KR20230054968A - Image Based Scalp Analysis and Prescription Method, System, Management Server and Recording Medium Using Big Data and Machine Learning Engine - Google Patents

Abstract

According to the present invention, provided is an image-based scalp analysis and prescription method, which includes: a scalp image acquisition step of acquiring a scalp image by photographing the scalp of a user through a scalp scanner; a scalp image transmission step of transmitting the scalp image to a management server through the scalp scanner or a user terminal; an analysis step of calculating analysis information on the scalp image by checking and analyzing the condition of the scalp and hair through the scalp image in the management server; and a prescription step of recommending prescription information for a product or prescription according to the scalp and hair of the user condition based on the analysis information.

Description

Image Based Scalp Analysis and Prescription Method, System, Management Server and Recording Medium Using Big Data and Machine Learning Engine}

The present invention relates to an image-based scalp analysis method, system, management server, and recording medium, and more particularly, by confirming and analyzing scalp image information obtained through an image scanner through big data and a machine learning engine to provide users with a By delivering more accurate and diverse information on scalp and hair, users can clearly check their current scalp and hair condition just by sending a scalp image, and the management server provides information on all ingredients, scalp and hair of the product. Image-based scalp analysis and prescription method that can be used to facilitate the product or prescription suitable for the user's scalp and hair condition by recommending a prescription suitable for the user's scalp and hair condition by storing medical and pharmaceutical information on the scalp and hair as big data , system, management server and recording media.

Recently, hair loss and scalp-related diseases are increasing due to stress or frequent drinking and smoking. In order to manage the scalp or hair, most people visit related establishments such as beauty salons, cosmetic stores, or dermatologists to receive treatment from specialists or receive prescriptions for medicine.

However, even for those who are interested in hair loss or hair condition, it is practically not easy to visit a beauty salon or dermatologist regularly to receive care. In addition, recently, as interest in appearance increases regardless of gender and age, various books or specialized Internet sites related to hair or scalp are increasing.

However, even if you refer to specialized books or Internet sites, it is preferable to directly check your current hair and scalp conditions in order to manage your hair or scalp yourself. However, there is a problem in that it is not easy to directly examine one's own hair or scalp. In addition, even if one's own hair or scalp is checked through a mirror or the like, it is difficult to clearly check the degree of damage or problem with the naked eye.

Accordingly, there is a demand for a technology that allows the person to easily and clearly check the state of their scalp.

KR 1169882 10

The present invention is to solve the conventional problem, by confirming and analyzing scalp image information acquired through an image scanner through big data and machine learning engines, providing users with more accurate and diverse information about their scalp and hair. Users can clearly check their current scalp and hair condition just by sending the scalp image, and the management server stores all ingredients of the product and medical and pharmaceutical information on the scalp and hair as big data. It provides an image-based scalp analysis and prescription method, system, management server, and recording medium that can be used to facilitate the user's product or prescription suitable for the user's scalp and hair condition by recommending a prescription suitable for the user's scalp and hair condition. There is a purpose.

The object of the present invention is not limited thereto, and other objects not mentioned will be clearly understood by those skilled in the art from the following description.

An image-based scalp analysis and prescription method for achieving the object of the present invention as described above includes a scalp image acquisition step of acquiring a scalp image by photographing the user's scalp through a scalp scanner, and the scalp image through the scalp scanner or user terminal. Scalp image transfer step of delivering to the management server, analysis step of calculating analysis information on the scalp image by confirming and analyzing the condition of the scalp and hair through the scalp image in the management server, and based on the analysis information A prescription step of recommending prescription information for products or prescriptions according to the user's scalp and hair conditions.

In this case, in the analyzing step, the scalp and hair conditions of the user may be confirmed from the scalp image through a machine learning engine.

Also, the machine learning engine may learn through at least one of pose tracking and line tracking based on labeling data.

In addition, the analysis step may calculate at least one index of the number of hairs, average hair thickness, average number of hairs per one hair root, scalp oil content, and scalp inflammation from the scalp image.

In addition, the analysis step may be performed by comparing with the scalp image through a program based on big data pre-stored in the management server.

