KR20230039473A - Apparatus and method for calculating size and weight of livestock - Google Patents

Abstract

Disclosed is an apparatus and a method for calculating the size and weight of livestock. The apparatus for calculating the size and weight of livestock, which comprises: a communication unit which acquires images and video information of the object from a first camera and a second camera disposed at a certain distance from the object on the top of the feeding trough or drinking fountain, respectively; and a control unit which analyzes the image captured by the first camera to determine an object, determines a shooting point of the second camera based on the analysis result, obtains image information from the second camera and calculates the size and weight of the object based on the acquired image information. Accordingly, the present invention can minimize stress on livestock.

Description

Apparatus and method for calculating the size and weight of livestock {APPARATUS AND METHOD FOR CALCULATING SIZE AND WEIGHT OF LIVESTOCK}

Embodiments disclosed herein relate to an apparatus and method for calculating the size and weight of livestock, and more particularly, by photographing an object using a camera located at the top of a feeding trough or drinking fountain in a barn to obtain an image. Apparatus for calculating the size and weight of livestock, obtaining image information by operating another camera based on the result of analyzing the obtained image, and calculating the size and weight of livestock from the obtained image information. and methods.

In the case of livestock farming that raises large livestock such as pigs and cows, it is necessary to obtain a good grade by bringing the size and weight of livestock to an appropriate level at the time of shipment.

Accordingly, conventionally, in measuring the size and weight of livestock to determine the time of shipment, the size and weight of livestock were measured by inducing the livestock to a specific cage in a barn equipped with a means for measuring the size and weight of livestock. .

However, as described above, in order to measure the size and weight of livestock, there is a problem in that the livestock must be driven into a specific cage, and manpower and time are consumed accordingly. In addition, even if the livestock moves to a specific cage, when the livestock is in an excited state, accurate measurement is not performed according to the movement, and quality is deteriorated due to the occurrence of stress.

Korean Patent Registration No. 10-2131558 (Announced on July 7, 2020)

Embodiments disclosed herein acquire an image by photographing an object using one camera located at the top of a feed container or drinking fountain in a barn, and operate another camera based on a result of analyzing the obtained image. It is an object of the present invention to provide a device and method for calculating the size and weight of livestock by obtaining image information and calculating the size and weight of livestock from the obtained image information.

Other objects and advantages of the present invention may be understood from the following description, and will be more clearly understood by an embodiment. It will also be readily apparent that the objects and advantages of the present invention may be realized by means of the instrumentalities and combinations thereof set forth in the claims.

As a technical means for achieving the above-described technical problem, the device for calculating the size and weight of livestock is a first camera and a second camera disposed at a predetermined distance from the object at the top of the feeder or drinking fountain, respectively, from the object A communication unit for acquiring image and video information taken by the camera; and determining an object by analyzing an image captured by the first camera, determining a capturing time point of the second camera based on the analyzed result, and obtaining image information from the second camera. and a controller for calculating the size and weight of the object based on the image information.

According to another embodiment, a method for calculating the size and weight of livestock in an apparatus for calculating the size and weight of livestock using a first camera and a second camera disposed in a barn may include photographing by the first camera. Analyzing the image to determine the object; determining a photographing time point of the second camera based on the analyzed result; and calculating the size and weight of the object based on the obtained image information when image information is obtained from the second camera.

According to another embodiment, the recording medium is a computer readable recording medium on which a program for performing a method of calculating the size and weight of livestock is recorded.

According to another embodiment, the computer program is a computer program stored in a recording medium to be executed by a device for calculating the size and weight of livestock and to perform a method for calculating the size and weight of livestock.

According to any one of the above-described problem solving means, an image is acquired by photographing an object using a camera located at an upper portion of a feeder or drinking fountain in a barn, and another camera is acquired based on a result of analyzing the obtained image. is operated to obtain image information, and the size and weight of livestock are calculated from the acquired image information, so that the size and weight of livestock can be calculated in a state in which movement of livestock is minimized, thereby minimizing stress on livestock and It has the effect of accurately calculating the size and weight. Accordingly, it is possible to more accurately predict the time of shipment of livestock. In addition, as human intervention is reduced, transmission of human-caused infectious diseases can be prevented.

