KR20150093332A - Personal color matching system and matching method thereof - Google Patents

Abstract

The present invention relates to a personal color matching system and a method thereof whereby a user can express a luxurious image by providing a personal color optimized for each person as the personal color optimized for each person is determined and extracted by matching a face image unique to each person with unique colors of spring, summer, autumn, and winter. The personal color matching system includes: an image type database wherein a face image data corresponding to a plurality of face images, a plurality of type groups a consultant sets, and sorted data obtained by sorting the face image data by a type group are stored; a user information database wherein user data input based on a face image of a user who wants consulting are stored; a color database wherein color data, arranged by a type group, are stored; an image type selection module which compares the input user data with the face image data to extract face image data similar with the user data from the face image data and then extracts a type group from the sorted data corresponding to the extracted face image data; a color matching module which extracts the color data corresponding to the extracted type group from the color data base; and a main control unit which controls the image type selection module and the color matching system.

Description

[0001] PERSONAL COLOR MATCHING SYSTEM AND MATCHING METHOD THEREOF [0002]

The present invention relates to a personal color matching system and method.

Personal color refers to a personalized color that blends in with the body color of the individual to make the animation appear lively and vibrant.

Personal color allows you to create a vivid and vibrant image on your face when you are in harmony with your body color.

On the other hand, when applying a personal color that does not match the individual's own body color, the skin looks rough and the sense of transparency disappears, so that the defects of the skin are highlighted. Therefore, the personal color suitable for the body color is recognized as clothing, , Lens color, hair color, etc., it is possible to perform individual image management more efficiently.

However, the personal color that is in harmony with the body color has a problem in that it is difficult for the individual to determine the personal color suitable for the body color because the individual is not objectively recognized and found.

The present invention combines the unique face image of each individual with the intrinsic colors of spring, summer, autumn and winter to diagnose and extract individual optimal personal colors, thereby providing personalized personalized colors for the user to produce a luxurious image A personal color matching system and method.

In one embodiment, the personal color matching system includes face image data corresponding to a plurality of face images, a plurality of type groups set by a consultant, and an image type database storing classification data classified by the type group; A user information database for storing user data inputted based on a face image of a user wishing to consult; A color database for storing color data for each type group; An image type selection module for extracting face image data similar to the user data from the face image data by comparing the input user data with the face image data and extracting a type group from the classification data corresponding to the extracted face image data; ; A color matching module for extracting the color data corresponding to the extracted type group from the color database; And a main control unit for controlling the image type selection module and the color matching system.

The face image data of the personal color matching system may include facial color data including facial color data, face facial data, non-dyed or dyed hair color data, no-lens or lens-wearing pupil color data At least one of them.

The user information database of the personal color matching system includes a user input database in which the user input data inputted by the user is stored and a consultant input database in which the image consultant judges the face image of the user and inputs the inputted consultant input data In the color database, coordination data suitable for occupation, socialization, events, and travel are stored for each type group.

Wherein the image type selection module of the personal color matching system applies a first weight to the user input data and applies the user data having a second weight greater than the first weight to the consultant input data to the type group, And extracts the image type of the user.

The color matching module of the personal color matching system compares the situation data with the situation data including job information, social information, event information, and travel information from the user, and selects the coordination data corresponding to the situation.

The type group of the personal color matching system is divided into eight groups, and the color data corresponding to each type group includes 32 colors.

In one embodiment, the personal color matching method includes a step of generating face image data corresponding to a plurality of face images, a type group and a type group based on face image data, and classification data obtained by classifying the face images by a plurality of face image data Constructing a color database including a face image database and colors set for each type group; Inputting user data associated with the user's face image in a user information database; Extracting facial image data similar to the user data from facial image data by comparing facial image data corresponding to a plurality of facial images stored in an image type classification database using the image type selection module and the user data, Comparing face image data with classification data to determine the type group of the user from the classification data; And extracting a color corresponding to the type group of the user from a color database in which a plurality of color data is stored using the color matching module.

