WO2020045702A1

WO2020045702A1 - Computer program and terminal for providing urinalysis using colorimetry table

Info

Publication number: WO2020045702A1
Application number: PCT/KR2018/010030
Authority: WO
Inventors: 고정욱; 지정민; 김동국
Original assignee: 주식회사 핏펫
Priority date: 2018-08-29
Filing date: 2018-08-30
Publication date: 2020-03-05
Also published as: JP2020535491A; KR20200025042A; CN111107792A

Abstract

Disclosed is a computer program stored on a computer-readable storage medium according to one embodiment of the present disclosure. The computer program comprises instructions for a computer to execute the following operations: obtaining a preview image photographed by a camera; recognizing a urinalysis kit in the preview image, wherein the urinalysis kit comprises a colorimetry table and a reagent pad strip; obtaining the shape of each of a plurality of colorimetry table cells included in the colorimetry table; recognizing the number of cells corresponding to a preset shape among the plurality of colorimetry table cells; if the number of cells corresponding to the preset shape is greater than or equal to a preset number, recognizing the position of each of the plurality of colorimetry table cells in the preview image; and if the position of each of the plurality of colorimetry table cells corresponds to a preset position, obtaining color information of each of a plurality of reagent pad cells included in the reagent pad strip by using the colorimetry table.

Description

Computer programs and terminals providing urine tests using colorimetric tables

The present disclosure relates to a computer program and a terminal stored in a computer readable storage medium, and more particularly, to a program and a terminal stored in a computer readable storage medium for providing a urine test using a colorimetric table.

In general, most urine test strips used for urinalysis are equipped with reagent pads that change color when the urine of the test subject touches. In addition, the urine test is a method of examining the health of the subject by comparing the degree of discoloration of the reagent pads with the reference color in response to the urine of the subject. Urine tests conducted in this manner require a specialist or separate urine strip analysis device to analyze the urine test strips.

Therefore, the urine test method using the urine test strip in this way it is not easy for the public to personally test. In addition, in order to personally test for urine, a urine test strip analysis device should be provided, but the price of such an urine test strip analysis device is expensive, so it is not easily used by the general public.

In order to solve this problem, a technique for analyzing test results by photographing urine test strips has been developed. That is, a method of colorimetric analysis of a photographed image by photographing a urine test strip and a reference color to be analyzed together.

However, in this method, the urine test strip to be photographed and the reference color are separated separately, and at the same time, the result of the test may be inaccurate due to the influence of the ambient light when photographing.

Thus, there may be a need in the art for a urine test system in which a person can easily proceed with a urine test personally and receive test results with higher accuracy.

Prior art document: Republic of Korea Utility Model Registration No. 20-0470398

SUMMARY The present disclosure has been made in response to the foregoing background, and provides a computer program and a terminal stored in a computer readable storage medium for providing a urine test using a colorimetric table.

The technical problems of the present disclosure are not limited to the technical problems mentioned above, and other technical problems not mentioned will be clearly understood by those skilled in the art from the following description.

In accordance with one embodiment of the present disclosure for solving the above problems, a computer program stored in a computer readable storage medium is disclosed. The computer program includes instructions for causing a computer to perform the following operations, the operations comprising: obtaining a preview image taken with a camera; Recognizing a urine test kit within the preview image, the urine test kit comprising a colorimetric table and a reagent pad strip; Obtaining a shape of each of the plurality of color table cells included in the color table; Recognizing the number of cells corresponding to a predetermined shape among the plurality of color table cells; Recognizing positions of each of the plurality of non-colored cells in the preview image when the number of cells corresponding to the preset shape is equal to or larger than a preset number; And acquiring color information of each of the plurality of reagent pad cells included in the reagent pad strip by using the color palette when the position of each of the plurality of color table cells corresponds to a preset position. have.

The operations may include generating a medical examination result corresponding to the color information by using health analysis data mapped to each of a plurality of colors previously stored in a memory; And displaying the result of the examination.

The operations may include transmitting the color information to an external server; Receiving information on a diagnosis result corresponding to the color information from the external server; And displaying information on the result of the examination.

In addition, obtaining a shape of each of the plurality of color table cells included in the color table may include: recognizing an outline of each of the plurality of color table cells; And acquiring a shape of each of the plurality of colorimetric cells based on an outline of each of the plurality of colorimetric cells.

In addition, recognizing the number of cells corresponding to a predetermined shape among the plurality of color table cells may include: recognizing a first horizontal length and a first vertical length of each of the plurality of color table cells; Recognizing a second horizontal length and a second vertical length of the urine test kit included in the preview image; And recognizing the number of cells that match the preset shape by using the first horizontal length, the second horizontal length, the first vertical length, and the second vertical length.

The cell corresponding to the preset shape may have a ratio value between the first horizontal length and the first vertical length corresponding to a first ratio value pre-stored in a memory, and the first horizontal length may be the second horizontal length. And a cell corresponding to a value obtained by multiplying a second ratio value pre-stored in the memory.

The cell corresponding to the preset shape may have a ratio value between the first horizontal length and the first vertical length corresponding to a first ratio value previously stored in a memory, and wherein the first vertical length is the second vertical length. And a cell corresponding to a value obtained by multiplying a third ratio value previously stored in the memory.

The cell corresponding to the preset shape may have a ratio value between the first horizontal length and the first vertical length corresponding to a first ratio value pre-stored in a memory, and the first horizontal length may be the second horizontal length. And a cell corresponding to a value obtained by multiplying a second ratio value previously stored in the memory, and the first vertical length may correspond to a value obtained by multiplying the second vertical length by a third ratio value pre-stored in the memory.

In addition, recognizing a position of each of the plurality of colorimetric cells in the preview image may include: recognizing each of a first reference cell and a second reference cell of the plurality of colorimetric cells; And based on the position of the first reference cell within the preview image, the position of the second reference cell within the preview image, and position information of colorimetric cells previously stored in a memory, the plurality of colorimetric colors within the preview image. Recognizing a location of each of the table cells.

In addition, the operation of acquiring color information of each of the plurality of reagent pad cells included in the reagent pad strip using the color palette may include recognizing a position of the reagent pad strip based on colorimetric information previously stored in a memory. action; And recognizing color information of each of the plurality of reagent pad cells when the preset second condition is satisfied.

The preset second condition may include a first virtual line connecting the first colorimetric cell included in the colorimetric table and a second colorimetric cell located below the first colorimetric cell and the reagent pad strip. The second virtual line connecting the first reagent pad cell and the second reagent pad cell included in parallel is parallel, and connects a third colorimetric cell positioned to the side of the first colorimetric cell and the first colorimetric cell. It can be satisfied if the first reagent pad cell is positioned on a third virtual line.

In addition, the operation of acquiring color information of each of the plurality of reagent pad cells included in the reagent pad strip using the colorimetric table may be performed by colorimetric analysis of the colors of each of the plurality of reagent pad cells with the plurality of colorimetric cells. And acquiring the color information of each of the plurality of reagent pad cells.

The color information analysis of the color information of each of the plurality of reagent pad cells with the plurality of colorimetric cells to obtain the color information of each of the plurality of reagent pad cells may include: generating a colorimetric analysis model; And calculating the color of each of the plurality of colorimetric cells and the plurality of reagent pad cells by using the colorimetric analysis model to obtain the color information of each of the plurality of reagent pad cells.

In addition, the operation of generating the colorimetric analysis model may be performed by labeling the learning color data of the plurality of colorimetric cells corresponding to the input of the training data and the learning steady state color data of the plurality of colorimetric cells previously stored in a memory. Generating data; And generating the colorimetric analysis model by learning the colorimetric analysis model including one or more network functions using a training data set including the training data.

The operation of generating the colorimetric analysis model by training the colorimetric analysis model including one or more network functions using a training data set including the training data may include: converting the learning color data into at least one of the colorimetric analysis model. Inputting to an input node included in an input layer of a network function; Deriving an error by comparing the learning color data with the labeled learning steady state color data and an output of the colorimetric analysis model; And a weight set on a link connecting each of the input node, the output layer, and the one or more hidden layers by propagating the error from the output layer of the one or more network functions of the colorimetric analysis model through the one or more hidden layers to the input layer. Updating operation may include.

The operation of acquiring the color information of each of the plurality of reagent pad cells by calculating the color of each of the plurality of color table cells and the plurality of reagent pad cells using the colorimetric analysis model may include: Combining at least two of the color models to generate a plurality of different color decision trees; And acquiring a plurality of color information corresponding to each of the plurality of reagent pad cells by using each of the plurality of color determination trees.

In accordance with an embodiment of the present disclosure for solving the above problems, a terminal for providing a urine test using a color table is disclosed. The terminal comprises: a camera unit for obtaining a preview image; And a controller configured to acquire color information of each of the plurality of reagent pad cells included in the reagent pad strip, based on the preview image.

