KR102239575B1 - Apparatus and Method for skin condition diagnosis - Google Patents

Abstract

The present invention includes an image acquisition unit that acquires a gray skin image; An image processing unit verifying and processing the gray skin image; An image analysis unit that analyzes the verified and processed gray skin image; A skin diagnosis unit that diagnoses skin moisturization based on the results analyzed by the image analysis unit; And a display unit for recognizing the diagnosis result of the skin, and to a skin diagnosis method using the same. Accordingly, it is possible to accurately diagnose skin moisturizing and skin moisturizing distribution by presenting an objective skin diagnosis through a skin image.

Description

Apparatus and Method for skin condition diagnosis

The present invention relates to a skin diagnosis apparatus and method. In more detail, the present invention relates to a skin diagnosis apparatus and method for evaluating a moisturizing state among skin conditions and visualizing this as an image so that the general public can easily receive their own skin moisturizing state information.

In general, when categorizing the skin type, it is divided into oily, dry, and neutral skin according to the amount of sebum secreted, and complexity and sensitivity are added to it.

As a way to find out this type of skin, first wait for the evening, wash your face cleanly, wait 15 to 20 minutes without applying anything, and then the whole sebum appears and starts to greasy, you will feel oily and dry. , If you don't find anything else, it is classified as a neutral skin.

In addition, when combined skin has a lot of sebum secretion in the forehead and nose, but the cheek always feels like a crumbly, that is, the skin has two or more skin properties, oily and dryness due to the imbalance of sebum secretion.

Sensitive skin shows a phenomenon that the skin looks red due to the expansion of capillaries and blood circulation is not possible, and when entering a warm room from a cold place, the skin may become itchy and the face may become red. Such skin is usually classified as sensitive skin.

However, since the skin information by the above method is information based on one's own feeling or guess, it is unscientific and unreasonable, and it is inappropriate to use it as accurate one's own skin care information.

In order to solve this problem, there is a need to perform scientifically accurate and comprehensive skin measurements, and to perform reasonable skin care according to diagnosis by experts.

Accordingly, in general, as a method for evaluating the moisturization of the stratum corneum, a corneometer CK (Germany), which measures electric capacity, and Nova ^TM DPM ^® (nova Technology Co.USA), measures impedance-based capacitance. ), there are Skicon 200 ^® (IBS, Japan) measuring methods to measure electrical conductivity. However, these measurement methods only present numerical results, and there is a disadvantage that the general public cannot easily understand them.

As a related invention, there is a'skin diagnosis system' which is Korean Patent Registration No. 10-0609823 (2006.07.31).

Referring to FIG. 1, the skin diagnosis system measures pores, pigmentation, oil, dead skin cells, moisture, elasticity, etc. as comprehensive information on the skin of the human body, diagnoses them, and prescribes cosmetics suitable for their skin type. It relates to a skin diagnosis system that enables scientific and rational skin management.

However, in the case of a moisture meter in the skin diagnosis system, since the measured value is output using the above-described moisturizing evaluation method, there is a problem that it is not easy to understand even if the general public is easily provided with their own skin moisturizing status information.

Accordingly, an object of the present invention is to provide an apparatus and method for diagnosing a skin condition by acquiring a skin image and analyzing a skin image based on the obtained skin image.

Preferably, it is an object of the present invention to provide a skin diagnostic apparatus and method for accurately diagnosing skin moisturizing through skin moisturizing and skin moisturizing patterns obtained by analyzing a skin image.

In addition, it is an object of the present invention to provide a skin diagnosis apparatus and method for providing a type of skin diagnosis result to be easily understood.

According to the present invention, the object is an image acquisition unit for obtaining a gray skin image; An image processing unit verifying and processing the gray skin image; An image analysis unit that analyzes the verified and processed gray skin image; A skin diagnosis unit that diagnoses skin moisturization based on the results analyzed by the image analysis unit; And a display unit for recognizing the diagnosis result of the skin.