The step of inputting the user data includes: directly inputting user input data by a user using the terminal 1; And inputting consultant data that the consultant judges the face image of the user using the terminal 2.

The type group includes eight groups, and the color data corresponding to each type group includes 32 colors.

Wherein the step of inputting the user data related to the face image of the user to the user information database includes inputting situation data including the user's job information, social information, event information, and travel information, When the situation data is inputted, the step of comparing the condition data and the coordination data suitable for the occupation, socialization, ceremony and travel stored in the color database, and selecting the color suitable for the user's situation.

The personal color matching system and method according to the present invention matches a face data of a user who desires consulting with a plurality of facial image data of a database to select a plurality of type groups suitable for the user's image, The present invention has the effect of improving the image of the user by applying the color best suited to the image of the user to the clothes, the accessories, the bag, the shoes, etc. by selecting the color and providing the coordinated color suitable for the user's situation among the personal colors.

1 is a block diagram of a personal color matching system in accordance with an embodiment of the present invention.
2 is a diagram showing the structure of facial image data of the image type database shown in Fig.
3 is a diagram showing the structure of a type group of the image type database shown in Fig.
Fig. 4 is a diagram showing the structure of classification data of the image type database of Fig. 1. Fig.
5 is a diagram showing the structure of the user information database of Fig.
FIG. 6 is a diagram showing the structure of the color database of FIG. 1. FIG.
7 is a flowchart illustrating a personal color matching method using a personal color matching system according to an embodiment of the present invention.
8 is a block diagram showing a matching procedure according to the personal color matching method of FIG.

In the following description, only parts necessary for understanding the embodiments of the present invention will be described, and the description of other parts will be omitted so as not to obscure the gist of the present invention.

The terms and words used in the present specification and claims should not be construed as limited to ordinary or dictionary meanings and the inventor is not limited to the meaning of the terms in order to describe his invention in the best way. It should be interpreted as meaning and concept consistent with the technical idea of the present invention. Therefore, the embodiments described in the present specification and the configurations shown in the drawings are merely preferred embodiments of the present invention, and are not intended to represent all of the technical ideas of the present invention, so that various equivalents And variations are possible.

1 is a block diagram of a personal color matching system in accordance with an embodiment of the present invention.

Referring to FIG. 1, a personal color matching system 700 includes an image type database 100, a user information database 200, a color database 300, an image type selection module 400, a color matching module 500 And a main control unit 600.

2 is a diagram showing the structure of facial image data of the image type database shown in Fig.

Referring to Figures 1 and 2, the image type database 100 includes facial image data 110 that includes cumulative data of multiple items associated with a plurality of faces or bodies already consulted by an image consultant, 120 and the classification data 130 classified by the type group are stored.

The face image data 110, the type group 120, and the classification data 130 of the image type database 100 are directly input and processed from the image consultant.

In particular, the image consultant sets the type group 120 based on the past consulting experience, coloring, and the like, and sets the classification data 130, which classifies each user into a specific type group based on the face image data 110, ).

2, the facial image data 110 includes identification data code1, makeup facial color data code2, and bare facial color data code3 for storing human information such as name, sex, Facial shape data code4, skin color data code5, hair color data code6, pupil color data code7, and lens color data code8.

The hair color data code6, the pupil color data code7, and the lens color data code8 are colors H, H, and H, respectively. In the face image data 110 of the image type database 100 in the form of a numerical form according to the HVC display indicate method that combines the brightness (V) and the saturation (C) .

Hereinafter, in one embodiment of the present invention, the numerical value according to the HVC notation is expressed in the form of a "number YR ".

Specifically, the facial color data code2 and the facial skin color data code3 can be generated by averaging the measured values of the forehead, the right ball, the left ball, and the jaw skin color measured through the colorimeter.