In addition, the control unit recognizes a urine test kit in the preview image, the urine test kit including a colorimetric table and a reagent pad strip, and obtains the shape of each of the plurality of colorimetric cells included in the colorimetric table. And recognizing the number of cells corresponding to a preset shape among the plurality of colorimetric cells, and when the number of cells corresponding to the preset shape is greater than or equal to a preset number, the plurality of colorimetric cells in the preview image. Recognize each position, and when the position of each of the plurality of color table cells corresponds to a preset position, color information of each of the plurality of reagent pad cells included in the reagent pad strip may be obtained using the color table. Can be.

Technical solutions obtained in the present disclosure are not limited to the above-mentioned solutions, and other solutions not mentioned above may be apparent to those skilled in the art from the following description. It can be understood.

The present disclosure may provide a program and a terminal stored in a computer readable storage medium for providing a urine test using a colorimetric table.

Effects obtained in the present disclosure are not limited to the above-mentioned effects, and other effects not mentioned above may be clearly understood by those skilled in the art from the following description. .

Various aspects are now described with reference to the drawings, wherein like reference numerals are used to refer to like components throughout. In the following examples, for purposes of explanation, numerous specific details are set forth in order to provide a thorough understanding of one or more aspects. However, it will be apparent that such aspect (s) may be practiced without these specific details.

1 is a block diagram of a terminal for providing a urine test using a colorimetric table, according to some embodiments of the present disclosure.

2 is a flowchart for explaining an example of a method for providing a urine test using a colorimetric terminal according to some embodiments of the present disclosure.

3 illustrates a top view of a urine test kit, in accordance with some embodiments of the present disclosure.

4 is a flowchart illustrating an example of a method of a terminal acquiring a shape of cells of each of a plurality of colorimetric cells included in a colorimetric table according to some embodiments of the present disclosure.

5 is a flowchart illustrating an example of a method for a terminal to recognize a location of each of a plurality of colorimetric cells in a preview image according to some embodiments of the present disclosure.

FIG. 6 is a flowchart illustrating an example of a method in which a terminal acquires color information of each of a plurality of reagent pad cells included in a reagent pad strip using a colorimetric table according to some embodiments of the present disclosure.

FIG. 7 is a flowchart illustrating another example of a method in which a terminal acquires color information of each of a plurality of reagent pad cells included in a reagent pad strip using a colorimetric table according to some embodiments of the present disclosure.

8 is a diagram for describing a color decision tree used when a terminal generates colorimetric analysis data according to some embodiments of the present disclosure.

9 is a schematic diagram illustrating a network function in accordance with some embodiments of the present disclosure.

10 is a diagram for describing a method of generating a colorimetric analysis model, according to some embodiments of the present disclosure.

11 shows a perspective view of a urine test kit in accordance with some embodiments of the present disclosure.

12 is a diagram illustrating an example of an interface displayed on a terminal according to some embodiments of the present disclosure.

FIG. 13 is a diagram for describing another example of an interface displayed in a terminal according to some embodiments of the present disclosure; FIG.

Various embodiments and / or aspects are now disclosed with reference to the drawings. In the following description, for purposes of explanation, numerous specific details are set forth in order to provide a thorough understanding of one or more aspects. However, it will also be appreciated by one of ordinary skill in the art that this aspect (s) may be practiced without these specific details. The following description and the annexed drawings set forth in detail certain illustrative aspects of the one or more aspects. However, these aspects are exemplary and some of the various methods in the principles of the various aspects may be used and the descriptions described are intended to include all such aspects and their equivalents. Specifically, as used herein, “an embodiment”, “an example”, “aspect”, “an example” and the like are not to be construed that any aspect or design described is better or advantageous than other aspects or designs. It may not.

Regardless of the reference numerals, the same or similar components are given the same reference numerals and redundant description thereof will be omitted. In addition, in the description of the embodiments disclosed herein, if it is determined that the detailed description of the related known technology may obscure the gist of the embodiments disclosed herein, the detailed description thereof will be omitted. In addition, the accompanying drawings are intended to facilitate understanding of the embodiments disclosed herein, and the technical spirit disclosed herein is not limited by the accompanying drawings.

The terminology used herein is for the purpose of describing particular embodiments only and is not intended to be limiting of the invention. In this specification, the singular also includes the plural unless specifically stated otherwise in the phrase. As used herein, “comprises” and / or “comprising” does not exclude the presence or addition of one or more other components in addition to the mentioned components.

Although the first, second, etc. are used to describe various elements or components, these elements or components are of course not limited by these terms. These terms are only used to distinguish one element or component from another element or component. Therefore, the first device or component mentioned below may be a second device or component within the technical idea of the present invention.

Unless otherwise defined, all terms used in the present specification (including technical and scientific terms) may be used in a sense that can be commonly understood by those skilled in the art. In addition, terms that are defined in a commonly used dictionary are not ideally or excessively interpreted unless they are specifically defined clearly.

In addition, the term “or” is intended to mean an inclusive “or” rather than an exclusive “or”. That is, unless specified otherwise or unambiguously in context, "X uses A or B" is intended to mean one of the natural implicit substitutions. That is, X uses A; X uses B; Or where X uses both A and B, "X uses A or B" may apply in either of these cases. In addition, the term "and / or" as used herein is to be understood to refer to and include all possible combinations of one or more of the listed related items.

In addition, the terms "information" and "data" as used herein are often used interchangeably.

Although the first, second, etc. are used to describe various elements or components, these elements or components are of course not limited by these terms. These terms are only used to distinguish one element or component from another element or component. Therefore, the first device or component mentioned below may be a second device or component within the technical idea of the present disclosure.

Unless otherwise defined, all terms used in the present specification (including technical and scientific terms) may be used as meanings that can be commonly understood by those skilled in the art to which the present disclosure belongs. In addition, terms that are defined in a commonly used dictionary are not ideally or excessively interpreted unless they are specifically defined clearly.

When a component is said to be "connected" or "connected" to another component, it may be directly connected to or connected to that other component, but it may be understood that other components may exist in the middle. Should be. On the other hand, when a component is referred to as being "directly connected" or "directly connected" to another component, it should be understood that there is no other component in between.

The suffixes "module" and "unit" for components used in the following description are given or mixed in consideration of ease of specification, and do not have meanings or roles that are distinct from each other in themselves.

When an element or layer is referred to as "on" or "on" of another element or layer, another layer or element in between, as well as on top of another element or layer, Includes all intervening cases. On the other hand, when a component is referred to as "directly on" or "directly on" indicates that there is no intervening component or layer in between.

The spatially relative terms " below ", " beneath ", " lower ", " above ", " upper " It can be used to easily describe a correlation with a component or other components. Spatially relative terms should be understood to include terms that differ in orientation of the device in use or operation in addition to the directions shown in the figures.

For example, when flipping a component shown in the drawing, a component described as "below" or "beneath" of another component may be placed "above" the other component. Can be. Thus, the exemplary term "below" can encompass both an orientation of above and below. The components can be oriented in other directions as well, so that spatially relative terms can be interpreted according to the orientation.

The objectives and effects of the present disclosure and the technical configurations for achieving them will be apparent with reference to the embodiments described below in detail with the accompanying drawings. In describing the present disclosure, when it is determined that a detailed description of a known function or configuration may unnecessarily obscure the subject matter of the present disclosure, the detailed description will be omitted. In addition, terms to be described below are terms defined in consideration of functions in the present disclosure, and may vary according to a user's or operator's intention or custom.

However, the present disclosure is not limited to the embodiments disclosed below, but may be implemented in various forms. The present embodiments are merely provided to make the present disclosure complete and to fully convey the scope of the disclosure to those skilled in the art, and the present disclosure is defined only by the scope of the claims. . Therefore, the definition should be made based on the contents throughout the specification.

According to some embodiments of the present disclosure, the terminal 100 may include a camera unit 110, a display unit 120, a communication unit 130, a memory 140, and a controller 150. However, the above-described components are not essential in implementing the terminal 100, and thus, the terminal 100 may have more or fewer components than those listed above. Here, each component may be composed of a separate chip, module or device, or may be included in one device.

Terminal 100 according to some embodiments of the present disclosure may include a personal computer (PC), notebook (note book), mobile terminal (mobile terminal), smart phone (smart phone), tablet PC (tablet pc), etc. It may include all types of terminals provided with a camera unit 110 capable of taking an image.

The terminal 100 may include one or more camera units 110 for inputting image information. The camera unit 110 processes image frames such as still images or moving images obtained by the image sensor in the photographing mode. The processed image frame may be displayed on the display 120 or stored in the memory 140.

Meanwhile, the plurality of camera units 110 included in the terminal 100 may be arranged to form a matrix structure. The camera unit 110 forming the matrix structure may provide various angles or focuses to the terminal 100. The plurality of pieces of image information may be input. In addition, the plurality of camera units 110 may be arranged in a stereo structure to obtain a left image and a right image for implementing a stereoscopic image.

According to some embodiments of the present disclosure, the camera unit 110 may obtain a preview image for the examination of the urine test. In detail, the camera unit 110 may acquire a preview image including a urine test kit including a colorimetric table and a reagent pad strip.