In addition, a questionnaire step may be further included between the analysis step and the prescription step for a clearer prescription.

In addition, the medical examination step may include an analysis information transmission step in which the management server transmits the analysis information to the user terminal, a medical examination form preparation step in which a medical examination form is prepared based on the analysis information and transmitted to the management server, and in the management server A diagnosis step of comprehensively diagnosing the condition of the scalp with reference to the analysis information and questionnaire and calculating a diagnosis result, and the prescription step may recommend a product or prescription based on the comprehensive diagnosis result calculated in the diagnosis step. .

In addition, the medical questionnaire may include at least one of a questionnaire including a question provided by the management server and text input through the user terminal together with the analysis information in the analysis information transmission step.

In addition, the management server may analyze the user's troubled area, troubled content, positives and negatives included in the text through deep learning-based natural language processing.

In addition, in the diagnosis step, the management server may determine a weak part of the user and a vulnerable state for each weak part based on the analysis information and the medical examination table.

In addition, the prescribing step may recommend a product or a treatment plan according to the diagnosis result based on all component information, medical information, or pharmaceutical information of the product collected by the management server.

The method may further include a prescription transmission step of transmitting the prescription information calculated in the prescription step to the user terminal.

As another category, the image-based scalp analysis and prescription system according to the present invention is a system for performing the above method, a scalp scanner for acquiring scalp image information by photographing the user's scalp, and the scalp image from the scalp scanner. The information is received, stored, and transmitted to the outside, the user terminal receiving the external information and the scalp image information transmitted from the user terminal are stored, and the user's scalp and hair condition is checked and analyzed through the previously entered program and a management server that calculates and prescribes the severity of the user's scalp and hair condition and transmits the calculation result and the prescription result to the user terminal.

As another category, the management server used in the above-described method and system is a receiving unit that receives information transmitted from the scalp scanner and the user terminal, and stores the scalp image received through the receiving unit using big data and a machine learning engine , It includes an analysis unit that confirms, analyzes, diagnoses, and prescribes, and a transmission unit that transmits information that has been analyzed by the analysis unit to the outside.

As another category, a recording medium used in the aforementioned management server is input to the aforementioned management server, and a program for confirming and analyzing the scalp image is recorded.

The image-based scalp analysis and prescription method, system, management server, and recording medium of the present invention have the following effects.

First, a user can obtain detailed analysis information on his or her scalp and hair only with images taken through a scalp scanner.

Second, the user can obtain information on the prevention and treatment of hair loss by obtaining information such as the condition of the user's scalp and hair as well as the condition of hair loss through detailed analysis.

Third, the management server can provide more detailed and accurate information through scalp image information transmitted by users through big data and machine learning engines.

Fourth, by setting various criteria such as age group and gender through big data, and providing information such as percentage of the corresponding indicator based on average and standard deviation for each criterion, users can clearly compare information such as scalp and hair damage. And there is an effect that can be confirmed.

Fifth, as more information is stored in big data through self-learning through a machine learning engine, the accuracy of checking image information and calculating state information gradually improves, and accordingly, the user's reliability is also improved.

Sixth, the analysis result is transmitted to the user terminal so that the user can quickly and easily check the analysis result.

Seventh, the management server confirms the user's scalp and hair condition by checking not only the medical questionnaire with the prescribed questions, but also the text that the user directly inputs to diagnose the user's scalp and hair condition. .

Eighth, as the management server recommends products or prescriptions according to the user's scalp and hair condition, the user can easily check products and medicines according to the user's scalp and hair condition without periodically visiting the hospital. .

Ninth, the management server has an effect of maximizing user convenience by delivering prescription information as well as product retailers, lowest price information, pharmacy and hospital information, etc. to the user.

The effects of the present invention are not limited to the above-mentioned effects, and other effects not mentioned will be clearly understood by those skilled in the art from the description of the claims.