The makeup facial color data (code 2) can be obtained, for example, in accordance with the HVC notation measured through a colorimetric system, for example, a1 (8.1YR), a2 (8.5YR), a3 (5.1YR) 5.9YR), a6 (5.5YR), a7 (4.6YR) and a8 (4.1YR). The makeup color data (code 2) may be displayed as a section.

B1 (8.0YR), b2 (8.4YR), b3 (5.0YR), b4 (4.8YR), and b5 (5.8) in accordance with the HVC notation measured through a colorimeter, YR), b6 (5.4YR), b7 (4.7YR), and b8 (4.0YR), and the male face color data (code 3) may be displayed as a section.

The face shape data (code4) is divided into, for example, a round shape, an egg shape, a long shape, and an angular shape, and the face shape data code4 is divided into text, numbers, Lt; / RTI >

In the face shape data (code4), for example, the round shape can be divided into c1, the egg shape is c2, the long shape is c3, and the angular shape is c4, and can be stored in the face image data 110. [

The skin color data (code 5) can be divided into a white, yellowish and shiny skin, a white and a reddish glare, a yellow glare and a glare with a yellowish and dark light, and the skin color data (code 5) And may be stored in the image type database 110 in the form of a combination of numbers.

The skin color data (code 5) may include not only the skin color of the face but also the skin color exposed to the outside such as the neck, hands, and feet.

The skin color data (code 5), for example, is divided into d1, whitish reddish, d2, whitish yellow and dull skin, d4, and d4, The skin color data (code 5) may be stored in the face image data 110.

The hair color data (code 6) can be classified into a warm brown shiny hair, a thin hair with a non-shiny hair, a frizzy mint condensation with no shiny hair, and a dull brown shiny hair, May be stored in the image type database 110 in the form of a number or a combination of text and numbers.

For example, the hair color data (code 6) is, for example, e1 for warm brown shiny hair, e2 for thin hair, and e2 for non-shiny hair. And the hair color data (code 6) may be stored in the face image data 110. In addition, the hair color data (code6) may further include hair and hair which have been dyed.

The eye color data (code 7) can be divided into brown eyes, soft brown eyes, soft eyes, deep eyes, bluish white eyes, and eye color data (code 7) And may be stored in the image type database 110 in the form of a combination of numbers.

The pupil color data (code 7) is classified into f1, brown, soft eyes, f2, soft brown, deep eye f3, bluish whiteness and f4, May be stored in the face image data 110.

The lens color data (code 8) can be classified according to the color of the lens worn on the eyeball, and the lens color data (code 8) can be stored in the image type database 110 in the form of text or numbers.

For example, the lens color data (code 8) is classified into a blue color lens g1, a green lens color g2, a brown lens color g3, and a purple color lens g4, (110). ≪ / RTI >

Although the facial image data 100 is shown and described as eight data items in the embodiment of the present invention, the facial image data 100 may be divided into 8 types according to consulting type and consulting purpose. Less than or more than nine data items may be included.

3 is a diagram showing the structure of a type group of the image type database shown in Fig.

Referring to Figures 1 and 3, the type group 120 included in the image type database 100 is defined by the image consultant.

The image consultant classifies the type group 120 into four main type groups 125, for example, and the four main type groups 125 are divided into two subtype groups 127, respectively. Thus, the image consultant, for example, divides the type group 120 into all eight type groups.

The image consultant classifies four main type groups 125 into, for example, srping type, summer type, autumn type and winter type.

The image consultant can, for example, divide the spring type into a vivid type and a warm type, divide the summer type into an elegant type and a romantic type, It is divided into natural type and classic type, and winter type is divided into cool type and dynamic type.

The image consultant is defined as a worm type, one of the spring type, that has no color, has a bright yellow color, has a uniform skin surface, has a uniform color, and has a large contrast of color of face, hair and eyes.