A detailed description of the camera unit 110 obtaining the preview image for the examination of the urine test will be described in detail with reference to FIG. 12 below.

The controller 150 may be implemented to control the overall operation of the terminal 100. In addition, the controller 150 may perform various operations performed by the terminal 100 and process data. The controller 150 may drive an operating system (OS), an application, and a database manager for driving the terminal 100.

The controller 150 may include a central processing unit (CPU), a co-processor, an arithmetic processing unit (APU), a graphic processing unit (GPU), and a digital signal processor (CPU). Digital Signal Processor (DSP), Application Processor (AP) and Communication Processor (CP).

According to some embodiments of the present disclosure, the controller 150 may obtain the shape of each of the plurality of colorimetric cells included in the colorimetric table in the preview image. In addition, the controller 150 may recognize the number of cells corresponding to a preset shape among the plurality of color table cells. In addition, when the number of cells corresponding to the preset shape is greater than or equal to the preset number, the controller 150 may recognize positions of each of the plurality of colorimetric cells in the preview image. In addition, when the position of each of the plurality of color table cells corresponds to a preset position, the controller 150 may acquire color information of each of the plurality of reagent pad cells included in the reagent pad strip using the color table. .

According to some embodiments of the present disclosure, the controller 150 may include color information of each of the plurality of reagent pad cells included in the reagent pad strip obtained by the controller 150 and a plurality of colors previously stored in the memory 140. By using the mapped health analysis data, a check result corresponding to the color information may be generated. In this case, the display 120 may display information on the examination result.

The display unit 120 displays (outputs) information processed by the terminal 100. For example, the display 120 may display execution screen information of an application program driven in the terminal 100, or UI (User Interface) or Graphic User Interface (GUI) information according to the execution screen information.

The display unit 151 may include a liquid crystal display (LCD), a thin film transistor-liquid crystal display (TFT LCD), an organic light-emitting diode (OLED), and a flexible display (flexible). display, a 3D display, and an e-ink display.

According to some embodiments of the present disclosure, the controller 150 may control the display unit 120 to display a result of the examination of the urine test generated by recognizing the color of the reagent pad strip. However, the present disclosure is not limited thereto, and the examination result may be information received from the external server through the communication unit 130 by the controller 150 of the terminal 100. Here, the examination result may mean information corresponding to each of the plurality of examination items that can be checked through the urine test.

In detail, the controller 150 may control the display 120 to display a list including a result of examinations corresponding to a plurality of items.

A detailed description of the display unit 120 displaying the result of the examination will be described in detail with reference to FIG. 13 below.

The communication unit 130 may include one or more modules that enable wireless communication between the terminal 100 and the wireless communication system, between the terminal 100 and another terminal 100, or between the terminal 100 and an external server. have. In addition, the communication unit 130 may include one or more modules for connecting the terminal 100 to one or more networks.

Wireless Internet technologies include, for example, Wireless LAN (WLAN), Wireless-Fidelity (Wi-Fi), Wireless Fidelity (Wi-Fi) Direct, Digital Living Network Alliance (DLNA), Wireless Broadband (WiBro), and WiMAX (World Interoperability for Microwave Access (HSDPA), High Speed Downlink Packet Access (HSDPA), High Speed Uplink Packet Access (HSUPA), Long Term Evolution (LTE), Long Term Evolution-Advanced (LTE-A), and the like. The module for transmitting and receiving data according to at least one wireless Internet technology in a range including the Internet technologies not listed above.

According to some embodiments of the present disclosure, the communication unit 130 may transmit the color information of each of the plurality of reagent pad cells included in the reagent pad strip obtained by the controller 150 to an external server. In addition, the communication unit 130 may receive information on the examination result corresponding to the color information from the external server. In this case, the display 120 may display information on the examination result.

The memory 140 stores data supporting various functions of the terminal 100. The memory 140 may store a plurality of application programs or applications that are driven by the terminal 100, data for operating the terminal 100, and instructions. At least some of these applications may be downloaded from an external server through wireless communication. In addition, at least some of these application programs may exist on the terminal 100 from the time of shipment for basic functions of the terminal 100. Meanwhile, the application program may be stored in the memory 140 and installed on the terminal 100 to be driven by the controller 150 to perform an operation (or function) of the terminal 100.

The memory 170 may include a flash memory type, a hard disk type, a solid state disk type, an SSD type, a silicon disk drive type, and a multimedia card micro type. ), Card type memory (e.g. SD or XD memory, etc.), random access memory (RAM), static random access memory (SRAM), read-only memory (ROM), electrically erasable programmable read It may include at least one type of storage medium of -only memory (PROM), programmable read-only memory (PROM), magnetic memory, magnetic disk and optical disk. The mobile terminal 100 may be operated in connection with a web storage that performs a storage function of the memory 170 on the Internet.

According to some embodiments of the present disclosure, the memory 140 may store health analysis data mapped to each of a plurality of colors that may appear on the reagent pad. Here, the health analysis data may include information about a health state corresponding to each of the plurality of colors that may appear on the reagent pad. For example, when the controller 150 recognizes the color information of the reagent pad using an RGB (Red, Green, Blue) model among the color models, the controller 150 recognizes a color corresponding to each value of the R, G, and B values. The health analysis data mapped to the color may be recognized.

In addition to the operation related to the application program, the controller 150 generally controls the overall operation of the terminal 100. The controller 150 may provide or process information or a function appropriate to a user by processing signals, data, information, or the like input or output through the above-described components or driving an application program stored in the memory 140.

In addition, the controller 150 may control at least some of the components described with reference to FIG. 1 to drive an application program stored in the memory 140. Furthermore, the controller 150 may operate by combining at least two or more of the components included in the terminal 100 to drive the application program.

2 is a flowchart for explaining an example of a method for providing a urine test using a colorimetric terminal according to some embodiments of the present disclosure. 3 illustrates a top view of a urine test kit, in accordance with some embodiments of the present disclosure. 4 is a flowchart illustrating an example of a method of a terminal acquiring a shape of cells of each of a plurality of colorimetric cells included in a colorimetric table according to some embodiments of the present disclosure. 5 is a flowchart illustrating an example of a method for a terminal to recognize a location of each of a plurality of colorimetric cells in a preview image according to some embodiments of the present disclosure. FIG. 6 is a flowchart illustrating an example of a method in which a terminal acquires color information of each of a plurality of reagent pad cells included in a reagent pad strip using a colorimetric table according to some embodiments of the present disclosure. FIG. 7 is a flowchart illustrating another example of a method in which a terminal acquires color information of each of a plurality of reagent pad cells included in a reagent pad strip using a colorimetric table, according to some embodiments of the present disclosure. 8 is a diagram for describing a color decision tree used when a terminal generates colorimetric analysis data according to some embodiments of the present disclosure.

According to some embodiments of the present disclosure, the controller 150 of the terminal 100 may obtain a preview image captured by the camera unit 110 (S100).

In detail, the controller 150 may acquire the preview image captured by the camera unit 110 based on the preview image capture command. Here, the photographing command may be received through the preview image photographing interface.

For example, when the controller 150 receives a selection input for an indicator related to the start of capture included in the preview image capturing interface, the controller 150 may recognize that a capture command has been received.

In addition, the controller 150 may recognize the urine test kit in the preview image (S200).

For example, the controller 150 may recognize an outline of an object in the captured preview image. In addition, the controller 150 may recognize whether the outline of the object is a shape previously stored in the memory 140. When the controller 150 recognizes that the outline of the object corresponds to a shape previously stored in the memory 140, the controller 150 may recognize the object included in the photographed preview image as a urine test kit.

As another example, the controller 150 may recognize an outline of an object in the captured preview image. The controller 150 may recognize whether the shape of the object and the size of the object correspond to the shape and size previously stored in the memory 140. When the controller 150 recognizes that the outline of the object corresponds to the shape and size previously stored in the memory 140, the controller 150 may recognize the object included in the photographed preview image as a urine test kit.

When the urine test kit is recognized in the preview image, the controller 150 may acquire the shapes of each of the plurality of colorimetric cells included in the colorimetric table (S300).

For example, the controller 150 may recognize an outline of each of the plurality of color table cells. In addition, the controller 150 may obtain the shape of each of the plurality of color table cells based on the outline of each of the plurality of color table cells.

According to some embodiments of the present disclosure, the controller 150 of the terminal 100 may recognize the number of cells corresponding to a predetermined shape among the plurality of color table cells (S400). A method of recognizing the number of cells corresponding to a preset shape will be described below with reference to FIGS. 3 and 4.

Referring to FIG. 4, the controller 150 of the terminal 100 may recognize the first horizontal length W1 and the first vertical length H1 of each of the plurality of colorimetric cells (S410). In addition, the controller 150 may recognize the second horizontal length W2 and the second vertical length H2 of the urine test kit included in the preview image (S420).

Referring to FIG. 3, the first horizontal length W1 is the horizontal length of each of the colorimetric cells in the preview image. Also, the first height H1 is the length of each of the colorimetric cells in the preview image. On the other hand, the second horizontal length W2 is the horizontal length of the colorimetric table 220 in the preview image. Also, the second vertical length H2 is the vertical length of the colorimetric table 220 in the preview image.