Effects obtainable from the disclosed embodiments are not limited to those mentioned above, and other effects not mentioned are clear to those skilled in the art from the description below to which the disclosed embodiments belong. will be understandable.

Hereinafter, the accompanying drawings illustrate preferred embodiments disclosed in this specification, and serve to further understand the technical idea disclosed in this specification together with specific details for carrying out the invention. The contents should not be construed as limited only to the matters described in such drawings.
1 is an example of a barn in which a device for calculating the size and weight of livestock according to an embodiment is implemented.
Figure 2 is a functional block diagram of a device for calculating the size and weight of livestock according to an embodiment.
3 is a diagram illustrating an example of capturing an object by a camera according to an exemplary embodiment.
4 is a flowchart according to an example of a method for calculating the size and weight of livestock according to an embodiment.
FIG. 5 is a flowchart for a more detailed explanation in step S420 of FIG. 4 .

Hereinafter, various embodiments will be described in detail with reference to the accompanying drawings. Embodiments described below may be modified and implemented in various different forms. In order to more clearly describe the characteristics of the embodiments, detailed descriptions of matters widely known to those skilled in the art to which the following embodiments belong are omitted. And, in the drawings, parts irrelevant to the description of the embodiments are omitted, and similar reference numerals are attached to similar parts throughout the specification.

Throughout the specification, when a component is said to be “connected” to another component, this includes not only the case of being “directly connected” but also the case of being “connected with another component intervening therebetween”. In addition, when a certain component "includes" a certain component, this means that other components may be further included without excluding other components unless otherwise specified.

Hereinafter, embodiments will be described in detail with reference to the accompanying drawings.

1 is an example of a barn in which a device for calculating the size and weight of livestock according to an embodiment is implemented.

Referring to FIG. 1 , a plurality of cameras c1 and c2 for photographing an object a may be installed above the feed trough or drinking fountain b in the barn. At this time, it is preferable that the above-described plurality of cameras c1 and c2 are disposed at a predetermined distance from the object in order to secure a sufficient shooting range for photographing the object. Meanwhile, according to an embodiment, the plurality of cameras c1 and c2 described above may include an RGB camera for photographing an object entering the barn and a depth camera for acquiring image information by photographing the object. there is. At this time, for convenience of description, the RGB camera will be referred to as a first camera c1 and the depth camera will be referred to as a second camera c2.

According to one embodiment, the device for calculating the size and weight of livestock is acquired by acquiring an image of the object (a) from a first camera (c1) disposed above the feeder or drinking fountain (b). An object is determined by analyzing the image, and if the result of the analysis of the object is determined to be a livestock, a trigger signal for operating the second camera c2 is generated. That is, if the analysis result of determining the object (a) is determined to be a livestock, this time may be determined as a photographing time of the second camera (c2) and a trigger signal for operating the second camera (c2) may be generated. Accordingly, the second camera c2 may photograph the livestock, generate image information, and transmit the image information to a device for calculating the size and weight of the livestock. In this case, the above-described image information may include depth information including a circumferential length for each body part of the livestock. Accordingly, the apparatus for calculating the size and weight of livestock according to an embodiment obtains image information from the second camera c2, detects depth information from the acquired image information, and determines the size and weight of an object from the detected depth information. Size and weight can be calculated. On the other hand, in describing an embodiment, the first camera (c1) and the second camera (c2) is described as a separate configuration, but is not limited thereto, and may be configured and disposed as an integrated type.

Hereinafter, referring to FIGS. 2 and 3, an apparatus for calculating the size and weight of livestock according to an embodiment will be described in more detail.

2 is a functional block diagram of a device for calculating the size and weight of livestock according to an embodiment, and FIG. 3 is a diagram showing an example of an object being photographed by a camera according to an embodiment.

The device 100 for calculating the size and weight of livestock according to the present embodiment may be implemented as an electronic terminal with an application capable of interacting with a user installed, implemented as a server, or implemented as a server-client system, and may be implemented as a server-client system. When implemented as a client system, it may include an electronic terminal in which an application for an online service for interaction with a user is installed.