The image consultant, for example, has a yellowish light, stronger face color than the worm type, a healthier look than the worm type, a uniformity of the skin surface and the face color, and a user with a high contrast of face color, hair color, Is defined as a vivid type which is one of the spring type.

An image consultant, for example, has a skin that is very white and has a weak pink color, and has a large unity of the skin surface and the overall color of the skin as well as a low contrast of color of face, hair and eyes. define.

The image consultant, for example, is a face color with partial pink light and yellow color, and has a characteristic that the surface of the skin is uneven, the unity of the face color is small, and the contrast between the face color and hair and eye color is small. It is defined as a romantic type.

The image consultant is a user who has a feature that the face color is yellow but the skin is not glossy, the color is not good, the unity of the skin surface and the face color is small, and the contrast between the face color and the hair color and eye color is small, It is defined as the natural type which is one of the type.

The image consultant, for example, has a darker yellow color than the natural type, and has a very small unity of the skin surface and the complexion of the skin surface, and has a low contrast between the face color and the hair and eye color. Type.

An image consultant, for example, is a user who has a light skin color but has a blue color, and has a uniformity of the skin surface and color of the skin with a soft touch, and has a large contrast between the color of face, hair color and eye color. It is defined as a cool type.

An image consultant is defined as a type of dynamics that is one of the winter type, for example, a user having a dark face of the entire face, uneven surface of skin, less uniformity of face color, and a characteristic of contrasting color of face, hair and eyes do.

3 defines the main type group 125 and the subtype group 127 as the image consultant defines the main loophole group 125 and the subtype group 127 in which the image consultant is defined is the image type data Are stored in the type group 120 of the base 100.

Although an image consultant has been shown and described as setting up four main type groups 125 and eight subtype groups 127 as shown in Figure 3 in one embodiment of the present invention, the main type group 125 ) And the number of subtype groups 127 may be added or subtracted depending on the content of consulting, the purpose of consulting, and the like.

Fig. 4 is a diagram showing the structure of classification data of the image type database of Fig. 1. Fig.

Referring to FIGS. 1, 2 and 4, the image consultant sets and stores the facial image data base 110 and the type group 120 in the facial image database 110, Based on the facial shape, skin color, hair color, pupil color, and lens color, and the feature grouping type group 120 described above, each user stored in the face image database 110 is divided into four main type groups and eight subtypes And stores them in the classification data 130.

The process of generating the classification data 130 may be performed directly by the image consultant but may be automatically classified according to the characteristics of each type set by the image consultant based on the face image data 110. [

Referring to FIG. 4, A of the identification data of FIG. 2 is a color image of a1 (8.5YR), a b1 (8.0YR), a c1 whose face is round, a d1 , The hair color is warm brown and the hair color index is e1, the eye color is soft brown and the soft look is f2, and the identification data A is the main type group 125 according to the characteristics defined by the above image consultant, The type group is a vivid type.

The facial color, the facial color, the skin color, and the facial shape in the type classification of the identification data A are involved, for example, in the selection of the main type group, and the hair color and the pupil color are, for example, However, such a selection is only an example, and the type of data for selecting the main swimming group and the subtype group may be changed depending on the user who desires consulting.

In this way, in FIG. 4, the identification data B is determined by the main type group 125 as a fall type, the sub type group as a class type, the identification data C as the main type group 125 is summer type, The identification data D is determined as the cool type, and the main type group 125 is determined as the winter type and the subtype group is determined as the cool type.

Hereinafter, the user information database 200 of the personal color matching system 700 will be described.

5 is a diagram showing the structure of the user information database of Fig.

Referring to FIGS. 1 and 5, the user information database 200 includes a user input database 210 and a consultant input database 220.

Hereinafter, the user input data stored in the user input database 210 and the consultant input data stored in the consultant input database 220 will be defined as user data.

The user who desires consulting inputs data related to his or her own facial color, facial color, face shape, skin color, hair color, pupil color, and lens color directly to the user input database 210 through the terminal 1 (205) The data stored and provided by the user who desires consulting is defined below as user input data.

