KR102333120B1 - Self Scalp Diagnostic System and Method - Google Patents

Abstract

A self-diagnosing system and method for self-diagnosing the scalp that guides a consistent scalp image acquisition method and quantitative analysis method, and can objectively identify and determine hair and scalp conditions are provided. A self scalp diagnosis method according to an embodiment of the present invention includes: recognizing a user's face with a front camera of a computing device; distinguishing a hair part and a facial part from the recognized face; setting an examination area with reference to the divided facial area and hair area; Including; examining the condition of the scalp in the examination area.
Accordingly, by guiding a consistent scalp image acquisition method and quantitative analysis method, accurate self-diagnosis of the scalp is possible, and it is possible to objectively grasp and determine the hair and scalp conditions.

Description

Self Scalp Diagnostic System and Method

The present invention relates to a technique for diagnosing hair loss, and to a method in which a user can obtain a scalp image by consistently identifying a test site, and analyze the acquired scalp image to determine the state of hair.

Hair is one of the most important elements of a person's appearance. People use their hair to create a new image, creating individuality and confidence. When hair loss occurs, it can be psychologically affected, which can lead to a lack of self-confidence and cause stress. Therefore, many people are very interested in scalp health and care.

Currently, various hair loss management products such as hair growth shampoos, scalp massagers, and far-infrared rays are being launched in the market. However, there is no effective way to verify the effectiveness of these products. It is expensive to get a diagnosis at a specialized clinic.

With the development of digital imaging technology, scalp diagnosis systems with various performance and price are being introduced to the market. Most of the popular scalp diagnosis systems simply show the image of the scalp and do not provide additional quantitative indicators. Without quantitative indicators, the usefulness of the scalp diagnosis system will decrease.

Laid-Open Patent Publication No. 10-2012-0110479 (October 10, 2012) Japanese Unexamined Patent Publication No. 2010-082245 (2010.04.15)

The present invention has been devised to solve the above problems, and an object of the present invention is to guide a consistent scalp image acquisition method and quantitative analysis method, and to objectively identify and determine hair and scalp conditions. To provide a diagnostic system and method.

According to an embodiment of the present invention for achieving the above object, a self-diagnosing method for scalp self-diagnosing includes: recognizing a user's face with a front camera of a computing device; distinguishing a hair part and a facial part from the recognized face; setting an examination area with reference to the divided facial area and hair area; Including; examining the condition of the scalp in the examination area.

The setting step may include inducing the user to part in the hair region through the screen of the computing device, detecting the parting line, and setting the inspection region by riding the part from the hair line part of the forehead to the crown part.

The setting step may be setting a plurality of inspection areas.

The setting step may include displaying the examination area on the screen of the computing device and guiding the user to acquire an image of the examination area with a scalp camera.

The image acquisition of the examination area may be performed through a button of a scalp camera or a user interface of a computing device.

The inspection step may include pre-processing the acquired image; estimating the thickness of hair from the pre-processed image; determining the number of hairs in the pre-processed image, and calculating the hair density; may include.

The self-diagnosing method for scalp self-diagnosing according to the present invention may further include the step of providing an analysis result by comparing the examination result with the existing examination result.

According to another aspect of the present invention, a scalp camera for acquiring an image in the inspection area of the scalp; and the front camera recognizes the user's face, distinguishes the hair part and the facial part from the recognized face, sets the inspection area by referring to the divided facial area and hair area, and inspects the scalp condition with the image acquired from the scalp camera A self-contained scalp diagnosis system is provided, comprising: a computing device.

As described above, according to the embodiments of the present invention, accurate self-diagnosis of the scalp is possible by guiding a consistent scalp image acquisition method and a quantitative analysis method, and it is possible to objectively identify and determine hair and scalp conditions. .

In particular, according to the embodiments of the present invention, the accuracy of the inspection is increased by consistently designating the position to be inspected, and the progress of the scalp can be quantitatively and easily confirmed by storing and comparing and showing the existing inspection data.

1 is a basic configuration of a self scalp diagnosis system according to an embodiment of the present invention;
2 is a scalp diagnosis flow chart;
3 is a face recognition guide screen;
4 is a hair region detection screen;
5 is an inspection area setting and image acquisition screen;
6 is a flow chart of the scalp inspection process;
7 is an example of hair outline extraction and line segment display, and
8 is an example of estimating the number of hairs using machine learning.