Referring to FIG. 4 again, the controller 150 may have a preset shape using the first horizontal length W1, the second horizontal length W2, the first vertical length H1, and the second vertical length H2. It is possible to recognize the number of cells that match with (S430).

In detail, at least one of a first ratio value, a second ratio value, and a third ratio value may be stored in the memory 140. The controller 150 may recognize the number of cells that match the preset shape by using at least one of the first ratio value, the second ratio value, and the third ratio value. Here, the first ratio value may be a value related to the ratio between the first horizontal length W1 and the first vertical length H1, and the second ratio value may include a first horizontal length W1 and a second horizontal length ( It may be a value associated with the ratio between W2), and the third ratio value may be a value associated with the ratio between the first longitudinal length H1 and the second longitudinal length H2.

According to some embodiments, the controller 150 may recognize whether the shapes of the plurality of cells coincide with the preset shapes using the first ratio value, the first horizontal length, and the first vertical length.

For example, when the controller 150 recognizes that the first ratio value pre-stored in the memory 140 is 1, the first horizontal length W1 is 0.5 mm, and the first vertical length H1 is 0.5 mm. In addition, it can be recognized that the shape of the colorimetric cell matches the preset shape.

In more detail, when the controller 150 recognizes that the value obtained by multiplying the first ratio value 1 by 0.5, which is the first horizontal length W1, corresponds to 0.5 that is the first vertical length H1, It can be recognized that the shape matches the preset shape.

According to some other embodiments, the controller 150 may include a ratio value between the first horizontal length W1 and the first vertical length H1 corresponding to the first ratio value pre-stored in the memory 140, and the second horizontal width. When the value obtained by multiplying the length W2 by the second ratio value pre-stored in the memory 140 corresponds to the first horizontal length W1, it may be recognized that the shape of the colorimetric cell corresponds to the preset shape.

For example, the controller 150 recognizes that the first ratio value pre-stored in the memory 140 is 1, the first horizontal length W1 is 0.5 mm, and the first vertical length H1 is 0.5 mm, When it is recognized that the second ratio value is 0.01 and the second horizontal length W2 is 50 mm, it may be recognized that the shape of the colorimetric cell corresponds to the preset shape.

In more detail, the controller 150 multiplies the first ratio value 1 by 0.5, which is the first horizontal length W1, and corresponds to 0.5 that is the first vertical length H1, and the second ratio value is 0.01 to the second ratio value. When it is recognized that the value multiplied by 50, which is 2 horizontal lengths W2, corresponds to 0.5, which is the first horizontal length W1, it may be recognized that the shape of the colorimetric cell corresponds to the preset shape.

According to another exemplary embodiment, the controller 150 may include a ratio value between the first horizontal length W1 and the first vertical length H1 corresponding to the first ratio value pre-stored in the memory 140, and the second ratio may be the second ratio. When the value obtained by multiplying the vertical length H2 by the preset third ratio value corresponds to the first vertical length H1, it may be recognized that the shape of the colorimetric cell corresponds to the preset shape.

For example, the controller 150 recognizes that the first ratio value pre-stored in the memory 140 is 1, the first horizontal length W1 is 0.5 mm, and the first vertical length H1 is 0.5 mm, When it is recognized that the third ratio value is 0.01 and the second vertical length H2 is 50 mm, it may be recognized that the shape of the colorimetric cell corresponds to the preset shape.

In more detail, the controller 150 multiplies the first ratio value 1 by 0.5, which is the first horizontal length W1, and corresponds to 0.5 which is the first vertical length H1, and the third ratio value is 0.01 to the third ratio value. When it is recognized that the value multiplied by 50, which is 2 vertical lengths H2, corresponds to 0.5, which is the first vertical length H1, it may be recognized that the shape of the colorimetric cell corresponds to the preset shape.

According to another exemplary embodiment, the controller 150 may include a ratio value between the first horizontal length W1 and the first vertical length H1 corresponding to the first ratio value pre-stored in the memory 140, and the second value may be the second ratio. The value obtained by multiplying the horizontal length W2 by the second ratio value pre-stored in the memory 140 corresponds to the first horizontal length W1 and the value obtained by multiplying the second vertical length H2 by the preset third ratio value When it corresponds to the first vertical length H1, it may be recognized that the shape of the colorimetric cell corresponds to the preset shape.

For example, the controller 150 recognizes that the first ratio value pre-stored in the memory 140 is 1, the first horizontal length W1 is 0.5 mm, and the first vertical length H1 is 0.5 mm, When the second ratio value is 0.01 and the second horizontal length W2 is recognized as 50 mm, and the third ratio value is 0.01 and the second vertical length H2 is 50 mm, the shape of the colorimetric cell is not shown. It can be recognized as matching the set shape.

In more detail, the controller 150 multiplies the first ratio value 1 by 0.5, which is the first horizontal length W1, and corresponds to 0.5 that is the first vertical length H1, and the second ratio value is 0.01 to the second ratio value. 2 multiplied by 50, which is the width W2, corresponds to 0.5, which is the first horizontal length W1, and multiplied by 50, which is the second longitudinal length, H2, by the third ratio value, 0.01, the first vertical length H1. If it is recognized that it corresponds to 0.5), it can be recognized that the shape of the colorimetric cell matches the preset shape.

According to some embodiments of the present disclosure, when the number of cells corresponding to a preset shape is not greater than or equal to a preset number (for example, 40), the controller 150 of the terminal 100 (S500, No), The camera unit 110 may be controlled to retake the preview image. In this case, the controller 150 may control the display 120 to display the guide text.

According to some other embodiments of the present disclosure, the controller 150 of the terminal 100 may display a preview image when the number of cells corresponding to the preset shape is not greater than or equal to the value of the total number of cells. The camera unit 110 may be controlled to photograph again.

For example, when the preset ratio value is 0.8 and the total number of cells is 55, the controller 150 previews when the number of total cells is not more than 44, which is a value multiplied by the preset ratio value 0.8, which is 55. The camera unit 110 may be controlled to retake the image. That is, when the number of all cells is 55, when the number of cells corresponding to the preset shape is less than 44, the controller 150 may control the camera unit 110 to retake the preview image.

As described above, the controller 150 may determine whether the camera unit 110 properly photographed the urine test kit included in the preview image by comparing the number of cells corresponding to the preset shape with the preset number. Can be. In detail, the controller 150 compares the number of cells corresponding to the preset shape with the preset number, and displays the preview image so that the camera unit 110 can recognize the plurality of cells of the urine test kit included in the preview image. It may be determined whether or not a picture was taken.

Therefore, the user can perform the urine test simply by photographing the urine test kit with a camera.

Meanwhile, referring back to FIG. 2, when the number of cells corresponding to a preset shape is greater than or equal to a preset number (S500, Yes), the controller 150 of the terminal 100 includes a plurality of colorimetric cells in the preview image. Each position may be recognized (S600). A method of recognizing a location of each of the plurality of colorimetric cells in the preview image will be described below with reference to FIGS. 3 and 5.

First, referring to FIG. 5, the controller 150 of the terminal 100 may recognize each of the first reference cell 201 and the second reference cell 202 of the plurality of colorimetric cells (S610). Here, the first reference cell 201 and the second reference cell 202 may be a cell located at a specific position among the plurality of colorimetric cells, or may be any cell of the plurality of colorimetric cells.

The controller 150 is based on the position of the first reference cell 201 in the preview image, the position of the second reference cell 202 in the preview image, and the position information of colorimetric cells pre-stored in the memory 140. The location of each of the plurality of colorimetric cells in the preview image may be recognized (S620). Here, the location information of the colorimetric cells may refer to information that can recognize the location of each of the plurality of cells corresponding to the reference cell. For example, the location information of colorimetric cells may include location information of cells located at the top, bottom, right, and left sides of the reference cell.

For example, referring to FIG. 3, the controller 150 may recognize the first reference cell 201 located at the top right of the plurality of colorimetric cells and the second reference cell 202 located at the bottom left of the plurality of colorimetric cells. Can be. In this case, the controller 150 may recognize positions of a plurality of cells positioned below or to the right of the first reference cell 201 based on the first reference cell 201. In addition, the controller 150 may recognize positions of a plurality of cells positioned above or to the left of the second reference cell 202 based on the second reference cell 202.

In another example, the controller 150 may include at least two cells that are comparable to position information of colorimetric cells pre-stored in the memory 140 among a plurality of colorimetric cells, the first reference cell 201 and the second reference cell 202. Can be determined. In addition, the controller 150 may use the first reference cell 201 and the second reference cell 201 and the second reference cell 202 and the color information of the colorimetric cells pre-stored in the memory 140. The location of each of the full colorimetric cells, including the reference cell 202, can be recognized.

Referring back to FIG. 2, the controller 150 of the terminal 100 may recognize whether each of the plurality of color table cells corresponds to a preset position (S700).