At this time, the electronic terminal may be implemented as a computer, portable terminal, television, wearable device, etc. capable of accessing a remote server through a network or connecting to other devices and servers. Here, the computer includes, for example, a laptop, desktop, or laptop equipped with a web browser, and the portable terminal is, for example, a wireless communication device that ensures portability and mobility. , PCS(Personal Communication System), PDC(Personal Digital Cellular), PHS(Personal Handyphone System), PDA(Personal Digital Assistant), GSM(Global System for Mobile communications), IMT(International Mobile Telecommunication)-2000, CDMA(Code Division Multiple Access)-2000, W-CDMA (W-Code Division Multiple Access), Wibro (Wireless Broadband Internet), Smart Phone, Mobile WiMAX (Mobile Worldwide Interoperability for Microwave Access), etc. (Handheld)-based wireless communication device may be included. In addition, television may include IPTV (Internet Protocol Television), Internet TV (Internet Television), terrestrial TV, cable TV, and the like. Furthermore, a wearable device is a type of information processing device that can be worn directly on the human body, such as, for example, a watch, glasses, accessories, clothes, shoes, etc. can be connected with

In addition, the server may be implemented as a computer capable of communicating over a network with an application for interaction with a user of the device 100 for calculating the size and weight of livestock or an electronic terminal having a web browser installed, or may be implemented as a cloud computing server. . In addition, the server may include a storage device capable of storing data or may store data through a third server.

As described above, the device 100 for calculating the size and weight of livestock may be implemented in any one form of an electronic terminal, a server, or a server-client system, and when implemented as a server, the size and weight of livestock Components constituting the device 100 for calculating may be performed in a plurality of physically separated servers or in one server.

Referring to FIG. 2 , the apparatus 100 for calculating the size and weight of livestock according to the present embodiment includes an input/output unit 110, a communication unit 120, a storage unit 130, and a control unit 140.

The input/output unit 110 may include an input unit for receiving an input from a user and an output unit for displaying information such as a state of the device 100 for calculating work results or the size and weight of livestock. For example, the input/output unit 110 may include a plurality of cameras, an operation panel for receiving a user input, and a display panel for displaying a screen. At this time, according to an embodiment, the plurality of cameras described above may include a first camera and a second camera, the first camera may be an RGB camera, and the second camera may be a depth camera. Meanwhile, the depth camera may be a LiDAR camera. Meanwhile, in describing an embodiment, the second camera is named a depth camera, but the second camera may be a photographing device capable of measuring depth. The image information measured by the second camera can be visualized in various forms and can be used for vision AI-based learning and detection. The second camera may obtain image information capable of depth-related visualization, and technologies such as 3D scan, laser, sonar, and depth measurement may be applied.

Specifically, the input unit may include devices capable of receiving various types of inputs, such as a keyboard, a physical button, a touch screen, a camera, or a microphone. Also, the output unit may include a display panel or a speaker. However, the input/output unit 110 is not limited thereto and may include a configuration supporting various input/outputs.

According to the embodiment, the input unit may photograph the object to obtain an image for determining the object or may capture the object to obtain image information that is a basis for calculating the size and weight of the object. In this case, the above-described image information may include depth information including a circumferential length for each body part of the livestock. In addition, when the size and weight of the object are calculated, the output unit may output the calculated information and, at the same time, output a notification message notifying it when the shipping time based on the weight arrives.

The communication unit 120 may perform wired/wireless communication with other devices (devices) and/or networks. To this end, the communication unit 120 may include a communication module supporting at least one of various wired/wireless communication methods. For example, the communication module may be implemented in the form of a chipset.

Meanwhile, wireless communication supported by the communication unit 120 includes, for example, Wi-Fi (Wireless Fidelity), Wi-Fi Direct, Bluetooth, Bluetooth Low Energy (BLE), and Ultra Wide Band (UWB). , Near Field Communication (NFC), LTE, LTE-Advanced, and the like. In addition, wired communication supported by the communication unit 120 may be, for example, USB or High Definition Multimedia Interface (HDMI). According to an embodiment, the communication unit 120 may acquire images of the above-described object and video information from a first camera and a second camera disposed at a predetermined distance from the object above the feed container or drinking fountain. .