The following drawings attached to this specification illustrate preferred embodiments of the present invention, and together with the detailed description of the invention serve to further understand the technical idea of the present invention, the present invention is limited only to those described in the drawings. and should not be interpreted.
1 is an image representing scalp image information acquired by a scalp scanner;
2 is an image for performing a data labeling operation on scalp image information in an analysis unit of a server according to the present invention;
3 is a pose tracking sample image used in the analysis unit of the server according to the present invention;
4 is a line tracking sample image used in the analysis unit of the server according to the present invention;
5 is a sample image in which the oil state is subdivided in the analysis unit of the server according to the present invention;
6 is a sample image in which the degree of inflammation is subdivided in the analysis unit of the server according to the present invention;
7 is a schematic configuration diagram of an image-based scalp analysis and prescription system according to the present invention;
8 is a flowchart sequentially illustrating an image-based scalp analysis method according to the present invention;
9 is an image showing an analysis result transmission form transmitted from a management server to a user terminal according to an embodiment of the present invention;
10 is an image showing a medical questionnaire and a check state of the medical questionnaire according to an embodiment of the present invention; and
11 is an image showing a state in which a medical questionnaire according to an embodiment of the present invention is transmitted as text.

Advantages and features of the present invention and methods of achieving them will become clear with reference to the detailed description of the following embodiments taken in conjunction with the accompanying drawings. However, the present invention is not limited to the embodiments disclosed below, but may be implemented in various different forms, and only these embodiments make the disclosure of the present invention complete, and those skilled in the art to which the present invention belongs It is provided to fully inform the scope of the present invention, the present invention is defined only by the scope of the claims.

Terms used herein are for describing the embodiments and are not intended to limit the present invention. In this specification, the singular form also includes the plural form unless otherwise specified in the phrase. As used herein, "comprises" and/or "comprising" does not exclude the presence or addition of one or more other elements other than the recited elements. Like reference numerals throughout the specification refer to like elements, and “and/or” includes each and every combination of one or more of the recited elements. Although "first", "second", etc. are used to describe various components, these components are not limited by these terms, of course. These terms are only used to distinguish one component from another. Therefore, it goes without saying that the first component mentioned below may also be the second component within the technical spirit of the present invention.

Unless otherwise defined, all terms (including technical and scientific terms) used in this specification may be used with meanings commonly understood by those skilled in the art to which the present invention belongs. In addition, terms defined in commonly used dictionaries are not interpreted ideally or excessively unless explicitly specifically defined.

Hereinafter, preferred embodiments of the present invention will be described in detail with reference to the accompanying drawings.

Configuration of image-based scalp analysis and prescription management server

The management server 300 receives a scalp image transmitted by a user, identifies and analyzes the scalp image. This management server 300 is largely composed of a receiving unit 310, an analyzing unit 320 and a transmitting unit 330.

1 is an image showing scalp image information acquired by a scalp scanner. The receiving unit 310 is a device that receives user information, such as scalp image information obtained through the scalp scanner 100, a medical examination form, and a user's text, as shown in FIG. 1 transmitted from the outside. The receiving unit 310 may use any device as long as it can easily receive data such as scalp image information transmitted from the outside and transfer the data to the analysis unit 320 .

The analyzer 320 is a device that analyzes the user information as shown in FIG. 1 received by the receiver 310 to analyze the user's scalp and hair condition, and determines prescription contents according to the analysis result. The analyzer 320 may use any device as long as it can quickly and accurately analyze the state of the scalp and hair by analyzing the scalp image information received through the previously input program. In one embodiment, a program used in the analysis unit 320 may analyze, diagnose, and prescribe a user's scalp condition through scalp image information by utilizing big data and a machine learning engine. A more detailed description of this is as follows.

The big data used in the analysis unit 320 may include a variety of information capable of analyzing, diagnosing, and prescribing based on the user's scalp image information. As such, various information stored in big data may include hair and scalp related information, product information, and prescription information. Here, the hair and scalp related information may include sample data input by various users using the management server or a manager of the management server according to the present invention. In addition, product information includes product information such as shampoo, conditioner, treatment, and ampoule sold on the market, and information such as all ingredients or efficacy of the product, and prescription information may include medical or pharmaceutical prescription information. And the information included in such big data can be continuously accumulated.