Here, the image processing unit may include a validity verification unit for verifying the validity of the gray skin image; And an image cutting unit configured to form an effective gray skin image by removing an invalid image area from the gray skin image verified to be effective.

In addition, the image analysis unit, MGL (Mean Gray Level), which is an average of pixel values from the effective gray skin image, and MTH20 (Mean Threshold), which is an average of the top 20% pixel values in the dark order of the effective gray skin image. histogram 20%) can be obtained, and an error rate can be obtained according to Equation 1 below.

Equation 1

Here, E is the error rate.

In addition, the display unit may further display the captured gray skin image or a histogram indicating an analysis result derived from the image analysis unit.

In addition, the image acquisition unit may be a skin scanner.

Meanwhile, the skin diagnosis unit may further include an information providing unit that provides information on a makeup product or a makeup method according to a skin diagnosis result.

The object according to the present invention, (a) obtaining a gray skin image; (b) verifying and processing the acquired gray skin image; (c) analyzing the verified and processed gray skin image; (d) diagnosing a skin moisturizing state based on the analyzed gray skin image; And (e) implementing a skin diagnosis result, wherein the step (b) comprises: (b1) verifying the validity of the gray skin image, and (b2) an invalid image area in the gray skin image. It is achieved by a skin diagnosis method comprising the step of removing to form an effective gray skin image.

Here, the step (c) includes MGL (Mean Gray Level), which is an average of pixel values from the effective gray skin image, and MTH20, which is an average of the top 20% pixel values from the darkest order of the effective gray skin image. Mean Threshold histogram 20%) and obtaining an error rate according to Equation 2 below using the MGL and the MTH20.

Equation 2

Here, E is the error rate.

In addition, it may further include providing information on a makeup product or a makeup method suitable for a skin condition according to the skin diagnosis result obtained in step (d).

The skin diagnosis apparatus and method according to an exemplary embodiment of the present invention having the above configuration can accurately diagnose skin moisturization through skin moisturization and skin moisturizing patterns obtained by analyzing a skin image.

That is, as the age increases, the deviation of the feeling of skin moisturization tends to increase, but the skin diagnosis apparatus and method according to a preferred embodiment of the present invention presents an objective skin diagnosis through a skin image to provide skin moisturization and Accurate diagnosis of skin moisturizing distribution can be made.

In addition, the user's convenience is provided by categorizing and providing the skin diagnosis results so that they can be easily understood.

1 is a diagram showing a conventional skin diagnosis system,
2 is a view showing a skin diagnosis apparatus according to an embodiment of the present invention,
3 is a view showing a validity verification unit of the skin diagnosis apparatus according to an embodiment of the present invention,
4 is a view showing an image cutout of the skin diagnosis apparatus according to an embodiment of the present invention,
5 is a diagram showing a relationship between MTH20 and a moisturizing degree in a skin diagnosis apparatus according to an embodiment of the present invention,
6 is a diagram showing a correlation between MTH20 and a moisturizing value measured by a coniometer in the skin diagnosis apparatus according to an embodiment of the present invention,
7 and 8 are diagrams showing an error rate (E) in the skin diagnosis apparatus according to an embodiment of the present invention,
9 is a view showing a skin moisturizing pattern divided by a skin diagnosis unit of the skin diagnosis apparatus according to an embodiment of the present invention.
10 is a view showing a display unit of the skin diagnosis apparatus according to an embodiment of the present invention,
11 is a diagram showing a method for diagnosing skin according to an exemplary embodiment of the present invention.

Hereinafter, preferred embodiments of the present invention will be described in detail with reference to the accompanying drawings in order to clarify a solution to the technical problem of the present invention. However, in describing the present invention, if the description of the related known technology rather obscure the subject matter of the present invention, a description thereof will be omitted. In addition, terms to be described later are terms defined in consideration of functions in the present invention, which may vary according to intentions or customs of designers, manufacturers, and the like. Therefore, the definition should be made based on the contents throughout the present specification. In addition, parts denoted by the same reference numbers (reference numbers) throughout the specification represent the same elements.