The storage unit 130 may install and store various types of data such as files, applications, and programs, and may be configured to include at least one of various types of memories such as RAM, HDD, and SSD. The control unit 140, which will be described later, may access and use data stored in the storage unit 130 or store new data in the storage unit 130. Also, the controller 140 may execute a program installed in the storage unit 130 . Meanwhile, a program for performing an operation of calculating the size and weight of livestock according to an embodiment may be installed in the storage unit 130 . On the other hand, according to the embodiment, the storage unit 130 may store standard data generated using livestock data collected in advance. At this time, the standard data may be data standardized by livestock type and number of months by measuring and analyzing livestock in livestock farms, and the standard data includes the circumference length, size and Weight information may be included. In addition, the storage unit 130 may store livestock images of various shapes including feature points capable of distinguishing the types of livestock.

The controller 140 has a configuration including at least one processor such as a CPU or an Arduino, and may control the overall operation of the device 100 for calculating the size and weight of livestock. That is, the controller 140 may control other components included in the apparatus 100 for calculating the size and weight of livestock to perform an operation for calculating the size and weight of livestock. Also, the controller 140 may execute a program stored in the storage unit 130, read a file stored in the storage unit 130, or store a new file in the storage unit 130.

The controller 140 determines the object by analyzing the image captured by the first camera. In this case, according to an embodiment, the first camera may be an RGB camera. An RGB camera can recognize an object by emitting infrared rays in pixel units to an object and accepting the reflected light. Meanwhile, the controller 140 may use an algorithm for determining a preset object in analyzing the photographed image. That is, the controller 140 may detect the shape of the object based on an algorithm for determining a preset object from an image captured by the first camera. In this case, the algorithm for discriminating the object may include shape-based instance segmentation, keypoint detection, and the like. The shape-based instance segmentation algorithm identifies an object based on its shape, and determines the degree to which the shape of the object in an image photographed by a camera matches a pre-stored shape to determine the shape of the object. In addition, the keypoint detection algorithm determines an object based on a specific key point, and the object may be determined by checking whether an object in an image captured by a camera includes a specific key point. In this case, the specific key points may include a tail, a hip, a waist, a shoulder, a horn, and the like. Meanwhile, a specific key point may include various elements that can characterize livestock in addition to the above elements. For example, as shown in (a) of FIG. 3 , the controller 140 cannot determine the object when the object in the image captured by the first camera does not include a specific key point, for example, a tail. As shown in (b) of FIG. 3 , when objects in the image captured by the first camera include all specific key points, the object may be determined. In addition, as shown in (a) of FIG. 3, the controller 140 cannot determine the object when only a part of the object is captured by the first camera, and as shown in (b) of FIG. 3, the controller 140 cannot determine the object. An object may be determined only when the shape is photographed. In this case, when the object is determined as a livestock, the controller 140 may generate a trigger signal for operating the second camera as will be described later. Meanwhile, the controller 140 may determine whether the object is a livestock by comparing livestock images of various shapes stored in the storage unit with images captured by the first camera. In addition, the type of livestock can be classified according to the characteristic points. In this case, the feature point may be specific information capable of distinguishing the type of livestock, such as the presence or absence of horns and the shape of a tail.

The controller 140 determines a capturing point of the second camera based on the image analysis result. In other words, as a result of analyzing the image of the object captured by the first camera, the controller 140 may generate a trigger signal when it is determined that the object is a livestock. In this case, the trigger signal may be a signal for operating the second camera. That is, as a result of analyzing the image captured by the first camera, the controller 140 determines that the shape of the object is a livestock, and if the movement of the object does not occur for a preset time, a trigger signal is generated to detect the second camera. can make it work. Meanwhile, according to an embodiment, the second camera may be a LiDAR (Light Detection And Ranging) camera. A lidar camera can accurately detect not only the distance to an object, but also its location and shape using a laser. That is, the lidar camera may measure the circumferential length of each body part of the livestock using a laser and may collect information on the length of the livestock. In this case, the second camera may acquire image information for calculating the size and weight of the livestock by capturing the object detected as the livestock. Meanwhile, the image information may include depth information including a circumferential length for each body part of the livestock.