The controller 150 may control the camera unit 110 to retake the preview image when the position of each of the plurality of color table cells does not correspond to the preset position (S700, No). In this case, the controller 150 may control the display 120 to display the guide text so that the positions of each of the plurality of colorimetric cells are at a preset position.

According to some embodiments of the present disclosure, when the location of each of the plurality of colorimetric cells corresponds to a preset position (S700, Yes), the controller 150 of the terminal 100 uses the colorimetric table to apply the reagent pad strip. Color information of each of the plurality of included reagent pad cells may be obtained (S800). A method of acquiring color information of each of the plurality of reagent pad cells included in the reagent pad strip using the colorimetric table will be described below with reference to FIGS. 3 and 6.

Referring to FIG. 6, the controller 150 of the terminal 100 may recognize a location of a reagent pad strip based on colorimetric information previously stored in the memory 140 (S810a). Here, the colorimetric information pre-stored in the memory 140 may include information about the position of the reagent pad strips coupled to the colorimetric table. Accordingly, the controller 150 may recognize the location of the reagent pad strips coupled to the colorimetric table using the colorimetric information pre-stored in the memory 140.

The controller 150 may recognize whether the second condition is satisfied. Here, the second condition may be a condition for confirming whether or not the position of the reagent pad strip coupled to the color table is at a preset position.

According to some embodiments of the present disclosure, the second condition may include a first colorimetric cell 221 included in the colorimetric table and a second colorimetric cell 222 positioned below the first colorimetric cell 221. The first virtual line 231 connected to the second virtual line 232 connecting the first reagent pad cell 211 and the second reagent pad cell 212 included in the reagent pad strip 210 are parallel to each other. And the first reagent pad on a third virtual line 233 connecting the first colorimetric cell 221 and a third colorimetric cell 223 positioned to the side of the first colorimetric cell 221. When the cell is located, it may be a condition satisfied. However, the present invention is not limited thereto.

If the second condition is not satisfied, the controller 150 may control the camera unit 110 to retake the preview image. In this case, the controller 150 may control the display unit 120 to display the guide text so that each of the plurality of reagent pad cells may be at a preset position.

On the other hand, if the second condition is satisfied, the controller 150 may recognize color information of each of the plurality of reagent pad cells (S820a).

According to some other embodiments of the present disclosure, when the location of each of the plurality of colorimetric cells corresponds to a preset position (S700, Yes), the controller 150 of the terminal 100 uses a colorimetric table. Color information of each of the plurality of reagent pad cells included in the strip may be obtained (S800).

For example, the controller 150 may acquire color information of each of the plurality of reagent pad cells by color analyzing the color of each of the plurality of reagent pad cells with the plurality of colorimetric cells. In this case, since color information of each of the plurality of reagent pad cells is obtained through colorimetric cells and colorimetric analysis, the reagents are more accurate regardless of the brightness of the environment in which the urine test kit is photographed or the camera state of the terminal 100. Color information of each of the pad cells may be obtained.

The controller 150 may generate a plurality of color analysis models when acquiring color information of each of the plurality of reagent pad cells, and acquire color information of each of the plurality of reagent pad cells using the colorimetric analysis model. . This will be described below with reference to FIGS. 3, 7 and 8.

Referring to FIG. 7, the controller 150 may generate a colorimetric analysis model including a plurality of different color decision trees generated by combining at least two or more color models of the plurality of color models (S810b).

In detail, the controller 150 may generate a plurality of different color decision trees by combining at least two or more color models of the plurality of color models. In addition, the controller 150 may generate a colorimetric analysis model including a plurality of different color decision trees. Here, the plurality of color models may include RGB (Red, Green, Blue) model, CMYK (Cyan, Magenta, Yellow, Black) model, HSV (Hue, Saturation, Value) model, HSL (Hue, Saturation, Lightness) model, It may be a HSI (Hue, Saturation, Intensity) model and HSB (Hue, Saturation, Brightness) model.

More specifically, referring to FIG. 8, the controller 150 combines at least two or more color models of the plurality of color models to form the first color decision tree 10a, the second color decision tree 10b, and the first color decision tree 10b. Each of the third color decision tree 10c and the fourth color decision tree 10d may be generated.

For example, the controller 150 may generate the first color determination tree 10a using the RGB model, the CMYK model, and the HSV model. The controller 150 may generate the second color decision tree 10b using the CMYK model, the HSV model, and the HSL model. The controller 150 may generate the third color decision tree 10c using the HSV model, the HSL model, and the HSI model. The controller 150 may generate the fourth color decision tree 10d using the HSL model, the HSI model, and the HSB model.

According to some embodiments of the present disclosure, the controller 150 is based on the color of each of the colorimetric cells recognized through the colorimetric analysis model and the information on the color of each of the colorimetric cells pre-stored in the memory 140. To generate the correction information. In detail, the controller 150 may generate correction information including a color difference value of a normal state of a specific cell stored in the memory 140 and a color recognized through a plurality of color decision trees through a colorimetric analysis model. .

Referring back to FIG. 7, the controller 150 calculates color information of each of the plurality of color table cells and color information of each of the plurality of reagent pad cells by using a colorimetric analysis model, thereby generating color information of each of the plurality of reagent pad cells. It may be obtained (S820b).

According to some embodiments, the controller 150 may obtain a plurality of prediction colors of each of the plurality of reagent pad cells through each of a plurality of different color decision trees. In addition, the controller 150 may recognize, as the color of each of the plurality of reagent pad cells, the color that is most output as the same color among the plurality of prediction colors of each of the plurality of reagent pad cells.

Specifically, referring to FIG. 8, the controller 150 may acquire the first prediction color 11 of a specific cell among the plurality of reagent pad cells through the first color decision tree 10a. In addition, the controller 150 may acquire the second prediction color 12 of the specific cell through the second color decision tree 10b. In addition, the controller 150 may obtain the third prediction color 13 of the specific cell through the third color decision tree 10c. In addition, the controller 150 may acquire the fourth prediction color 14 of the specific cell through the fourth color decision tree 10d. In addition, the controller 150 may recognize, as the color of a specific cell, the predicted color most frequently output as the same color among the plurality of predicted

colors

11, 12, 13, and 14 acquired through each of the plurality of color decision trees. .

For example, a first prediction color 11 of a specific cell is yellow, a second prediction color 12 of a specific cell is yellow, a third prediction color 13 of a specific cell is orange, and a first prediction color 11 of a specific cell is yellow. 4 When the predicted color 14 is yellow, the controller 150 may recognize yellow, which is most output as the same color, as a color of a specific cell through a colorimetric analysis model. Therefore, the controller 150 may recognize the color of the specific cell more accurately.

According to another exemplary embodiment, the controller 150 may obtain color information of each of the plurality of reagent pad cells using the plurality of prediction colors and correction information of each of the plurality of reagent pad cells.

In detail, the controller 150 may recognize the plurality of predicted colors for any one of the plurality of reagent pad cells using each of the plurality of color determination trees. The controller 150 may acquire color information of each of the plurality of reagent pad cells by adding or subtracting a difference value included in the correction information to the color most outputted with the same color among the plurality of prediction colors.

Accordingly, the controller 150 may acquire more accurate color information of each of the reagent pad cells, regardless of the brightness of the environment in which the urine test kit is photographed or the camera state of the terminal 100.

In this case, the controller 150 may generate a diagnosis result corresponding to the color information of each of the plurality of reagent pad cells obtained by using the health analysis data mapped to each of the plurality of colors previously stored in the memory 140. have. In addition, the controller 150 may control the display 120 to display the generated examination result.

However, the present invention is not limited thereto, and the controller 150 may control the communicator 130 to transmit the color information of each of the obtained plurality of reagent pad cells to an external server. In addition, the controller 150 may receive information about a result of the examination from an external server through the communication unit 130. In this case, the controller 150 may control the display 120 to display the received examination result.

Therefore, the user may be provided with a diagnosis result generated based on more accurate prediction color information.

The aforementioned steps of FIGS. 2 and 4 to 7 may be changed in order, and at least one or more steps may be omitted or added. In addition, the above-described steps are only embodiments of the present disclosure, and the scope of the present disclosure is not limited thereto.

Throughout this specification, computational models, neural networks, network functions, neural networks may be used in the same sense. A neural network may consist of a set of interconnected computing units, which may generally be referred to as "nodes." Such "nodes" may be referred to as "neurons". The neural network comprises at least one node. The nodes (or neurons) that make up the neural networks may be interconnected by one or more "links".

Within a neural network, one or more nodes connected via a link may form a relationship of input node and output node relatively. The concept of an input node and an output node is relative; any node in an output node relationship for one node may be in an input node relationship in relation to another node, and vice versa. As mentioned above, the input node to output node relationship can be created around the link. An output node can be connected to a single input node via a link, and vice versa.

In an input node and output node relationship connected via one link, the output node may be determined based on data input to the input node. Here, the node interconnecting the input node and the output node may have a weight. The weight may be variable, and may be varied by the user or algorithm in order for the neural network to perform the desired function. For example, if an input node is interconnected by each link to one output node, the output node is based on the values input to the input node associated with the output node and the weights set on the link corresponding to the input node. The value can be determined.