In addition, big data can also be stored based on these key indicators in order to classify information provided to users by core indicators so that users can easily check scalp and hair related information. At this time, the key indicators may include the number of hairs in a certain area, average hair thickness, average number of hairs per one hair root, scalp oiliness, scalp inflammation, etc., and by age group, the average value and standard deviation of key indicators for each age group, etc. of information may be included.

2 is an image in which data labeling is performed on scalp image information in the analysis unit of the server according to the present invention, FIG. 3 is a pose tracking sample image used in the analysis unit of the server according to the present invention, and FIG. 4 is the present invention. This is a line tracking sample image used in the analysis unit of the server according to In addition, the analysis unit 320 utilizes a machine learning engine based on big data. Describing this in more detail, as shown in FIG. 2, the analysis unit 320 includes labeling data indicating the location of each hair root and hair included in the scalp image information transmitted through the receiver 310. Based on ), at least one machine learning engine of pose tracking shown in FIG. 3 and line tracking shown in FIG. 4 can be designed and trained. As such, the analysis unit 320 can improve analysis accuracy by accumulating learning data in big data using a machine learning engine, and comparing the accumulated data with the user's scalp image information to determine the hair of each image. The number of hairs, the average thickness of hairs, and the average number of hairs occurring per hair can be derived.

5 is a sample image in which the oil state is segmented in the analysis unit of the server according to the present invention, and FIG. 6 is a sample image in which the degree of inflammation is segmented in the analysis unit of the server according to the present invention. In addition, the analysis unit 320 labels a large amount of images to design an image segmentation machine learning engine (Image Segmentation ML Engine) to classify scalp oil and inflammation into detailed stages, as shown in FIGS. 5 to 14 can In the present invention, the oil content and the inflammation degree are shown and described with a focus on subdividing into five stages, but this is only an example and it is obvious that each subdivision can be classified into various stages.

As described above, based on the big data learned and accumulated using the machine learning engine, the analyzer 320 checks the scalp image information received through the receiver 310 and compares it with the big data to determine the user's value for each key indicator. It can analyze, diagnose and prescribe scalp conditions. For example, based on scalp image information and the average and standard deviation of the same age group on tens of thousands of pieces of big data stored in the management server 300, the percentage is calculated for each key index to analyze the user's scalp and hair condition and hair loss severity. And, it is possible to provide a prescription corresponding to the user's scalp and hair through detailed diagnosis based on the medical questionnaire provided therewith.

The transmission unit 330 is a device that transmits the confirmation result, diagnosis result, prescription result, etc. analyzed by the analysis unit 320 to the user. The transmission unit 330 may use any device as long as it can deliver the results of the analysis unit 320 to the user in various ways.

The above-mentioned method of using the management server will be described in more detail in 'image-based scalp analysis and prescription method' to be described later.

Image-based scalp analysis and prescription program

A program that is input to the analysis unit 320 of the above-described management server 300 and performs an 'image-based scalp analysis and prescription method' described later is recorded on a recording medium readable by devices such as computers, and devices such as computers It is possible to execute the above-described functions by being executed by.

In this way, in order to execute the image-based scalp analysis method according to an embodiment of the present invention implemented as a program by reading a program recorded on a recording medium in a device such as a computer, the above-described program is a computer processor (CPU) It may include code coded in a computer language such as executable C, C++, JAVA, or machine language.

These codes may include functional codes related to functions defining the above-described functions, and may include control codes related to execution procedures required for a processor of a device such as a computer to execute the above-described functions according to a predetermined procedure. may be

In addition, these codes include code related to memory reference for additional information or media required for the processor of a device such as a computer to execute the above-described functions from which location (address address) of the internal or external memory of the device such as a computer should be referenced. can include more.

In addition, when the processor of a device such as a computer needs to communicate with any other remote device or server in order to execute the above-mentioned functions, the code is such that the processor of the device such as a computer communicates with the computer's communication module (e.g. wired and/or a wireless communication module) may further include communication-related codes such as how to communicate with any other remote computer or server, and what information or media should be transmitted/received during communication.

In addition, the functional program for implementing the present invention and related codes and code segments are developed by programmers in the technical field to which the present invention belongs, taking into account the system environment of a device such as a computer that reads a recording medium and executes the program. It can be easily inferred or changed.