Hereinafter, a skin diagnosis apparatus and a skin diagnosis method using the same according to an embodiment of the present invention will be described.

Referring to FIG. 2, the skin diagnosis apparatus 1 according to an exemplary embodiment of the present invention includes an image acquisition unit 100, an image processing unit 200, an image analysis unit 300, a skin diagnosis unit 400, and A display unit 500 may be included.

The image acquisition unit 100 acquires a gray skin image by using an imaging device including a sensor array in which a capacitive sensor is integrated so as to acquire 2D data of skin moisturization. That is, when scanning the skin, the imaging device combines (arranges) 2D pixel data and outputs the gray skin image.

Here, the imaging device may be a skin scanner using a sensor such as a fingerprint recognition sensor. Of course, the gray skin image may be obtained using an imaging device such as a camera.

Accordingly, the image acquisition unit 100 may acquire a gray skin image from human skin using the imaging device. In particular, the image acquisition unit 100 may acquire a skin image of a face or a skin image of a portion of the face.

In more detail, the image acquisition unit 100 acquires the gray skin image. In this case, a region in which the skin contains a lot of moisture in the gray skin image appears dark in the gray skin image. Accordingly, the gray skin image can be generated to check the degree of skin moisture.

In this regard, as shown in FIG. 6, in the correlation between the moisturizing value measured by the conventional moisturizing evaluation method, the coniometer, and the MTH20 value, it can be confirmed that the darkened area is the skin containing a lot of moisture.

The image processing unit 200 may include a validity verification unit 210 and an image cutting unit 220.

Accordingly, after verifying the validity of the gray skin image, the image processing unit 200 removes an invalid image area from the gray skin image to minimize an error in the analyzed result.

The validity verification unit 210 divides the gray skin image into a plurality of identical areas, measures an average value of gray-scale of each area, and calculates a standard deviation between each area.

When the standard deviation value calculated by the validation unit 210 is greater than a preset value, the validation unit 210 determines that the skin image is not a valid image, Lets you acquire an image.

If the standard deviation value verified by the validation unit 210 is smaller than a preset value, the validation unit 210 determines that the gray skin image is a valid image.

As illustrated in FIG. 4, the image cutting unit 220 removes an edge area of the gray skin image, that is, an invalid image area, which is determined by the validity verification unit 210 as a valid image. That is, the image cutting unit 220 removes the edge of the gray skin image at a distance separated by a preset distance from the outline of the skin.

Accordingly, the image cutting unit 220 forms an effective gray skin image from which an invalid image area is removed, so that when analyzing the gray skin image, an error in analysis through the gray skin image can be minimized.

The image analysis unit 300 analyzes the effective gray skin image and calculates and processes the image and numerical values.

That is, MGL (Mean Gray Level), which is the average of pixel values from the effective gray skin image, and MTH20 (Mean Threshold histogram 20%), which is the average of the top 20% pixel values from the darkest order of the effective gray skin image. Can be obtained.

For example, the pixel value of the effective gray skin image may be expressed as a value between 0 and 255. In addition, as the pixel value of the effective gray skin image is closer to 0, it is expressed darker.

Here, the MGL, as described above, is used as an index for determining whether the skin image is valid, and the MTH20 excludes factors that affect data such as down hair and skin troubles, and in particular, the imaging It is used as an index to analyze mainly the area contacted by the device.

Therefore, the MTH20 is used as an index to determine the degree of skin moisture.

At this time, as shown in FIG. 5, when the MTH20 value is less than 30, the skin contains a rich moisture content, so it is analyzed as a deep moisturizing state, and when the MTH20 value is 30 or more and less than 50, the skin contains a general moisture content. It can be analyzed as a mixed moisturizing state that requires a habit of skin care. In addition, when the MTH20 value is 50 or higher, the skin is in a dry state due to insufficient moisture, so it can be analyzed as a pale moisturizing state that requires attention to moisturizing management.

