GC icon, that is, information on the growth environment of the plant. Information about the current growth environment of the plant is displayed, and the researcher can immediately check whether the temperature or humidity is appropriate.

FIG. 12 is a screen displaying the EI icon, that is, the phenotype information of the plant. The number of the leaves, the number of differentiations, the number of fruits, the specificity, etc. of the plant can be confirmed. In some cases, The user may directly enter the phenotype information while watching the plant. The input information may be stored together with the plant identification information, the input time, and the like, transmitted to the analysis server 2, and stored in the DB.

In the above-described embodiment, the plant information confirmation application 100 'is implemented as an application separate from the tagging application 100, but the function may be integrated with the tagging application 100.

The tagging application 100 and the plant information confirmation application 100 'are the same in that they identify the plant identification information at the time of initial operation. If the two applications are integrated with the analysis server 2, . ≪ / RTI >

13 is a flowchart of a method of tagging plant identification information using the tagging application 100 according to an embodiment of the present invention.

Referring to FIG. 13, a method for tagging plant entity information according to an embodiment of the present invention downloads tagging application 100 to portable smart device 1 (S10). When the tagging application 100 is executed (S11), a module for recognizing plant identification information is activated. For example, if the identification information of the plant is the RFID tag, the identification information of the plant is confirmed through the RFID reading module. If the identification information of the plant is the NFC module, the identification information of the plant is recognized through the NFC communication (S12). As another example, if the plant identification information is written in the QR code or the barcode format, the camera 10 is activated to acquire the QR code or the bar code, and then the identification information of the plant is confirmed (S12).

After confirming the identification information of the plant, a plant image is obtained (S13). After obtaining the image of the plant, the identification information of the plant is tagged to the image information of the plant (S14), and the tagged image information is transmitted to the analysis server 2 (S15).

Here, the image of the plant may be obtained once or several times. This may vary depending on the needs of the user, but a procedure may be required to confirm whether the plant image acquisition has been completed in the process.

If the user clicks on the icon indicating that the image acquisition is complete, the user can click on the icon to tag the plant identification information to the acquired images after the recognition of the plant identification information. Another example is that once the user acquires all the images of the desired plant, the identification information of the plant is recognized once again to confirm that the image acquisition process of the plant has been completed. In this case, the tagging application 100 recognizes that the image acquisition of the corresponding plant is completed, and tags and transmits the plant identification information to the images when the procedure of recognizing plant identification information, image acquisition, and plant identification information is performed.

On the other hand, the process of acquiring an image of a plant is as follows. After acquiring the identification information of the plant, the camera 10 is activated to acquire an image of the plant. If the user adjusts the size of the plant or the screen scale displayed on the screen, the camera 10 focuses on the adjusted scale to enlarge or reduce the screen. If the user sets a certain area of the screen as a region of interest, the region of interest information is stored. The stored ROI information is included in the image information and transmitted to the analysis server 2.

FIG. 15 is a flowchart for explaining a process of analyzing a plant image in the analysis server 2. The analysis server 2 receives the plant image telegram from the portable smart device (S20). Identify the plant using the identification information in the received information (S21).

Then, the image of the plant is analyzed using the model constructed through the machine learning. The foreground and the background are separated from the image of the plant, and the plant areas such as leaf, stem, fruit, and branch are extracted from the foreground S23).

The size, area, and color information are calculated by geometric transformation of the extracted plant areas such as leaf, stem, fruit, and branches, and matching with the model constructed through the machine learning model (S25).

At this time, as described above, the matching range may be narrowed by using the information included in the plant image without performing matching in the entire data, or the growing information of the plant or the plant analysis information May be used to analyze the image.

As described above, according to the present invention, the tagging application 100 is installed in the portable smart device 1, the identification information is tagged and transmitted to the analysis server 2 to acquire the accurate phenotype information of the plant There is an advantage to be able to do. Also, by analyzing the image based on the model constructed through the machine learning in the analysis server 2, it is possible to accurately analyze the size, color area and the like of the leaves, stems, branches and fruits of the plants.

Although the growth information calculating unit 220 is described in the above embodiment as being provided in the analysis server 2, according to another embodiment of the present invention, the growth information calculating unit 220 may be included in the tagging application 100 . The tagging application can be continuously updated with the machine learning model unit 221 that calculates the growth information of the plant in conjunction with the analysis server 2, and both image acquisition and analysis can be performed in the tagging application.

Here, the machine learning model may be a model in which the growth data of the plants constructed by DB are machine-learned, depending on the kinds of plants. However, in the analysis server 2 of the present invention, The size and color information of leaves, stems, fruits, branches, and the like are already established, so that a machine learning model adapted only to plants corresponding to the identification information can be applied.

While the present invention has been described in connection with what is presently considered to be the most practical and preferred embodiment, it is to be understood that the invention is not limited to the disclosed embodiments. That is, within the scope of the present invention, all of the components may be selectively coupled to one or more of them. In addition, although all of the components may be implemented as one independent hardware, some or all of the components may be selectively combined to perform a part or all of the functions in one or a plurality of hardware. As shown in FIG. The codes and code segments constituting the computer program may be easily deduced by those skilled in the art. Such a computer program can be stored in a computer-readable storage medium, readable and executed by a computer, thereby realizing an embodiment of the present invention. As the storage medium of the computer program, a magnetic recording medium, an optical recording medium, a carrier wave medium, or the like may be included.