In addition, the recording medium on which the above-described program is recorded is distributed to computer systems connected through a network, so that readable codes can be stored and executed in a distributed manner. In this case, any one or more of the plurality of distributed devices may execute some of the aforementioned functions, transmit the result of execution to one or more of the other distributed devices, and the device that receives the result. It can also execute some of the aforementioned functions and provide the results to other decentralized devices as well.

The above-described recording medium may be, for example, ROM, RAM, CD-ROM, magnetic tape, floppy disk, optical media storage device, and the like.

In addition, a recording medium recording an application, which is a program for executing the image-based scalp analysis and prescription method according to an embodiment of the present invention, is included in an application providing server including an application store server, an application or a web server related to the corresponding service, and the like. It may be a stored storage medium or the like, or the application providing server itself, or a terminal device such as another computer, a mobile phone, etc., in which a program is recorded, or its storage medium.

Zyi, which can read a recording medium on which an application, which is a program for executing an image-based scalp analysis and prescription method according to an embodiment of the present invention, is recorded is not only PCs such as general desktops and laptops, but also smartphones, tablet PCs, PDAs and It may include mobile terminal devices such as mobile communication terminal devices, and should be construed as not only this, but also all devices capable of computing.

If a computer capable of reading a recording medium on which an application, which is a program for executing the advertisement blocking method according to an embodiment of the present invention, is recorded, a mobile device such as a smart phone, tablet PC, PDA (Personal Digital Assistants) and mobile communication terminal device In the case of a terminal device, the mobile terminal device can download and install the corresponding application from an application providing server including an application store server, web server, etc. In some cases, after being downloaded from the application providing server to a general PC, through a synchronization program. It may be installed in a mobile terminal device.

Configuration of image-based scalp analysis and prescription system

7 is a schematic configuration diagram of an image-based scalp analysis and prescription system according to the present invention. As shown in FIG. 7 , the image-based scalp analysis system according to the present invention may include a scalp scanner 100 , a user terminal 200 and a management server 300 .

The scalp scanner 100 is a device that acquires image information of the scalp and hair by photographing the user's scalp. The scalp scanner 100 may use any device as long as it can obtain scalp image information by capturing an image of the user's scalp. However, preferably, a device capable of storing the obtained scalp image information or directly transmitting it to the outside is used, or it is connected to the user terminal 200 such as a user mobile phone or computer by wire or wireless to transmit the acquired scalp image information. It is better to use a device that can. If the scalp scanner 100 includes a function capable of transmitting and receiving, it does not matter if the user terminal 200 is not provided. However, it is preferable that the user terminal 200 is included in order to receive and easily check result values described later from the management server 300 and to continuously communicate with the management server 300 for medical examination.

In the user terminal 200, the user checks and stores an image captured by the scalp scanner 100 in real time, transmits the stored scalp image information to the management server 300, and receives result data from the management server 300. It is a device for exchanging information between the back scalp scanner 100 and the management server 300 . The user terminal 200 may be a variety of devices, such as a user's mobile phone or tablet PC, as well as a general desktop or laptop computer. At this time, a program or application for smooth information transmission and reception with the management server 300 may be installed in the user terminal 200 . The user terminal 200 may transmit and receive data to and from the management server 300 using wireless communication, etc., and such data transmission and reception may be connected to the management server 300 through an Internet function or application of the user terminal 200. there is. As such, a method for connecting with the management server 300 may be achieved through various methods, and these methods are not particularly limited.

The management server 300 is a device that checks and analyzes scalp image information transmitted from the scalp scanner 100 or the user terminal 200 through the aforementioned recording medium, and transmits the analysis result to the user terminal 200.

As described above, the management server 300 may include a receiving unit 310, an analyzing unit 320, and a transmitting unit 330.

Image-based scalp analysis and prescription method

An image-based scalp analysis and prescription method for analyzing and prescribing a user's scalp by utilizing a management server in which a recording medium having the above configuration is stored will be described in more detail with reference to the drawings.