As shown in FIG. 6, looking at the correlation between the moisturizing value measured by the conventional moisturizing evaluation method, the coniometer, and the MTH20 value, the values of 30 and 50, which are the values set in the MTH20, determine the skin condition. It can be a criterion to do. In FIG. 6, a blue dot indicates a moisturizing value measured by the coniometer, and indicates a skin area equal to one area of the imaged skin measured by the coniometer.

Meanwhile, the image analysis unit 300 obtains an error rate (E) using the MGL and the MTH20.

The error rate (E) is used as an index to analyze the skin moisturizing pattern of the measured area. That is, the error rate (E) is used as an index to determine whether the moisturizing is evenly distributed.

Here, the error rate (E) can be obtained by Equation 1 below.

MGL = average of the pixel values of the effective gray skin image.

MTH20 = average of the top 20% pixel values from the darkest order of the effective gray skin image.

As shown in Figure 7 (a), if the error rate (E) is less than 50, it can be analyzed that the moisture of the skin is maintained in an even distribution, as shown in Figure 7 (b), When the error rate (E) is 50 or more, it can be analyzed that the moisture of the skin is maintained in an uneven distribution. In FIG. 7, the red line simply shows the distribution of the histogram for each pixel value of the effective gray skin image.

In more detail, as shown in FIG. 8, the effective gray skin image may be expressed as a histogram of FIG. 8 by an image analysis unit. Here, as the distribution of the histogram is skewed to the left, it means that the moisture content of the imaged skin is higher. Here, the vertical axis means the number of pixels.

The skin diagnosis unit 400 diagnoses skin moisturization based on the result of the image analysis unit 300.

As shown in FIG. 9, the skin diagnosis unit 400 may classify a skin moisturizing pattern into preset types and diagnose a user's skin moisturizing based on a result value included in each category type.

The present invention is divided into six types, and the skin is diagnosed as an example, but it is not necessarily limited thereto, and of course, it may be classified into a variety of types for the user's request or for an accurate and more detailed diagnosis. .

The display unit 500 implements the skin diagnosis result so that the user can easily recognize it.

That is, as shown in FIG. 10, the display unit 500 may implement basic information and diagnosis results for diagnosis, such as the effective gray skin image, the histogram of the image analysis unit, and a skin moisturizing diagnosis result by the skin diagnosis unit. I can.

In addition, a 3D color map expressed by converting the effective gray skin image into 3D color may be further included. That is, since the effective gray skin image is converted into 3D color in consideration of the pixel value of the effective gray skin image, the moisturizing contained in the skin is higher in the blue area in the 3D color map.

Therefore, since moisture is implemented in blue in the 3D color map, the user can easily grasp the skin moisturizing and skin moisturizing distribution by comparing it with the image of the measurement area.

Meanwhile, the skin diagnosis apparatus 1 may further include an information providing unit 600.

The information providing unit 600 provides information on a makeup product or a makeup method suitable for the diagnosed skin condition based on the result of the skin diagnosis unit 400.

Specifically, the information providing unit 600 may include a cosmetic product information unit 610 and a makeup information unit 620.

The cosmetic product information unit 610 provides information on cosmetic products suitable for the diagnosed skin condition.

Specifically, the cosmetic product information unit 610 may receive user information such as the brand of the cosmetic product preferred from the user, the user's age, the user's gender, or the price to be purchased, and comprehensively collect the received user information and the diagnosed skin condition. Considering this, it provides information on cosmetic products.

The cosmetic product information unit 610 may include a cosmetic product database, and the cosmetic product database is stored by subdividing cosmetic products into various categories such as type, function, preferred age, price, brand, or product capacity.

The cosmetic product information unit 610 selects a cosmetic product suitable for the diagnosed skin condition according to a preset algorithm from the cosmetic product database in consideration of user information, and provides the selected information to the user.

The makeup information unit 620 provides information on a makeup method suitable for the diagnosed skin condition.

Specifically, the makeup information unit 620 may provide information on a makeup method suitable for a skin condition diagnosed as a cosmetic product provided to a user by the makeup product information unit 610.

The information provided by the makeup information unit 620 may be not only photos and images, but also videos.