As described above, a neural network is formed by interconnecting one or more nodes through one or more links to form an input node and an output node relationship within the neural network. The characteristics of the neural network may be determined according to the number of nodes and links in the neural network, the relationship between the nodes and the links, and the value of the weights assigned to the links. For example, if there are the same number of nodes and links, and there are two neural networks with different weight values between the links, the two neural networks may be recognized as different from each other.

The neural network may comprise one or more nodes. Some of the nodes that make up the neural network may construct one layer based on distances from the original input node, for example, a set of nodes with a distance n from the original input node, You can configure n layers. The distance from the original input node may be defined by the minimum number of links that must pass to reach the node from the original input node. However, the definition of such a layer is arbitrary for explanation, and the order of the layer in the neural network may be defined in a manner different from that described above. For example, a layer of nodes may be defined by distance from the final output node.

The initial input node may refer to one or more nodes to which data is directly input without going through a link in relation to other nodes among the nodes in the neural network. Alternatively, in a neural network network, in a relationship between nodes based on a link, it may mean nodes having no other input nodes connected by a link. Similarly, the final output node may refer to one or more nodes that do not have an output node in relation to other nodes of the nodes in the neural network. Also, the hidden node may refer to nodes constituting a neural network other than the first input node and the last output node. The neural network according to an embodiment of the present disclosure may have the same number of nodes in the input layer as the number of nodes in the output layer, and the number of nodes decreases and then increases again as the number of nodes goes from the input layer to the hidden layer. Can be. In addition, the neural network according to another embodiment of the present disclosure may be a neural network in which the number of nodes in the input layer is smaller than the number of nodes in the output layer, and the number of nodes decreases as the node progresses from the input layer to the hidden layer. have. In addition, the neural network according to another embodiment of the present disclosure may have a larger number of nodes in the input layer than the number of nodes in the output layer, and the number of nodes increases as the number of nodes increases from the input layer to the hidden layer. Can be. The neural network according to another embodiment of the present disclosure may be a neural network of a combination of the neural networks described above.

A deep neural network (DNN) may refer to a neural network including a plurality of hidden layers in addition to an input layer and an output layer. Deep neural networks can be used to identify latent structures of data. In other words, you can identify the potential structures of photos, texts, videos, voices, and music (e.g., what objects are in the photos, what the content and emotions of the text are, and what the content and emotions of the voice are). . Deep neural networks include convolutional neural networks (CNNs), recurrentneural networks (RNNs), auto encoders, Generic Adversarial Networks (GAN), restricted boltzmann (RBM) machine), deep belief network (DBN), Q network, U network, Siamese network and the like. The description of the deep neural network described above is merely an example and the present disclosure is not limited thereto.

The neural network may be learned in at least one of supervised learning, unsupervised learning, and semi supervised learning. Training of neural networks is intended to minimize errors in the output. In the neural network learning, the neural network errors are inputted from the output layer of the neural network in order to repeatedly input the training data into the neural network, calculate the neural network output and target errors for the training data, and reduce the errors. The process of updating the weight of each node of the neural network by backpropagation in the direction. In the case of teacher learning, the learning data using the correct answer is labeled in each learning data (ie, the labeled learning data), and in the case of the comparative learning, the correct answer may not be labeled in each learning data. That is, for example, the learning data in the case of teacher learning regarding data classification may be data in which a category is labeled in each of the learning data. The labeled training data is input to the neural network, and an error can be calculated by comparing the label of the training data with the output (category) of the neural network. As another example, in the case of non-comparative learning on data classification, an error may be calculated by comparing learning data as an input with a neural network output. The calculated error is propagated backward in the neural network (ie, the direction from the output layer to the input layer), and the connection weight of each node of each layer of the neural network may be updated according to the reverse propagation. The connection weight of each node to be updated may be changed according to a learning rate. The computation of the neural network for the input data and the backpropagation of the errors can constitute a learning cycle. The learning rate may be applied differently according to the number of repetitions of the learning cycle of the neural network. For example, in the early stages of neural network learning, high learning rates can be used to allow the neural network to quickly achieve a certain level of performance, increasing efficiency, and lower learning rates for later learning.

In the learning of neural networks, in general, the training data may be a subset of the actual data (i.e., the data to be processed using the trained neural network), thus reducing the error for the training data but not the error for the actual data. There may be an increasing learning cycle. Overfitting is a phenomenon in which an error about the actual data is increased by excessively learning the training data. For example, a neural network that learns a cat by showing a yellow cat may not recognize that the cat is a cat other than a yellow cat. Overfitting can act as a cause of increased errors in machine learning algorithms. Various optimization methods can be used to prevent such overfitting. In order to prevent overfitting, a method of increasing learning data, regulating, or dropping out of a node of a network in the course of learning may be applied.

A learning method in a colorimetric analysis model according to some embodiments of the present disclosure is described.

The controller 150 may generate a colorimetric analysis model including one or more network functions 600. The network function 600 may include one input layer 630, one or more

hidden layers

640 and 650, and one output layer 660. Here, the input layer 630 may include an input node 601. One or more

hidden layers

640 and 650 may each include one or more hidden nodes. The output layer 660 can include an output node 661. In addition, the input node 601 included in the input layer 630, the one or more hidden nodes included in the

hidden layers

640 and 650, and the output node 661 included in the output layer 660 are one of different layers. The above nodes and links may be connected respectively. In addition, each link may be weighted.

According to some embodiments of the present disclosure, when generating a colorimetric analysis model, the controller 150 may include learning color data of a plurality of colorimetric cells corresponding to input of training data and a plurality of colorimetric colors previously stored in the memory 140. Learning data can be generated by labeling the learning steady state color data of a table cell. In addition, the controller 150 may train a colorimetric analysis model including one or more network functions using a training data set including training data. For example, the controller 150 may input training color data into the network function 600 of the colorimetric analysis model. Each item of learning color data may be input to an input node 601 included in the input layer 630 of the network function 600 of the colorimetric analysis model. For example, an item value for at least one of the color data of each of the plurality of colorimetric cells may be input to the input node 601.

According to some embodiments of the present disclosure, the controller 150 may input the learning color data to an input node included in an input layer of one or more network functions of the colorimetric analysis model. In addition, the controller 150 may derive an error by comparing the learning color data with the labeled learning steady state color data and the output of the colorimetric analysis model. In addition, the controller 150 may update the weights set in the respective links by propagating the derived error from the output layer of the one or more network functions of the colorimetric analysis model to the input layer through the one or more hidden layers.

The controller 150 may calculate the item value input to the input node 601 included in the input layer 630 of the network function 600 with the weight set on the link connected to the input node and propagate it to the hidden layer. have. For example, the first hidden node 621 included in the hidden layer 1 640 may receive a value delivered to the input node 601 and a value calculated from the first weight 611. For example, the first hidden node 621 included in the hidden layer 1 640 may receive a value obtained by multiplying the value transmitted to the input node 601 by the first weight 611. The description of the above operation is merely an example, and the present disclosure is not limited thereto.

The learning color data of the network function 600 may be propagated from the input layer 630 to the output layer 660 through the hidden layer 1 640 and the hidden layer 2 650. Network function based on the error of the color information (i.e. output) and the learning steady state color data (i.e. correct answer) of each of the plurality of colorimetric cells, which is an output value at the output node 661 included in the output layer 660. The weight of 600 can be adjusted.

The controller 150 passes from the output layer 660 of the network function 500 to the input layer 630 via one or more hidden layers (for example, in order of hidden layer 2 650 and then hidden layer 1 640). While propagating the error, the weights set for each link may be updated (for example, after adjusting the weights of W2 (1,1) 631), the weights of W1 (1,1) 611 may be adjusted.

According to some embodiments of the present disclosure, when the colorimetric analysis model is generated, the controller 150 may input color data of each of the plurality of reagent pad cells to be measured into the generated colorimetric analysis model. In this case, the colorimetric analysis model may output color information of each of the reagent pad cells based on a weight set in advance by learning. Therefore, the controller 150 may acquire color information of each of the plurality of reagent pad cells, which are output values of the colorimetric analysis model.

Specifically, the controller 150 may input each item value of items included in the color data of the reagent pad cell to an input node included in the input layer 630 of the network function 600. For example, the controller 150 may input color data of one of the plurality of reagent pad cells (eg, the first reagent pad cell) to the input node 601 of the input layer 630. Can be. The controller 150 weights the value input to the input layer 630 of the network function 600 (in this example, the first weight W1 (1,1) 611) and the second weight W2 (1,1). Output node 661 included in output layer 660 via one or more hidden nodes (in this example, including hidden layer 1 640 and hidden layer 2 650) Can propagate. The controller 150 may recognize color information, which is an output value of the output node 661, as color information of the first reagent pad cell.

The description of the method for generating color information of each of the plurality of reagent pad cells described above is merely an example, and the present disclosure is not limited thereto.