The user input data inputted by the user through the terminal 1 205 may be stored in the user input database 210 via the Internet, a local area network, a wired network, or the like.

5, the user input data stored in the user input database 210 by the user Hong Kim (tentative name) who desires consulting is a3 (5.1YR) and the bare face color is b4 (4.8YR) , Face shape is c1, skin color is white, yellow color is d1, shiny skin color, hair color is brown, shiny hair is e1, eye color is soft brown and soft eye color is f2, G1.

Meanwhile, the image consultant judges the face image of the user Hong Kim (tentative name) who wishes consulting to be a face to face, a photograph, a moving image, etc. and sends data of Hong Gil Dong (tentative name) to the consultant input database 220 through the terminal- .

The consultant input data, which judges the face image of the user Hong Kim (tentative name) who wants to consult with the image consultant and stored in the consultant input database 220, has a facial color of a5 (5.9YR) and b7 (4.7 Yr), face shape is egg-shaped c2, skin color is white and red, d2 is skinless color, hair color is brown with shiny hair e1, pupil color is soft brown with soft eye index f2 and optional lens color is blue G1 which is a color lens.

Referring to FIG. 5, when the user input data inputted by the user who desires consulting and the consultant input data judged by the image consultant are determined by the user who desires consulting, the user input data and the consultant input data partially match Some are different.

This is because users wishing to consult are generally unable to calculate face or body information objectively and precisely.

In one embodiment of the present invention, an image consultant who knows a professional color matching technique together with user input data provided by a user who desires consulting objectively consults a user who desires consulting and provides consultant input data Accepting the needs of users who desire consulting, we judge the objective and accurate type of users who desire consulting.

When the type of the user is determined by accepting both the user input data inputted by the user and the consultant input data inputted by the image consultant, as described above, the user input data and the consultant input data are all different from each other .

When the input user data and the consultant input data are partially or completely different from each other, the first weight is applied to the user input data inputted by the user as shown in FIG. 5, and the consultant input data provided by the image consultant The second weight that is higher than the first weight is applied to generate the comprehensive judgment data so as to reflect both the opinion of the user and the opinion of the image consultant but the opinion of the image consultant can be accepted more.

Although the second weight used to reflect the opinion of the image consultant is higher than the first weight used to reflect the opinion of the user in an embodiment of the present invention, in order to positively reflect the opinion of the user The first weight may be equal to or greater than a second weight for reflecting opinions of the image consultant.

The user judgment data stored in the user information database 200 is a combination of user input data and consultant input data input by the user and the consultant wishing to consult in the user information database 200.

In addition to the user input data and the consultant input data, the user information database 200 shown in Fig. 5 includes status information such as a job of Hong Gil-dong (tentative name) who is a user who desires consulting, various kinds of meetings, events, Or may be stored through the terminal 1 205 or the terminal 2 215. [

FIG. 6 is a diagram showing the structure of the color database of FIG. 1. FIG.

Referring to Figures 1 to 6, an image consultant may be able to provide an image consultant with experience, color, trends and fashion sense, etc., of the image consultant once the type group 120 of the image type database 100 is set up, Based on the color data of the color database 300, sets the type-specific colors for each type group 120 for each type group 120 on the basis of the color data, 310).

In addition, the image consultant separately selects a color suitable for the user's job, gender, age, meeting, dinner, and travel, and stores it in the coordination data 320 of the color database 300.

The color data 310 stored in the color database 300 is formed in a number corresponding to each type group 120 shown in FIG.

For example, when the type group 120 shown in FIG. 3 is composed of two main type groups 125 and eight subtype groups 127, the color data 310 is also made up of eight groups.

Specifically, the color data 310 includes elemental color data 311 applied to the element type of the summer type, and the elemental color data 311 includes eight color groups in detail, Is composed of four different colors, and includes a total of 32 colors.