The makeup information unit 620 receives information from the skin diagnosis unit 400 to diagnose a skin condition. It is preferable that the skin diagnosis unit 400 uses the result of diagnosing the skin condition for each part of the skin, particularly the face.

However, it is important to make make-up suitable for the skin condition of each part of the face, but since make-up that matches well overall is also important, it is desirable to implement an algorithm that provides suitable make-up in consideration of this.

The makeup information unit 620 does not necessarily describe an appropriate makeup method using the makeup product selected in the makeup product information unit 610, but obtains makeup information most suitable for the diagnosed skin condition from the makeup information storage database and provides it to the user. have. Here, the makeup information storage database stores information on a skin condition and a suitable makeup method, and this information can be changed according to fashion, personal characteristics, advancement of makeup, or advancement of makeup products.

Accordingly, information provided by the makeup product information unit 610 and the makeup information unit 620 may be implemented by the display unit 500.

The skin diagnosis apparatus 1 according to an embodiment of the present invention diagnoses a skin condition and provides information on a cosmetic product and makeup method suitable for the diagnosed skin condition, so that a user can manage the skin condition and maintain beauty. To be there.

Hereinafter, a method for diagnosing skin will be described with reference to FIG. 11.

The skin diagnosis method (S1) according to an embodiment of the present invention includes obtaining a gray skin image (S10), verifying and processing the gray skin image (S20), and verifying the verified and processed gray skin image. Analyzing (S30), diagnosing a skin moisturizing condition based on the analyzed gray skin image (S40), implementing a skin diagnosis result (S50), and information on a makeup product or makeup method suitable for the skin condition It may include a step (S60) of providing.

In the step S10 of acquiring a skin image, a gray skin image is acquired using the imaging device.

In the step of verifying and processing the gray skin image (S20), after verifying the validity of the obtained gray skin image, an invalid image area of the gray skin image is removed to minimize an error in the analyzed result.

Accordingly, the step of verifying and processing the gray skin image (S20) includes verifying the validity of the gray skin image (S21) and removing an invalid image area from the gray skin image (S22). I can.

In the step of verifying the validity of the gray skin image (S21), the gray skin image is divided into a plurality of identical areas, the average value of the gray-scale of each area is measured, and then the standard deviation between each area is calculated. do.

Accordingly, in verifying the validity of the gray skin image (S21), it is determined whether the gray skin image is a valid image for analysis.

In the step of removing the invalid image area from the gray skin image (S22), an edge area of the gray skin image determined to be a valid image, that is, an invalid image area is removed. Accordingly, a valid gray skin image from which an invalid image area has been removed is obtained.

In the step of analyzing the verified and processed skin image (S30), the effective gray skin image is analyzed and calculated as an image and a numerical value.

Analyzing the processed skin image (S30) includes a mean gray level (MGL), which is an average of pixel values from the effective gray skin image, and a pixel value of the top 20% from the darkest order of the effective gray skin image. Obtaining an average MTH20 (Mean Threshold histogram 20%) (S31), and using the MGL and the MTH20, obtaining an error rate (E) according to Equation 2 (S32). can do.

MGL = average of the pixel values of the effective gray skin image.

MTH20 = average of the top 20% pixel values from the darkest order of the effective gray skin image.

That is, in the step of analyzing the processed skin image (S30), MGL (Mean Gray Level), which is an average of pixel values from the effective gray skin image, and the top 20% pixels from the darkest order of the effective gray skin image MTH20 (Mean Threshold histogram 20%), which is the average of the values, is obtained, and based on this, an error rate (E) is calculated using Equation 2 above.

In the step of diagnosing the skin moisturizing state based on the analyzed skin image (S40), the skin moisturizing is diagnosed based on the result of the image analysis unit 300.

9, in the step of diagnosing a skin moisturizing state based on the analyzed gray skin image (S40), a skin moisturizing pattern is classified into a preset type, and the verified and processed gray skin image is analyzed. The skin moisturizing and skin moisturizing distribution of the user included in each category type may be diagnosed based on the result value in step S30.