11 illustrates an exploded perspective view of a urine test kit in accordance with some embodiments of the present disclosure.

According to some embodiments of the present disclosure, urine test kit 200 may include a reagent pad strip 210 and a colorimetric table 220.

Specifically, the reagent pad strip 210 of the urine test kit 200 may be coupled to one region of the colorimetric table 220.

One region of the colorimetric table 220 may include an inlet corresponding to the shape of the reagent pad strip 210 to facilitate coupling of the reagent pad strip 210. The reagent pad strip 210 may be combined with the colorimetric table 220 by insertion into the inlet. The reagent pad strip 210 of the urine test kit 200 may be inserted into the inlet of the color table 220 to be firmly coupled to the color table 220.

Meanwhile, a leader line may be displayed to facilitate coupling of the reagent pad strip 210 to one region of the colorimetric table 220.

Referring to FIG. 12A, the controller 150 of the terminal 100 may control the display 120 to display the preview image acquired from the camera on the preview image capturing interface 20. Here, the preview image capturing interface 20 may include a guide line 21. The user may adjust the position of the terminal 100 to position the urine test kit in a specific region (guide line), so that the urine test kit may be easily photographed.

According to some embodiments of the present disclosure, the controller 150 may recognize the movement of the preview image obtained from the camera. In this case, the controller 150 may control the display 120 to display the first guide text 22 on the preview image capturing interface 20. For example, the first guide text 22 may be text that may help to capture a preview image, such as “Please shoot in a bright place where no shadow is lost”.

According to some embodiments of the present disclosure, the controller 150 may recognize that the urine test kit is included in the preview image obtained from the camera. In addition, the controller 150 may recognize whether the urine test kit included in the preview image is an appropriate size. In detail, the controller 150 may compare the size of the urine test kit included in the preview image with the size of the guide line 21. In addition, the controller 150 may display the second guide text 23 through the preview image capturing interface 20 when the size of the urine test kit included in the preview image is smaller than the size of the guide line 21. The display 120 may be controlled. For example, the second guide text 23 may be text that helps to capture a preview image such as “Please take a closer picture of the camera”.

Referring to FIG. 12B, as described above, the controller 150 may recognize the size of the urine test kit included in the preview image and compare it with the size of the guide line 21. In addition, when the size of the urine test kit matches the size of the guide line 21, the controller 150 may recognize whether the urine test kit is located in the guide line 21. In addition, the controller 150 may include a preview image photographing interface when the urine test kit included in the preview image matches the size of the guide line 21 and the urine test kit is not located in the guide line 21. The display 120 may be controlled to display the third guide text 24 through the reference numeral 20. For example, the third guide text 24 may be text to help the preview image shooting, such as “Please match the colorimetric outline”.

However, the present invention is not limited to the above-described example, and the first guide text 22, the second guide text 23, and the third guide text 24 may be any text that guides the preview image to be properly captured. Can be.

Referring to FIG. 12C, the controller 150 may control the display 120 to display the plurality of guide cells 25 on the preview image captured through the preview image capturing interface 20. . Therefore, the user can intuitively recognize whether the urine test kit is accurately photographed on the photographed preview image.

In addition, the controller 150 may control the display 120 to display the indicator 26 that receives whether the preview image captured by the preview image capturing interface 20 is correctly captured. For example, one region of the indicator 26 may include text such as "Is the colorimetric chart actually photographed and the white rectangle (guide cell) match?". In addition, the controller 150 may receive an input corresponding to confirmation or cancellation (re-shooting) from the user through the indicator 26.

Operation of controlling the display unit 120 so that the above-described control unit 150 displays the preview image capturing interface 20 and the configuration of the preview image capturing interface 20 will be described in detail as an example to help understand the present disclosure. However, the present disclosure is not limited thereto.

FIG. 13 is a diagram illustrating another example of an interface that may be viewed in a terminal according to some embodiments of the present disclosure.

FIG. 13 illustrates a screening result interface 30 that may be shown to the user after the user captures the preview image.

According to some embodiments of the present disclosure, the controller 150 corresponds to a color of each of the obtained plurality of reagent pad cells using health analysis data mapped to each of the plurality of color information pre-stored in the memory 140. The results of the examination can be generated. However, the present invention is not limited thereto, and the controller 150 may control the communicator 130 to transmit the color information of each of the obtained plurality of reagent pad cells to an external server. In addition, the controller 150 may receive information about a result of the examination from an external server through the communication unit 130.

The controller 150 may control the display unit 120 to display a result of the examination generated by the controller 150 or received from an external server.

Referring to FIG. 13A, the controller 150 of the terminal 100 may control the display 120 to display the examination result interface 30.

In detail, the controller 150 may control the display 120 to display a plurality of check items and a check result graph corresponding to the plurality of check items in the first area 32 of the check result interface 30. have.

For example, the first region 32 of the examination result interface 30 may include a screening item such as glucose, bilirubin, ketone, blood, pH, protein, nitrite, urobilinogen, specific gravity, and leukocyte, and a corresponding screening item. Graphs may be included. Therefore, the user can intuitively check the health state corresponding to the plurality of examination items.

In addition, the controller 150 may control the display unit 120 to display the indicator 31 for confirming detailed information of each of the plurality of examination items in one region of the examination result interface 30.

FIG. 13B illustrates a screen that may be displayed to the user when the user touches the indicator 31 of FIG. 13A.

According to some embodiments of the present disclosure, the controller 150 may control the display 120 to display the plurality of check item indicators in the second area 33 of the check result interface 30. The user may select any one of a plurality of check items and check details of a check item desired by the user.

In detail, the controller 150 may control the display unit 120 to display an indicator corresponding to each examination item in the second area 33 of the examination result interface 30. In addition, the controller 150 may receive a selection input of an indicator corresponding to each examination item. In this case, the controller 150 may control the display 120 to display the health state information corresponding to the selected indicator in the third region 34 of the examination result interface 30.

For example, when the controller 150 receives an input for selecting an indicator for glucose among the plurality of indicators, the controller 150 displays the health state information including detailed information about glucose in the third area 34. 120 can be controlled.

In another example, when the controller 150 receives an input for selecting an indicator for blood among the plurality of indicators, the controller 150 displays the health state information in the third area 34 including information representing the blood test result in detail. The display 120 may be controlled.

Operation of controlling the display unit 120 so that the controller 150 displays the examination result interface 30 and the configuration of the examination result interface 30 are merely exemplary descriptions to help understand the present disclosure. The present disclosure is not limited thereto.

The above-described embodiments may be generally implemented in computer executable instructions that may be executed on one or more computers, and those skilled in the art will appreciate that the present disclosure may be implemented in combination with other program modules and / or as a combination of hardware and software. You will know well.

In general, modules herein include routines, procedures, programs, components, data structures, etc. that perform particular tasks or implement particular abstract data types. In addition, those skilled in the art will appreciate that the methods of the present disclosure may include uniprocessor or multiprocessor computer systems, minicomputers, mainframe computers, as well as personal computers, handheld computing devices, microprocessor-based or programmable consumer electronics, and the like (each of which And other computer system configurations, including one or more associated devices.

Computers in accordance with the present disclosure typically include a variety of computer readable media. Any medium that can be accessed by a computer can be a computer readable medium, which can be volatile and nonvolatile media, transitory and non-transitory media, removable and non-transitory media. Removable media. By way of example, and not limitation, computer readable media may comprise computer readable storage media and computer readable transmission media.

Computer-readable storage media are volatile and nonvolatile media, temporary and non-transitory media, removable and non-removable implemented in any method or technology for storing information such as computer readable instructions, data structures, program modules or other data. Media. Computer-readable storage media include RAM, ROM, EEPROM, flash memory or other memory technology, CD-ROM, digital video disk or other optical disk storage device, magnetic cassette, magnetic tape, magnetic disk storage device or other magnetic storage. It includes, but is not limited to, a device or any other medium that can be accessed by a computer and used to store desired information.

Computer readable transmission media typically embody computer readable instructions, data structures, program modules or other data on modulated data signals, such as carrier waves or other transport mechanisms, and the like. Includes all information delivery media. The term modulated data signal refers to a signal that has one or more of its characteristics set or changed to encode information in the signal. By way of example, and not limitation, computer readable transmission media includes wired media such as a wired network or direct-wired connection, and wireless media such as acoustic, RF, infrared, or other wireless media. Combinations of any of the above should also be included within the scope of computer readable transmission media.

One of ordinary skill in the art of the disclosure will appreciate that the various illustrative logical blocks, modules, processors, means, circuits and algorithm steps described in connection with the embodiments disclosed herein may be implemented in electronic hardware, It will be appreciated that for purposes of the present invention, various forms of program or design code, or combinations thereof, may be implemented. To clearly illustrate this interchangeability of hardware and software, various illustrative components, blocks, modules, circuits, and steps have been described above generally in terms of their functionality. Whether such functionality is implemented as hardware or software depends on the particular application and design constraints imposed on the overall system. One skilled in the art of the present disclosure may implement the described functionality in various ways for each particular application, but such implementation decisions should not be interpreted as causing a departure from the scope of the present disclosure.