8 is a flowchart sequentially illustrating an image-based scalp analysis and prescription method according to the present invention. First, as shown in FIG. 8, the user obtains a scalp image by photographing his or her scalp through the scalp scanner 100 (S100). At this time, the scalp scanner 100 may use any device capable of acquiring a scalp image by photographing the user's scalp. However, it is preferable to use a device capable of transmitting information by being connected to the user terminal 200 such as a smartphone or a computer so that the scalp state photographed by the user can be checked and stored in real time.

Next, scalp image information obtained through the scalp scanner 100 is transmitted to the management server 300 (S200). If the scalp scanner 100 has a built-in transmission device for information transmission, the scalp image information is transmitted directly from the scalp scanner 100 to the management server 300. Otherwise, the user's mobile phone, computer, etc. Acquired scalp image information may be transmitted to the management server 300 through the user terminal 200 of the user terminal 200 . When the scalp image information is transmitted in this way, the management server 300 receives the transmission through the receiver 310 . At this time, the user can transmit personal information such as the user's name or ID and the product name of the scalp scanner 100 used for scalp acquisition for easy and continuous management. In this way, as personal information is input, the user's scalp and hair state changes according to repeated use are stored in the management server, and through this, the user can easily check the change in the state of the user's hair and scalp. In addition, since the area to be photographed may be different depending on the product of the scalp scanner 100, when the product information of the scalp scanner 100 is transmitted together, the reference area can be calculated more clearly, so the management server 300 A more accurate analysis can be performed.

Next, the management server 300 checks and analyzes the user's scalp and hair conditions based on the transmitted scalp image information by utilizing the aforementioned big data and machine learning engine to calculate analysis information (S300). The management server 300 checks the user's scalp and hair conditions included in the transmitted scalp image information by utilizing the aforementioned big data and machine learning engine (S300). As in the above-described 'configuration of the image-based scalp analysis management server 300', the analysis unit 320 of the management server 300 utilizes a big data-based machine learning engine to perform pose tracking, line tracking, and image segmentation learning The engine extracts key indicators of the user's scalp and hair condition through scalp image information. That is, the number of hairs, the average thickness of hair, and the average number of hairs occurring per hair are extracted from the scalp image information transmitted through pose tracking and line tracking, and the scalp image is compared with big data to determine the user's scalp oil content and Assess the degree of inflammation.

In addition, the analysis unit 320 compares the user's hair condition with comparison data stored in the management server 300 to calculate the severity of the user's hair and scalp condition (S400). At this time, the comparison data stored in the management server 300 is big data collected through data learning, and such big data includes at least one of the number of hairs, average hair thickness, average number of hairs per one hair root, scalp oil content, and scalp inflammation. It includes any one key indicator, and each key indicator can include average and standard deviation data by age group for more accurate comparison. Accordingly, it is possible to perform accurate comparison according to the user's age group, and depending on the usage mode, all information and comparisons are performed regardless of the user's age group, or the severity of the user's hair and scalp is calculated by setting criteria other than age. It is self-evident that it can be done. As a result of this calculation, the number of hairs in the reference area, the average thickness of hair, and the average number of hairs per hair root are derived, and the scalp oil content and scalp inflammation are classified according to the steps of the preset program, which corresponds to the user's scalp. steps can be calculated. In addition to these methods, any method may be used as long as the user can easily check the user's scalp and hair conditions based on the scalp image information transmitted from the user.

Next, based on the analysis information analyzed through the analysis step (S300), the user's scalp and hair care habits, the user's concerns or questions are additionally collected, and a questionnaire for more accurate diagnosis and prescription is performed ( S400). This paperweight process (S400) will be described in more detail as follows.

9 is an image showing an analysis result transmission form transmitted from a management server to a user terminal according to an embodiment of the present invention. In order to perform the questionnaire, the management server 300 transmits the analysis information analyzed through the analysis step (S300) to the user terminal 200 (S410). At this time, the analysis information may be delivered to the user in various forms by a program pre-entered into the management server 300 so that the user can easily check it. Here, the transmission form may include various formats such as text, numbers, graphs, and images. In one embodiment, the result transmitted to the user terminal 200 may be delivered in the form of a report including various information, as shown in FIG. 9 . This format is only according to one embodiment, and it is obvious that a specific key indicator may be displayed in more detail using various formats, only a few key indicators may be displayed, or more core indicators may be set and displayed. At this time, the management server 300 may transmit a medical questionnaire containing questions such as the user's scalp and hair condition and concerns to the user terminal 200 together with analysis information. Depending on the usage mode, the medical questionnaire may be directly input by the user without a separate example sentence, and in this case, the medical questionnaire may not be transmitted.