Furthermore, the terms "comprises", "comprising", or "having" described above mean that a component can be implanted unless otherwise specifically stated, But should be construed as including other elements. All terms, including technical and scientific terms, have the same meaning as commonly understood by one of ordinary skill in the art to which this invention belongs, unless otherwise defined. Commonly used terms, such as predefined terms, should be interpreted to be consistent with the contextual meanings of the related art, and are not to be construed as ideal or overly formal, unless expressly defined to the contrary.

The foregoing description is merely illustrative of the technical idea of the present invention, and various changes and modifications may be made by those skilled in the art without departing from the essential characteristics of the present invention. Therefore, the embodiments disclosed in the present invention are intended to illustrate rather than limit the scope of the present invention, and the scope of the technical idea of the present invention is not limited by these embodiments. The scope of protection of the present invention should be construed according to the following claims, and all technical ideas within the scope of equivalents should be construed as falling within the scope of the present invention.

1: Portable Smart Device 2: Analysis Server
10: camera 20: memory unit
30: Application control section 40:
41: user interface screen 50:
100: tagging application 110: identification information recognition unit
120: Image acquiring unit 121: Scale setting unit
122: scale adjustment unit 123: information storage unit
124: ROI setting unit 125:
140: Transmission unit 150: User input unit
210: Plant Database Division 211: Leaf DB
213: Branch DB 215: Stem DB
217: Fruit DB 220: Growth information calculating section
221: Machine learning model part

Claims (13)

A camera for acquiring an image;
A memory unit storing a tagging application for tagging plant identification information on a plant image;
An application control unit for executing the tagging application;
A display unit for displaying a user interface screen according to execution of the tagging application; And
And a communication unit for communication with the outside;
The tagging application includes an identification information recognizing unit for recognizing the identification information of the plant, an image acquiring unit for acquiring an image of the plant by activating the camera, a tagging unit for tagging the identification information of the plant to image information of the plant, And a transmitting unit for transmitting image information of the plant tagged with the identification information to an analysis server.
The method according to claim 1,
Wherein the image obtaining unit comprises: a region of interest setting unit that can input or select a region of interest of the plant; And
Further comprising an information storage unit for storing information about a region of interest of the plant in the image information of the plant upon image acquisition of the plant.
The method according to claim 1,
Wherein the identification information recognizing unit includes at least one of RFID, QR code, and bar code recognition unit.
The method according to claim 1,
Wherein the tagging application further comprises a user input unit for receiving a specific item of the plant from the user.
5. The method according to any one of claims 1 to 4,
The tagging application includes an information requesting unit for transmitting identification information of the plant to the analysis server and requesting individual information about the plant, and an information display unit for displaying item information on the plant sent from the analysis server Further included,
Wherein the individual information on the plant includes at least one of genetic information of the plant, 2D or 3D image information of the plant, cultivation environment information of the plant, growth information of the plant, and phenotype information of the plant. Smart devices.
5. The method according to any one of claims 1 to 4,
The tagging application further includes a growth information calculation unit for calculating a growth characteristic information of the plant by analyzing the image of the plant acquired through the image acquisition unit using a machine learning model,
Wherein the information storage unit stores the calculated growth characteristics information of the plant in the image information of the plant.
The method according to claim 6,
Wherein the growth characteristics information of the plant includes the size, area, and color information of a leaf, a stem, a branch or a fruit of the plant.
A portable smart device that recognizes identification information of a plant using identification information recognition means, acquires an image of the plant, and transmits the image of the plant together with the identification information to an analysis server; And
And a growth information calculation unit for calculating the growth characteristics information of the plant by analyzing the image of the plant transmitted from the portable smart device using a machine learning model unit constructed through machine learning, Information analysis system.
9. The method of claim 8,
The growth information calculating unit extracts leaf, stem, fruit, or branch area from the image of the plant using the model constructed through machine learning, and performs matching with the reference model to determine the leaf, stem, And the size, area, and color information of the fruit are calculated.
A method for tagging and analyzing plant identification information using a tagging application,
Executing the tagging application on a smart device;
Recognizing the identification information of the plant using the identification information recognition means;
Obtaining an image of the plant using a camera of the smart device;
Tagging the identification information of the plant to the image information of the plant; And
And analyzing the image of the plant through a machine learning model to calculate the growth characteristics information of the plant.
11. The method of claim 10,
The step of calculating the growth characteristics information comprises:
Extracting leaf, stem, fruit, or branch regions from the plant image using a model constructed through machine learning; And
And calculating the size, area, and color information of leaves, stems, branches or fruits of the plant by performing matching with the reference model.
12. The method of claim 11,
The step of acquiring an image of the plant may include the steps of inputting or selecting a region of interest of the plant, and storing information about a region of interest of the plant in the image information of the plant when the image of the plant is acquired The method comprising the steps of:
11. The method of claim 10,
Transmitting identification information of the plant to the analysis server to request individual information about the plant; And
Further comprising the step of displaying entity information on the plant transmitted from the analysis server by item;
Wherein the individual information on the plant includes at least one of genetic information of the plant, 2D or 3D image information of the plant, cultivation environment information of the plant, growth information of the plant, and phenotype information of the plant. How to tag and analyze identification information.

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