Hereinafter, the present invention will be described in more detail with reference to the drawings.

1 shows a basic configuration of a self scalp diagnosis system according to an embodiment of the present invention. The self scalp diagnosis system according to the embodiment of the present invention, as shown, includes a 'scalp diagnosis camera device 100' (hereinafter abbreviated as 'scalp camera 100') and a 'computing device equipped with a front camera ( 200)' (hereinafter abbreviated as 'computing device 200').

The scalp camera 100 is used for acquiring a scalp image, and is a microscope device that can expand and show a small area. The scalp camera 100 is configured to include a camera body 110 , a scalp contact unit 120 , an LED 130 , an LED brightness control unit 140 , and a focus control unit 150 , as shown.

The camera body 110 is provided with a scalp contact unit 120 , an LED 130 , and a focus control unit 150 , and is connected to the LED brightness control unit 140 and the computing device 200 . The scalp contact part 120 is a part in contact with the test part of the scalp.

The LED 130 is a light that brightly illuminates the examination area, the LED brightness control unit 140 is a means for adjusting the brightness of the LED 130, and the focus adjustment unit 150 enlarges or reduces the examination area to view the examination area. It is a means to adjust the focus so that

The computing device 200 processes the scalp image input from the scalp camera 100 and provides a user interface to designate an examination location and show the examination result. The computing device 200 may be in the form of a smartphone, tablet, PC, notebook, or the like.

Figure 2 shows the overall process flow of the system.

In the face recognition step, the user's face is recognized using the front camera of the computing device 200 (S310). To recognize the face, it uses an algorithm such as Haar Cascade to classify the user's face. The user interface guides the user to look in front of the camera and bow slightly (see FIG. 3 ).

In the hair region detection step, the hair part and the facial part are distinguished from the recognized face by using a color classification technique (S320: see FIG. 4).

In the examination area setting step, the area to be examined is divided and displayed on the screen with reference to the recognized facial area and hair area (S330)

Specifically, through the user interface, the user is asked to part the hair area. The parting line is detected through image analysis, and the inspection area is marked by riding the part from the hairline part of the forehead to the crown part.

A plurality of inspection areas are generated according to the image resolution of the scalp camera 100 . The user places the scalp camera 100 on the portion displayed on the screen and acquires an image.

Image acquisition uses a snapshot button mounted on the scalp camera 100 or a method provided in a user interface (eg, pressing a virtual button on the screen, recognizing double eye blinks, etc.). The procedure of acquiring an image along the parting is performed several times in different parts of the hair area depending on the settings. Finally, image the inspection area along the hairline (see Fig. 5).

All of the acquired images are stored in the memory of the computing device 200 after being classified (labeling - labeling) according to the acquisition site.

In the scalp inspection step, the images stored in the memory are inspected in the same manner as in FIG. 6 (S340). 6 is a flowchart of a scalp inspection process.

In the scalp image pre-processing step, several steps of image processing are performed to determine the thickness and number of hairs from the image (S341).

Specifically, in step S341, the image is converted to a black-and-white channel through image contrast enhancement, and then the image contrast is improved through histogram equalization. In addition, by removing the light reflection area through the morphology operation, the part that appears white as the light is reflected on the hair area is removed. Then, the scalp region and the hair region are separated through image binarization.

In the thickness estimation step, the thickness of the hair is estimated (S342). Detect the skeleton of hair using image thinning (skeletonization), extract a line segment from the thinned hair image using Hough transform, find the distance from the extracted line segment to the hair outline, and based on this Calculate the thickness of the hair. The method of finding the intersection of the drawn line and the contour at the center of the line segment and finding the distance between the line segment and the intersection can be used.

In the hair density calculation step, the number of hairs compared to the image area is determined (S343). The number of hairs may be counted by grasping the line endpoints of the thinned hair, or the number of hairs may be obtained using machine learning as shown in FIG. 8 .

If the hair thickness or density cannot be calculated from the specific image acquired, the user is instructed to acquire the image of the region again through the user interface. The calculated quantitative index items are divided into an acquisition inspection area, date and time, and all are stored in the memory of the computing device 200 .