The controller 140 detects depth information of livestock from the image information obtained from the second camera and calculates the size and weight of livestock from the detected depth information based on a preset algorithm for calculating the size and weight of livestock. can In this case, an algorithm for calculating the size and weight of livestock may calculate the size and weight of livestock by comparing standard data with depth information included in image information acquired from the second camera. For example, if the type of object photographed by the first camera is determined to be a cow, and among the depth information included in the image information obtained from the second camera, the chest circumference information of the cow is 100 inches, the controller 140 In the standard data stored in the storage unit 130, information corresponding to the type of livestock and the chest circumference of 100 inches, for example, information on the number of months, weight information, size information, etc. of livestock can be calculated. there is. In addition, the algorithm for calculating the size and weight of livestock divides the volume of an object determined to be livestock at fine intervals, calculates the total sum by summing the volumes of the divided sections, and then converts the volume to calculate the weight. may be

On the other hand, the control unit 140 may calculate the weight of the livestock more accurately using a regression analysis algorithm based on the chest circumference information and the length information of the livestock. At this time, the image information captured by the second camera may be processed and expressed in the form of a point cloud, and the control unit 140 may calculate the weight of the livestock by extracting valid data from the above image information. On the other hand, a point cloud may be 3D image information generated in the form of points from location coordinate values that are reflected and returned when the second camera radiates a laser beam to an object. For example, the controller 140 may calculate the weight of the livestock by reflecting a preset constant for weight calculation to the chest circumference and length of the livestock. Meanwhile, since the method of calculating the weight of livestock using a regression analysis algorithm based on the above-described livestock chest circumference information and length information is a well-known technique, a detailed description thereof will be omitted.

As described above, in calculating the size and weight of livestock, since a plurality of cameras are used at the top of the feeding trough or drinking fountain in the barn, manpower and time consumption can be minimized. In addition, as human intervention is reduced, the occurrence of human-caused infectious diseases can be prevented in advance. In addition, livestock such as cows and pigs minimize their movement when drinking water or feeding. At this time, more accurate size and weight can be calculated by acquiring image information for calculating size and weight. In addition, it is possible to minimize the stress on the livestock by performing an operation to calculate the size and weight when the livestock drinks or feeds itself, and automatically adjusts the feeding amount or drinking water amount according to the calculated weight. The quality of livestock can be further improved.

Meanwhile, various services may be provided by utilizing a device for calculating the size and weight of livestock according to an embodiment. For example, based on the measured circumference length of each body part of the livestock, it is possible to manage the individual by adjusting the amount of feeding or drinking water for each individual, and when a camera capable of providing a thermal image is separately installed, It is possible to observe whether there is an outbreak of an infectious disease. In addition, as the environment in the barn can be monitored using a camera, it is possible to provide an automated service for improving the barn environment by checking and improving the contamination level in the barn.

4 is a flowchart according to an example of a method for calculating the size and weight of livestock according to an embodiment, and FIG. 5 is a flowchart for a more detailed explanation in step S420 of FIG. 4 .

The method for calculating the size and weight of livestock according to the embodiment shown in FIGS. 4 to 5 is processed time-sequentially in the apparatus 100 for calculating the size and weight of livestock shown in FIGS. 1 to 3 contains the steps Therefore, even if the content is omitted below, the information described above with respect to the device 100 for calculating the size and weight of livestock shown in FIGS. 1 to 3 is the embodiment shown in FIGS. 4 to 5 It can also be applied to a method for calculating the size and weight of livestock according to the method.

As shown in FIG. 4, the method for calculating the size and weight of livestock according to the present embodiment includes analyzing an image captured by a first camera (S410), determining a capturing time point of a second camera Step S420 and step S430 of calculating the size and weight of the object based on the image information obtained from the second camera.

In step S410, the apparatus 100 for calculating the size and weight of livestock analyzes the image taken by the first camera to determine the object. In this case, the first camera according to an embodiment may be an RGB camera. The apparatus 100 for calculating the size and weight of livestock may utilize an algorithm for determining a preset object in analyzing a photographed image. That is, the apparatus 100 for calculating the size and weight of livestock may detect the shape of an object based on an algorithm for determining a preset object from an image captured by the first camera. In this case, the algorithm for discriminating the object may include shape-based instance segmentation, keypoint detection, and the like.