10 is an image showing a medical examination according to an embodiment of the present invention and a checked state of the medical examination, and FIG. 11 is an image showing a state in which the medical examination according to an embodiment of the present invention is transmitted as text. Next, the user checks the condition of the user's scalp and hair through the analysis information transmitted through the user terminal 200, prepares a questionnaire based on this, and transmits it to the management server 300 (S420). As shown in FIG. 10, the questionnaire sent from the management server 300 together with the analysis information is checked for programs or applications installed in the user terminal 200 to determine the user's usual scalp and hair care habits and questions. You can fill out a medical questionnaire by checking information such as matters, products used, and medications taken. In addition, depending on the usage mode, a separate medical questionnaire is not transmitted from the management server 300, and the user may directly input text or images using a counseling messenger function included in a program or application. Of course, the medical questionnaire and the user's direct input may be performed simultaneously. Accordingly, the medical questionnaire described in the present invention may be used as a meaning including both a questionnaire including a question provided by the management server 300 and text or characters directly input by a user.

Next, the management server 300 comprehensively analyzes and diagnoses the user's scalp and hair condition by referring to the analysis information analyzed in the analysis step (S300) and the questionnaire transmitted in the questionnaire preparation step (S420) to calculate the diagnosis result. Do (S430). At this time, as shown in FIG. 10 , the management server 300 may extract items checked in the questionnaire of the medical questionnaire or analyze the text to confirm the user's management habits, concerns, questions, and the like. If the questionnaire is input as text, in one embodiment, the management server 300 analyzes the user's troubled area, the content of the trouble, and positive or negative expressions included in the text through deep learning-based natural language processing. . This is only an example, and any method or program that can clearly analyze the contents through the medical questionnaire may be used. As such, the management server 300 can diagnose the user's weak scalp and hair and vulnerable conditions for each vulnerable part in more detail and accurately through the analysis information and the questionnaire. At this time, the weak parts and vulnerable states can be ranked in consideration of the severity, etc., and the diagnosis result is calculated based on the parts and conditions with high severity.

Next, the management server 300 recommends products or prescription information according to the condition of the user's scalp and hair according to the diagnosis result of the diagnosis step (S430) (S500). As described above, the management server 300 includes not only big data on scalp and hair images, but also various product information such as product type and all ingredients, and prescription information on medical prescriptions and pharmaceutical prescriptions. Prescription results suitable for the results can be easily calculated. This prescription information mainly selects product information based on all ingredients, effects, and efficacy information of products such as shampoo, conditioner, treatment, and ampoule sold on the market, and depending on the severity, medical and pharmaceutical prescriptions in addition to product use are selected. If deemed necessary, prescribing information is selected. In addition, product and prescription information may further include product sales sites, product lowest price information, hospital information, and the like, thereby maximizing user convenience.

Finally, the prescription information calculated in the prescription step (S500) is transmitted from the management server 300 to the user terminal 200 (S600). Depending on the usage mode, the user may connect to the management server 300 to check prescription information, but it is preferable to transmit the prescription information to the user terminal 200 in order to quickly deliver information and maximize user convenience. Using the prescription information transmitted in this way, the user can purchase a product suitable for the condition of the user's scalp and hair, or, if necessary, visit a pharmacy or hospital to receive pharmaceutical or medical treatment. At this time, the user may separately search for a vendor for product purchase, but user convenience may be maximized by utilizing recommended vendors or sales site information transmitted through the big data of the management server 300 .

As described above, those skilled in the art to which the present invention pertains will understand that the present invention can be embodied in other specific forms without changing the technical spirit or essential characteristics thereof. Therefore, the above-described embodiments should be understood as illustrative in all respects and not limiting. The scope of the present invention is indicated by the following claims rather than the detailed description, and all changes or modifications derived from the meaning and scope of the claims and equivalent concepts should be construed as being included in the scope of the present invention.