The color data 310 includes romantic color data 312 applied to a romantic type as a summer type and the romantic color data 312 is composed of 8 color groups in detail and each color group includes four It contains 32 colors in total.

The color data 310 includes four color color data 313 applied to a natural type as a fall type, and the natural color data 313 includes eight color groups in detail, And contains a total of 32 colors.

The color data 310 includes classical color data 314 applied to the classical type as a fall type, and the classical color data 314 includes eight color groups in detail and each color group includes four It contains 32 colors in total.

The color data 310 includes vivid color data 315 that is applied to the vivid type as a spring type, and the vivid color data 315 is composed of eight color groups in detail, and each color group includes four different colors And a total of 32 colors.

The color data 310 includes worm color data 316 applied to the worm type in the spring type and the worm color data 316 includes eight color groups in detail and each color group includes four different colors And a total of 32 colors.

The color data 310 includes cool color data 316 applied to the cool type as a winter type, and the cool color data 317 includes eight color groups in detail, and each color group includes four different colors And a total of 32 colors.

The color data 310 includes dynamic color data 318 applied to the dynamic type as a winter type and the dynamic color data 318 is composed of eight color groups in detail and each color group includes four It contains 32 colors in total.

Thus, since eight subtype groups each contain 32 colors, the color data 310 includes a total of 256 colors.

The coordination data 320 stored in the color database 300 includes 32 colors constituting the color data 310 included in each subtype group according to occupation, various kinds of meetings, events, preferred travel destinations, special situations And includes information data classified into three categories.

Accordingly, when a user types a job, a meeting type, an event, a preferred travel destination, and a special situation after a type group of a user who desires consulting is determined, the user can use the coordination data 320 to search for colors included in the color data 310 Can be selected.

If the image type selection module 400 receives the user input data from the user wishing to consult through the first terminal 205 and the consultant input data from the image consultant through the second terminal 215 into the user information database 200 The user input data and the consultant input data are loaded and the face image data 110 is compared with the user data to extract the face image data 110 matched with the user data.

If there is no matching data with the user data in the face image data 110, the image type selection module 400 informs the terminal 2 (215) that there is no matching data so that the image consultant can select the type group of the user To make decisions.

Once the type group of the user desiring consulting is determined from the image type selection module 400, the type group data of the user selected in the image type selection module 400 is provided to the color matching module 500 to be described later.

The image type selection module 400 searches the user information database 200 for the type group of Hong Kil Dong (a pseudonym) input in the user information database of Fig. 5 from the user data and image type database 100, The image data are respectively loaded and compared and analyzed.

For example, in the input data of Hong Gil-dong (a pseudonym) who is a user wishing to consult in FIG. 5, the facial color is a3 (5.1YR), the facial color is b3 (5.0YR) The skin color is white and red, d2, which is a dull skin color, hair color is thin and shiny hair e2, eye color is soft brown and f2 is soft eye light.

When the user data of Hong Kil-dong (a pseudonym) is input, the image type selection module 400 compares the user data of Hong Kil-dong (a pseudonym) with the face image data 110 shown in FIG. 2 to obtain face image data 110).

For example, since the identification data C in Fig. 2 is identical to the user data of Hong Gil-dong (a pseudonym) who is a user who wishes to consult, except for the makeup face color, the image type selection module 400 determines that the identification data C is Hong- It is determined that the face image is the most similar to the face image.

The image type selection module 400 searches the classification data 130 shown in FIG. 4 to select the type group corresponding to the selected identification data C, and extracts from the classification data 130 the main type group of the identification data C and the group Type group is extracted.

As a result of the extraction, the image type selection module 400 selects the main group type of Hong Kil Dong (a pseudonym) as a summer type because the main type group of the identification data C in Fig. 4 is summer type and the sub type group is an elegance type, Select the group type as the element type.

In one embodiment of the present invention, the image type selection module 400 compares the user data and the face image data 110, for example, if the user data and the face image data 110 match 60% Image data can be selected.