In step S420, the apparatus 100 for calculating the size and weight of livestock determines a photographing time point of the second camera based on the analyzed result in step S410. More specifically, the apparatus 100 for calculating the size and weight of livestock analyzes the image of the object captured by the first camera in step S410, and as shown in FIG. 5, the analyzed result is displayed in the image. If it is determined that the object is a livestock, a trigger signal for operating the second camera may be generated (S510) (S520). Accordingly, the second camera that receives the trigger signal may operate to photograph the object and generate image information. At this time, the generated image information may be acquired by the apparatus 100 for calculating the size and weight of livestock and used as basic information for calculating the size and weight of livestock (S530). Meanwhile, according to an embodiment, the second camera may be a LiDAR (Light Detection And Ranging) camera, and the second camera detects not only the distance to the object but also the location and shape, and the circumferential length for each body part of the livestock. can measure

When the apparatus 100 for calculating the size and weight of livestock in step S430 acquires image information captured by the second camera in step S420, the size and weight of the object may be calculated based on the obtained image information. there is. The apparatus 100 for calculating the size and weight of livestock may utilize a preset algorithm for calculating the size and weight of livestock when calculating the size and weight of an individual. That is, the apparatus 100 for calculating the size and weight of livestock detects depth information of livestock from the image information obtained from the second camera, and based on a preset algorithm for calculating the size and weight of livestock, the detection The size and weight of livestock can be calculated from the obtained depth information. In this case, an algorithm for calculating the size and weight of livestock may calculate the size and weight of livestock by comparing standard data with depth information included in image information acquired from the second camera.

The term '~unit' used in the above embodiments means software or a hardware component such as a field programmable gate array (FPGA) or ASIC, and '~unit' performs certain roles. However, '~ part' is not limited to software or hardware. '~bu' may be configured to be in an addressable storage medium and may be configured to reproduce one or more processors. Therefore, as an example, '~unit' refers to components such as software components, object-oriented software components, class components, and task components, processes, functions, properties, and procedures. , subroutines, segments of program patent code, drivers, firmware, microcode, circuitry, data, databases, data structures, tables, arrays and variables.

Functions provided within components and '~units' may be combined into smaller numbers of components and '~units' or separated from additional components and '~units'.

In addition, components and '~units' may be implemented to play one or more CPUs in a device or a secure multimedia card.

On the other hand, the method for calculating the size and weight of livestock according to an embodiment described through this specification may be implemented in the form of a computer-readable medium storing instructions and data executable by a computer. In this case, instructions and data may be stored in the form of program codes, and when executed by a processor, a predetermined program module may be generated to perform a predetermined operation. Also, computer-readable media can be any available media that can be accessed by a computer and includes both volatile and nonvolatile media, removable and non-removable media. Also, a computer-readable medium may be a computer recording medium, which is a volatile and non-volatile memory implemented in any method or technology for storage of information such as computer-readable instructions, data structures, program modules, or other data. It can include both volatile, removable and non-removable media. For example, the computer recording medium may be a magnetic storage medium such as HDD and SSD, an optical recording medium such as CD, DVD, and Blu-ray disc, or a memory included in a server accessible through a network.

In addition, the method for calculating the size and weight of livestock according to one embodiment described through this specification may be implemented as a computer program (or computer program product) including instructions executable by a computer. A computer program includes programmable machine instructions processed by a processor and may be implemented in a high-level programming language, object-oriented programming language, assembly language, or machine language. . Also, the computer program may be recorded on a tangible computer-readable recording medium (eg, a memory, a hard disk, a magnetic/optical medium, or a solid-state drive (SSD)).

Therefore, the method for calculating the size and weight of livestock according to an embodiment described through this specification can be implemented by executing the computer program as described above by a computing device. A computing device may include at least some of a processor, a memory, a storage device, a high-speed interface connected to the memory and a high-speed expansion port, and a low-speed interface connected to a low-speed bus and a storage device. Each of these components are connected to each other using various buses and may be mounted on a common motherboard or mounted in any other suitable manner.