Again, a detailed description will be given of the subsequent process of the scalp inspection step (S340) by returning to FIG. 2 .

In the existing data comparison step, a difference is calculated by comparing the previously stored quantitative index with the newly obtained quantitative index item (S350).

And, in the step of providing the analysis result, the inspection result is organized and displayed to the user through the user interface (S360).

So far, a preferred embodiment of the self-diagnosing system and method for scalp diagnosis has been described in detail.

In an embodiment of the present invention, a self-diagnosing system and method for self-diagnosing the scalp that can objectively identify and determine hair and scalp conditions by guiding a method for obtaining a consistent scalp image and a quantitative analysis method are presented.

Through this, it is possible to increase the accuracy of the inspection by consistently designating the location to be inspected, and by storing and comparing the existing inspection data, it is quantitative and easy to check the scalp condition.

On the other hand, it goes without saying that the technical idea of the present invention can also be applied to a computer-readable recording medium containing a computer program for performing the functions of the apparatus and method according to the present embodiment. In addition, the technical ideas according to various embodiments of the present invention may be implemented in the form of computer-readable codes recorded on a computer-readable recording medium. The computer-readable recording medium may be any data storage device readable by the computer and capable of storing data. For example, the computer-readable recording medium may be a ROM, RAM, CD-ROM, magnetic tape, floppy disk, optical disk, hard disk drive, or the like. In addition, the computer-readable code or program stored in the computer-readable recording medium may be transmitted through a network connected between computers.

In addition, although preferred embodiments of the present invention have been illustrated and described above, the present invention is not limited to the specific embodiments described above, and the technical field to which the present invention belongs without departing from the gist of the present invention as claimed in the claims In addition, various modifications may be made by those of ordinary skill in the art, and these modifications should not be individually understood from the technical spirit or perspective of the present invention.

100: camera device for scalp diagnosis (scalp camera)
200: computing device with front camera (computing device)
110: camera body
120: scalp contact part
130: LED
140: LED brightness control unit
150: focus control unit

Claims (8)

Recognizing, by the self-scalp diagnosis system, the user's face with the front camera of the computing device;
distinguishing, by the self scalp diagnosis system, a hair part and a facial part from the recognized face;
setting, by the self scalp diagnosis system, an examination area with reference to the divided facial area and hair area;
Including, by the self scalp diagnosis system, inspecting the scalp condition in the examination area;
The setting steps are
A self-diagnosing method for scalp diagnosis, comprising inducing a user to part a hair region through a screen of a computing device, detecting the parting line, and setting the parting from the hair line part of the forehead to the crown part as an examination area.
delete The method according to claim 1,
The setting steps are
A self-diagnosing method for scalp diagnosis, characterized in that a plurality of examination areas are set.
4. The method according to claim 3,
The setting steps are
A self-diagnosing method for scalp self-diagnosing, comprising displaying an examination area on a screen of a computing device and guiding a user to acquire an image of the examination area with a scalp camera.
5. The method according to claim 4,
Image acquisition of the inspection area,
A self-diagnosing method for scalp self-diagnosis, characterized in that it is performed through a button of a scalp camera or a user interface of a computing device.
5. The method according to claim 4,
The inspection step is
The self scalp diagnosis system, pre-processing the acquired image;
estimating, by the self-scalp diagnosis system, the thickness of the hair from the pre-processed image;
The self-scalp diagnosis method comprising the steps of: calculating, by the self-scalp diagnosis system, the number of hairs in the pre-processed image and calculating the hair density.
The method according to claim 1,
The self scalp diagnosis method further comprising the step of, by the self scalp diagnosis system, comparing the examination result with the existing examination result and providing the analysis result.
a scalp camera that acquires images in the inspection area of the scalp; and
Recognizes the user's face with the front camera, distinguishes the hair part and the facial part from the recognized face, sets the inspection area by referring to the divided facial area and hair area, and inspects the scalp condition with the image acquired from the scalp camera. Computing device; including;
computing device,
A self-diagnosing system for scalp diagnosis characterized by inducing the user to part in the hair region through the screen, detecting the parting line, and setting the parting from the hair line part of the forehead to the crown part as the inspection area.

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