10: image-based scalp analysis system
100: scalp scanner
200: user terminal
300: management server
310: receiver
320: analysis unit
330: transmitter

Claims (15)

A scalp image acquisition step of acquiring a scalp image by photographing a user's scalp through a scalp scanner;
a scalp image transfer step of transferring the scalp image to a management server through the scalp scanner or user terminal;
An analysis step of calculating analysis information on the scalp image by confirming and analyzing the state of the scalp and hair through the scalp image in the management server; and
a prescription step of recommending prescription information for products or prescriptions according to conditions of the scalp and hair of the user based on the analysis information;
Image-based scalp analysis and prescription method comprising a. According to claim 1,
The analysis step is an image-based scalp analysis and prescription method, characterized in that for confirming the user's scalp and hair conditions from the scalp image through a machine learning engine. According to claim 2,
An image-based scalp analysis and prescription method in which the machine learning engine learns through at least one of pose tracking and line tracking based on labeling data. According to claim 1,
The analysis step is an image-based scalp analysis and prescription method of calculating at least one index of the number of hairs, average hair thickness, average number of hairs per one hair root, scalp oil content, and scalp inflammation from the scalp image. According to claim 1,
The analysis step is an image-based scalp analysis and prescription method, characterized in that for analysis by comparing with the scalp image through a program based on big data pre-stored in the management server. According to claim 1,
Image-based scalp analysis and prescription method further comprising a paperwork step for more clear prescription between the analysis step and the prescription step. According to claim 6,
In the questionnaire step,
Analysis information delivery step of the management server transmitting the analysis information to the user terminal;
Creating a medical questionnaire based on the analysis information to create a medical questionnaire and forwarding to the management server; and
A diagnosis step of comprehensively diagnosing the condition of the scalp with reference to the analysis information and the questionnaire in the management server and calculating a diagnosis result;
including,
Image-based scalp analysis and prescription method, characterized in that the prescription step recommends a product or prescription based on the comprehensive diagnosis result calculated in the diagnosis step. According to claim 7,
The questionnaire is an image-based scalp analysis and prescription method including at least one of a questionnaire including a question provided by the management server and text input through the user terminal together with the analysis information in the analysis information transmission step. According to claim 8,
The image-based scalp analysis and prescription method, characterized in that the management server analyzes the user's troubled part, trouble content, positive and negative included in the text through deep learning-based natural language processing. According to claim 7,
The diagnosis step is an image-based scalp analysis and prescription method, characterized in that the management server determines a vulnerable part of the user and a vulnerable state for each vulnerable part based on the analysis information and the questionnaire. According to claim 7,
The prescription step is an image-based scalp analysis and prescription method, characterized in that for recommending a product according to the diagnosis result or recommending a treatment plan based on all component information, medical information or pharmaceutical information of the product collected by the management server . According to claim 1,
Image-based scalp analysis and prescription method further comprising a prescription transmission step of transmitting the prescription information calculated in the prescription step to the user terminal. In the system for performing the image-based scalp analysis and prescription method according to at least one of claims 1 to 12,
a scalp scanner for acquiring scalp image information by photographing the user's scalp;
a user terminal that receives, stores, and transmits the scalp image information from the scalp scanner, and receives external information; and
The scalp image information transmitted from the user terminal is stored, and the user's scalp and hair condition is checked and analyzed through a pre-entered program to calculate and prescribe the severity of the user's scalp and hair condition, and the calculation result and prescription result are obtained. a management server transmitting to the user terminal;
Image-based scalp analysis and prescription system comprising a. In the management server according to at least one of claims 1 to 12,
a receiving unit for receiving information transmitted from the scalp scanner and the user terminal;
an analyzer for storing, confirming, analyzing, diagnosing, and prescribing the scalp image received through the receiving unit using big data and a machine learning engine; and
a transmission unit for transmitting the information analyzed by the analysis unit to the outside;
A management server that includes a. A recording medium on which a program for confirming and analyzing the scalp image input to the management server according to at least one of claims 1 to 12 is recorded.

Images