In the step of implementing the skin diagnosis result (S50), the skin diagnosis result may be easily recognized by the user using the display unit 500.

In the step (S60) of providing information on a makeup product or a makeup method suitable for a skin condition, information on a makeup product or a makeup method suitable for the diagnosed skin condition is provided based on the result of the skin diagnosis unit 400.

It goes without saying that various embodiments according to the present invention can solve various technical problems other than those mentioned in the present specification in the related technical field as well as in the relevant technical field.

Up to now, the present invention has been described with reference to embodiments. However, those skilled in the art will be able to clearly understand that the present invention can be implemented in a modified form without departing from the essential technical idea of the present invention. Therefore, the disclosed embodiments should be considered from an illustrative point of view rather than a limiting point of view. That is, the true technical scope of the present invention is shown in the appended claims, and all differences within the scope of equivalents thereto are to be construed as being included in the present invention.

1: skin diagnosis device 100: image acquisition unit
200: image processing unit 300: image analysis unit
400: skin diagnosis unit 500: display unit
600: information providing unit
S1: How to diagnose skin

Claims (9)

An image acquisition unit that acquires a gray skin image;
An image processing unit verifying and processing the gray skin image;
An image analysis unit that analyzes the verified and processed gray skin image;
A skin diagnosis unit that diagnoses skin moisturization based on the results analyzed by the image analysis unit; And
And a display unit displaying a diagnosis result of the skin,
The image processing unit
Obtaining an effective gray skin image from the gray skin image,
The image analysis unit
Obtaining a Mean Gray Level (MGL), which is an average of pixel values from the effective gray skin image, and a Mean Threshold histogram (MTH), that is an average of pixel values in a predetermined range from the dark order of the effective gray skin image, The difference between the MGL and the MTH is divided by the MGL and multiplied by 100 to calculate an error rate,
Based on the MTH, determine the degree of skin moisture,
A skin diagnosis device that determines whether skin moisturizing is evenly distributed or unevenly distributed based on the error rate. The method of claim 1,
The image processing unit,
A validity verification unit to verify the validity of the gray skin image; And
Skin diagnosis apparatus for obtaining a valid gray skin image by removing an invalid image area from the validated gray skin image. The method of claim 1,
The predetermined range is the top 20% skin diagnosis device. The method of claim 1,
The display unit further displays a histogram indicating the effective gray skin image or an analysis result derived from the image analysis unit. The method of claim 1,
The skin diagnosis apparatus, wherein the image acquisition unit is a skin scanner. The method of claim 1,
And an information providing unit for providing information on a makeup product or a makeup method according to a skin diagnosis result of the skin diagnosis unit. (a) obtaining a gray skin image;
(b) verifying and processing the acquired gray skin image;
(c) analyzing the verified and processed gray skin image;
(d) diagnosing a skin moisturizing state based on the analyzed gray skin image; And
(e) implementing a skin diagnosis result,
The step (b),
(b1) verifying the validity of the gray skin image, and
(b2) forming an effective gray skin image by removing an invalid image area from the gray skin image,
The step (c),
Acquiring a Mean Gray Level (MGL) that is an average of pixel values from the effective gray skin image and a Mean Threshold histogram (MTH) that is an average of pixel values in a predetermined range from the dark order of the effective gray skin image; and ,
Multiplying a value obtained by dividing the difference between the MGL and the MTH by the MGL by 100 to obtain an error rate,
The step (d),
Determining a skin moisture level based on the MTH,
Including the step of determining whether the skin moisturizing is even distribution or uneven distribution based on the error rate
Skin diagnostic method of the skin diagnostic device. The method of claim 7,
The predetermined range is the top 20%
Skin diagnostic method of the skin diagnostic device. The method of claim 7,
It characterized in that it further comprises the step of providing information on a makeup product or a makeup method suitable for a skin condition according to the skin diagnosis result obtained in step (d).
Skin diagnostic method of the skin diagnostic device.

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