The color matching module 500 loads the color data 310 of the color database 300 and determines whether the consulting is desired From the color database 300, the color data corresponding to the main type group and the sub type group of the user.

For example, since the main type group of Hong Gil-dong (a pseudonym) who is a user wishing consulting shown in FIG. 5 is a summer type and the sub type group is an elegant, the color matching module 500 is included in the color data 310 And the elegant color data 311 is selected as the personal color best suited to the face and body image of the user Hong Kim (a pseudonym) who desires consulting.

5, when the status information of the user such as a job of Hong Gil-dong (a pseudonym), various kinds of meetings, an event, a favorite travel destination, and a special situation is inputted, the color matching module 500 displays And selects at least one of the colors included in the color data 311, which is suitable for the situation.

For example, the color matching module 500 selects at least one of the 32 colors included in the elegant color data 311 when a certain person (a pseudonym) wants to consult with the meeting. The color matching module 500) includes at least one color best suited to the meeting situation.

In addition, the color matching module 500 may provide colors suitable for each type of wear item, such as clothing color, accessory color, bag, shoes, and the like.

The main control unit 600 performs data input and output in the image type database 100, the user information database 200 and the color database 300, and the image type selection module 400 and the color matching system And controls data comparison and data extraction in the memory 500.

7 is a flowchart illustrating a personal color matching method using a personal color matching system according to an embodiment of the present invention. 8 is a block diagram showing a matching procedure according to the personal color matching method of FIG.

7 and 8, an image type database 100 and a color database 300 are first constructed to match a personal color suitable for a user wishing to consult (step S10)

The image type database 100 and the color database 300 can be constructed by accumulating data of users who have performed consulting in the past.

As shown in FIG. 2, the image type database 100 includes facial image data 110 associated with a plurality of facial images, a type group 120 classifying facial image data into eight facial image data 110 and facial image data 110, And the classification data 130 classified by the group 120 are respectively stored.

In the color database 300, color data 310 including 32 colors corresponding to eight type groups 120 and coordination data 320 applied according to the user's situation are stored.

After the image type database 100 and the color database 300 are constructed, if the user desires consulting, the user data associated with the user is input to the user information database 200 through the terminal 1 and the terminal 2 . (Step S20)

The user data stored in the user information database 200 includes user input data 210 directly input by a user who desires consulting and consultant input data 220 judged by the image consultant ).

The user data is data collectively determined by giving a first weight to the user input data 210 and giving a second weight greater than the first weight to the consultant input data 220. [

The data included in the user data may include a makeup face color, a face color, a face shape, a skin color, a hair color, a pupil color, a lens color, and the user data includes various data such as body size, Can be added.

Also, the user data may include status information such as a user's job, a favorite place, a meeting type, a favorite travel destination, and the like.

When the user data is input to the user information database 200, the image type selection module 400 selects the user data input in the user information database 200 and the face image data 110 stored in the image type database 100, And compares the user data and the face image data 110 to extract the face image data 110 similar to the user data.

If the facial image data 110 similar to the user's data can not be extracted from the image type database 100, the image type database 100 outputs the user's data to the terminal 2 215 managed by the consultant, Allows the consultant to select the type group of the user from the user's input data.

When the image type selection module 400 extracts the face image data most similar to the user data, the image type selection module 400 searches the classification data 130 corresponding to the extracted face image data, The main type group and the sub-main type group of the user who desires to receive the consulting from the user (step S30)

When the main type group and the subtype group of the user wishing to consult by the image type selection module 400 are selected, the color matching module 500 selects the color type corresponding to the subtype group selected and determined from the color database 300 The personal color of the user who desires consulting is extracted from the data 310 (step S40)

The personal color information is provided to terminal 2 (215) managed by the image consultant. The personal color information may be provided not only to the terminal 2 215 managed by the image consultant but also to the terminal 1 205 of the user.