Here, the processor may process commands within the computing device, for example, to display graphic information for providing a GUI (Graphic User Interface) on an external input/output device, such as a display connected to a high-speed interface. Examples include instructions stored in memory or storage devices. As another example, multiple processors and/or multiple buses may be used along with multiple memories and memory types as appropriate. Also, the processor may be implemented as a chipset comprising chips including a plurality of independent analog and/or digital processors.

Memory also stores information within the computing device. In one example, the memory may consist of a volatile memory unit or a collection thereof. As another example, the memory may be composed of a non-volatile memory unit or a collection thereof. Memory may also be another form of computer readable medium, such as, for example, a magnetic or optical disk.

And, the storage device may provide a large amount of storage space to the computing device. A storage device may be a computer-readable medium or a component that includes such a medium, and may include, for example, devices in a storage area network (SAN) or other components, such as a floppy disk device, a hard disk device, an optical disk device, or a tape device, flash memory, or other semiconductor memory device or device array of the like.

The above-described embodiments are for illustrative purposes, and those skilled in the art to which the above-described embodiments belong can easily transform into other specific forms without changing the technical idea or essential features of the above-described embodiments. You will understand. Therefore, it should be understood that the embodiments described above are illustrative in all respects and not restrictive. For example, each component described as a single type may be implemented in a distributed manner, and similarly, components described as distributed may be implemented in a combined form.

The scope to be protected through this specification is indicated by the claims to be described later rather than the detailed description above, and all changes or modifications derived from the meaning and scope of the claims and equivalent concepts thereof are included in the scope of the present invention. should be interpreted as being

100: device for calculating the size and weight of livestock
110: input/output unit
120: communication department
130: storage unit
140: control unit

Claims (12)

a communication unit that obtains an image of the object and video information from a first camera and a second camera disposed at a predetermined distance from the object above the feed container or drinking fountain; and
When an object is determined by analyzing an image captured by the first camera, a capturing time point of the second camera is determined based on the analyzed result, and image information is obtained from the second camera, the obtained image Apparatus for calculating the size and weight of livestock, including; a control unit for calculating the size and weight of the object based on the information. According to claim 1,
The control unit,
An apparatus for calculating the size and weight of livestock, characterized in that for detecting the shape of the object from the image taken by the first camera based on a preset algorithm for discriminating the object. According to claim 2,
The control unit,
When it is determined that the type of the detected object is a livestock, a trigger signal is generated to operate the second camera, and image information for calculating the size and weight of the livestock is obtained from the second camera. Characterized in that A device for calculating the size and weight of livestock. According to claim 3,
The control unit,
Depth information including the circumferential length of each body part of the livestock is detected from the image information acquired from the second camera, and the size and weight of the livestock are calculated from the detected information based on a preset algorithm. Apparatus for calculating the size and weight of livestock, characterized in that for calculating the size and weight. According to claim 1,
The first camera is an RGB camera,
The apparatus for calculating the size and weight of livestock, characterized in that the second camera is a depth camera. A method for calculating the size and weight of livestock in a device for calculating the size and weight of livestock using a first camera and a second camera disposed in a barn,
determining an object by analyzing an image captured by the first camera;
determining a photographing time point of the second camera based on the analyzed result; and
When image information is obtained from the second camera, calculating the size and weight of the object based on the obtained image information; method for calculating the size and weight of livestock. According to claim 6,
The step of determining the object is,
Based on a preset algorithm for determining the object, detecting the shape of the object from the image taken by the first camera. According to claim 7,
The step of determining the shooting point of the second camera,
When it is determined that the type of the detected object is a livestock, generating a trigger signal to operate the second camera, and acquiring image information for calculating the size and weight of the livestock from the second camera Method for calculating the size and weight of livestock, characterized in that. According to claim 8,
Calculating the size and weight of the object,
Depth information including the circumferential length of each body part of the livestock is detected from the image information acquired from the second camera, and the size and weight of the livestock are calculated from the detected information based on a preset algorithm. A method for calculating the size and weight of livestock, comprising the step of calculating the size and weight. According to claim 6,
The first camera is an RGB camera,
The method of calculating the size and weight of livestock, characterized in that the second camera is a depth camera. A computer-readable recording medium in which a program for performing the method according to claim 6 is recorded. A computer program stored in a recording medium to perform the method according to claim 6 and performed by a device for calculating the size and weight of livestock.

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