The various embodiments presented herein may be embodied in a method, apparatus, or article of manufacture using standard programming and / or engineering techniques. The term "article of manufacture" includes a computer program, carrier, or media accessible from any computer-readable device. For example, computer-readable storage media may include magnetic storage devices (eg, hard disks, floppy disks, magnetic strips, etc.), optical disks (eg, CDs, DVDs, etc.), smart cards, and flashes. Memory devices (eg, EEPROM, cards, sticks, key drives, etc.), but are not limited to these. The term “machine-readable medium” includes, but is not limited to, a wireless channel and various other media capable of storing, holding, and / or delivering instruction (s) and / or data.

It is to be understood that the specific order or hierarchy of steps in the processes presented is an example of exemplary approaches. Based upon design priorities, it is understood that the specific order or hierarchy of steps in the processes may be rearranged within the scope of the present disclosure.

The description of the presented embodiments is provided to enable any person skilled in the art to make or use the present disclosure. Various modifications to these embodiments will be apparent to those skilled in the art, and the generic principles defined herein may be applied to other embodiments without departing from the scope of the present disclosure. Thus, the present disclosure should not be limited to the embodiments set forth herein but should be construed in the broadest scope consistent with the principles and novel features set forth herein.

As described above, related contents have been described in the best mode for carrying out the invention.

The present disclosure relates to a computer program and a terminal stored in a computer readable storage medium, and more specifically, to a program and a terminal stored in a computer readable storage medium for providing a urine test using a colorimetric table.

Claims

A computer program stored in a computer readable storage medium,

The computer program includes instructions for causing a computer to perform the following operations, the operations:

Obtaining a preview image captured by the camera;

Recognizing a urine test kit within the preview image, the urine test kit comprising a colorimetric table and a reagent pad strip;

Obtaining a shape of each of the plurality of color table cells included in the color table;

Recognizing the number of cells corresponding to a predetermined shape among the plurality of color table cells;

Recognizing positions of each of the plurality of non-colored cells in the preview image when the number of cells corresponding to the preset shape is equal to or larger than a preset number; And

Acquiring color information of each of the plurality of reagent pad cells included in the reagent pad strip using the color palette when the position of each of the plurality of color table cells corresponds to a preset position;

Including,

Computer program stored on a computer readable storage medium.
The method of claim 1,

Generating a examination result corresponding to the color information by using health analysis data mapped to each of a plurality of colors previously stored in a memory; And

Displaying the result of the examination;

Including more;

Computer program stored on a computer readable storage medium.
The method of claim 1,

Transmitting the color information to an external server;

Receiving information on a diagnosis result corresponding to the color information from the external server; And

Displaying information about the examination result;

Including more;

Computer program stored on a computer readable storage medium.
The method of claim 1,

Acquiring the shape of each of the plurality of colorimetric cells included in the colorimetric table,

Recognizing an outline of each of the plurality of colorimetric cells; And

Acquiring a shape of each of the plurality of colorimetric cells based on an outline of each of the plurality of colorimetric cells;

Including,

Computer program stored on a computer readable storage medium.
The method of claim 1,

Recognizing the number of cells corresponding to a predetermined shape among the plurality of color table cells may include:

Recognizing a first horizontal length and a first vertical length of each of the plurality of colorimetric cells;

Recognizing a second horizontal length and a second vertical length of the urine test kit included in the preview image; And

Recognizing the number of cells that match the preset shape using the first horizontal length, the second horizontal length, the first vertical length, and the second vertical length;

Including,

Computer program stored on a computer readable storage medium.
The method of claim 5, wherein

The cell matching the preset shape is

A ratio value between the first width and the first length corresponds to a first ratio value previously stored in a memory, and the first width is multiplied by the second ratio and a second ratio value previously stored in the memory. The cell corresponding to the value,

Computer program stored on a computer readable storage medium.
The method of claim 5, wherein

The cell matching the preset shape is

A ratio value between the first horizontal length and the first vertical length corresponds to a first ratio value pre-stored in a memory, wherein the first vertical length is multiplied by the second vertical length and a third ratio value pre-stored in the memory The cell corresponding to the value,

Computer program stored on a computer readable storage medium.
The method of claim 5, wherein

The cell matching the preset shape is

A ratio value between the first width and the first length corresponds to a first ratio value previously stored in a memory, and the first width is multiplied by the second ratio and a second ratio value previously stored in the memory. Corresponding to a value, wherein the first vertical length is a cell corresponding to a value obtained by multiplying the second vertical length by a third ratio value pre-stored in the memory,

Computer program stored on a computer readable storage medium.
The method of claim 1,

Recognizing the position of each of the plurality of colorimetric cells in the preview image,

Recognizing each of a first reference cell and a second reference cell of the plurality of colorimetric cells; And

Based on the position of the first reference cell within the preview image, the position of the second reference cell within the preview image, and position information of colorimetric cells previously stored in memory, the plurality of colorimetric tables within the preview image. Recognizing a location of each of the cells;

Including,

Computer program stored on a computer readable storage medium.
The method of claim 1,

Acquiring color information of each of the plurality of reagent pad cells included in the reagent pad strip using the colorimetric table,

Recognizing a location of the reagent pad strip based on colorimetric information previously stored in a memory; And

Recognizing color information of each of the plurality of reagent pad cells when a preset second condition is satisfied;

Including,

Computer program stored on a computer readable storage medium.
The method of claim 10,

The preset second condition is,

A first imaginary line connecting the first colorimetric cell included in the colorimetric table and a second colorimetric cell positioned below the first colorimetric cell, and a first reagent pad cell and a second included in the reagent pad strip. The first reagent on the third virtual line connecting the second virtual line parallel to the reagent pad cells and connecting the third colorimetric cell located to the side of the first colorimetric cell and the first colorimetric cell. Satisfied when the pad cell is located,

Computer program stored on a computer readable storage medium.
The method of claim 1,

Acquiring color information of each of the plurality of reagent pad cells included in the reagent pad strip using the colorimetric table,

Color-analyzing the colors of each of the plurality of reagent pad cells with the plurality of colorimetric cells to obtain the color information of each of the plurality of reagent pad cells;

Including,

Computer program stored on a computer readable storage medium.
The method of claim 12,

Colorimetric analysis of the color information of each of the plurality of reagent pad cells with the plurality of colorimetric cells, to obtain the color information of each of the plurality of reagent pad cells,

Generating a colorimetric analysis model; And

Obtaining the color information of each of the plurality of reagent pad cells by calculating a color of each of the plurality of colorimetric cells and the plurality of reagent pad cells using the colorimetric analysis model;

Including,

Computer program stored on a computer readable storage medium.
The method of claim 13,

The operation of generating the colorimetric analysis model,

Generating learning data by labeling learning color data of the plurality of colorimetric cells corresponding to input of training data and learning steady state color data of the plurality of colorimetric cells previously stored in a memory; And

Training the colorimetric analysis model including one or more network functions using a training data set including the training data to generate the colorimetric analysis model;

Including,

Computer program stored on a computer readable storage medium.
The method of claim 14,

Learning the colorimetric analysis model including one or more network functions by using the training data set including the training data to generate the colorimetric analysis model,

Inputting the training color data into an input node included in an input layer of at least one network function of the colorimetric analysis model;

Deriving an error by comparing the learning color data with the labeled learning steady state color data and an output of the colorimetric analysis model; And

The error is propagated from the output layer of the one or more network functions of the colorimetric analysis model through the one or more hidden layers to the input layer so that weights set in the link connecting each of the input node, the output layer and the one or more hidden layers are obtained. Updating;

Including,

Computer program stored on a computer readable storage medium.
The method of claim 13,

The operation of acquiring the color information of each of the plurality of reagent pad cells by calculating the color of each of the plurality of colorimetric cells and the plurality of reagent pad cells using the colorimetric analysis model may include:

Combining at least two or more color models of the plurality of color models to generate a plurality of different color decision trees; And

Acquiring a plurality of color information corresponding to each of the plurality of reagent pad cells using each of the plurality of color determination trees;

Including,

Computer program stored on a computer readable storage medium.
A terminal for providing a urine test using a colorimetric table,

A camera unit for obtaining a preview image; And

A control unit obtaining color information of each of a plurality of reagent pad cells included in a reagent pad strip based on the preview image;

Including,

The control unit,

Recognize in the preview image a urine test kit, the urine test kit including a colorimetric and reagent pad strips,

Obtaining the shape of each of the plurality of color table cells included in the color table,

Recognize the number of cells corresponding to a preset shape among the plurality of colorimetric cells;

When the number of cells corresponding to the preset shape is equal to or larger than the preset number, the positions of the plurality of colorimetric cells in the preview image are recognized.

When the position of each of the plurality of color table cells corresponds to a preset position, obtaining color information of each of the plurality of reagent pad cells included in the reagent pad strip using the color table.

A terminal providing a urine test using a colorimetric table.