On the other hand, after the main type group and the subtype group of the user are determined, the color matching module 500 determines whether the user who desires consulting inputs status information such as job, meeting type, travel, and the like, (Step S50), the coordination data suitable for a plurality of colors included in the subtype group of the user is extracted using the coordination data 320 included in the color database 300. [ (Step S60)

As described above in detail, matching a face data of a user who desires consulting with a plurality of face image data of a database, selects a plurality of type groups suitable for the user's image, selects a personal color included in the type group And provides the coordination color suitable for the user's situation among the personal colors, so that it is possible to improve the image of the user by applying the color best suited to the image of the user to the clothes, accessories, bags, shoes and the like.

It should be noted that the embodiments disclosed in the drawings are merely examples of specific examples for the purpose of understanding, and are not intended to limit the scope of the present invention. It will be apparent to those skilled in the art that other modifications based on the technical idea of the present invention are possible in addition to the embodiments disclosed herein.

100 ... image type database 200 ... user information database
300 ... color database 400 ... image type selection module
500 ... color matching module 600 ... main control unit
700 ... Personal Color Matching System

Claims (10)

A face image data corresponding to a plurality of face images, a plurality of type groups set by a consultant, and an image type database storing classification data classified by the type groups;
A user information database for storing user data inputted based on a face image of a user wishing to consult;
A color database for storing color data for each type group;
An image type selection module for extracting face image data similar to the user data from the face image data by comparing the input user data with the face image data and extracting a type group from the classification data corresponding to the extracted face image data; ;
A color matching module for extracting the color data corresponding to the extracted type group from the color database; And
The image type selection module and the main control unit controlling the color matching system. The method according to claim 1,
Wherein the face image data includes at least one of facial color data including facial color, facial shape data, non-dyed or dyed hair color data, lens non-fusing or lens wearing pupil color data including bare face color or makeup facial color Personal color matching system. The method according to claim 1,
The user information database includes a user input database storing user input data input by the user and a consultant input database storing consultant input data inputted by an image consultant judging the user's face image,
The personal color matching system according to claim 1, wherein the color database stores coordinate data suitable for occupation, socialization, event, and travel for each type group. The method of claim 3,
Wherein the image type selection module applies a user weight to the consultant input data and applies the user data having a second weight greater than the first weight value to the type group to determine the image type of the user A personal color matching system to extract. The method of claim 3,
Wherein the color matching module compares the situation data with the situation data including job information, social information, event information, and travel information from the user, and selects the coordination data corresponding to the situation. The method according to claim 1,
Wherein the type group is divided into eight groups, and the color data corresponding to each type group includes 32 colors. A face image database including a face image data corresponding to a plurality of face images, a type group and a type group based on face image data, and classification data obtained by classifying the face images into a plurality of groups by face image data, Constructing a color database including colors;
Inputting user data associated with the user's face image in a user information database;
Extracting facial image data similar to the user data from facial image data by comparing facial image data corresponding to a plurality of facial images stored in an image type classification database using the image type selection module and the user data, Comparing face image data with classification data to determine the type group of the user from the classification data; And
And extracting a color corresponding to the type group of the user from a color database in which a plurality of color data is stored using the color matching module. 8. The method of claim 7,
The step of inputting the user data includes: directly inputting user input data by a user using the terminal 1; And
And using the terminal 2, the consultant inputs the consultant data judging the face image of the user. 8. The method of claim 7,
Wherein the type group comprises eight groups, and wherein the color data corresponding to each of the type groups comprises 32 colors. 8. The method of claim 7,
Wherein the step of inputting the user data related to the face image of the user to the user information database includes inputting situation data including the user's job information, social information, event information, and travel information,
Further comprising the step of, when the status data is inputted, selecting color suitable for the user's condition by comparing the status data and the coordination data suitable for occupation, socialization, ceremony and travel stored in the color database, Way.

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