KR102195033B1 - Big Data Molding Consulting System - Google Patents

Abstract

An objective of the present invention is to provide a big data cosmetic surgery consulting system for providing a cosmetic surgery prediction image and a lifestyle predicted by the cosmetic surgery prediction image which improves the reliability of cosmetic surgery to undergo the cosmetic surgery in a stable mind. According to the present invention, the big data cosmetic surgery consulting system for providing a cosmetic surgery prediction image and a lifestyle predicted by the cosmetic surgery prediction image comprises: a big data collection unit to collect big data for a pre-cosmetic surgery image and a post-cosmetic surgery image of a cosmetic surgery patient who has undergone cosmetic surgery; a big data analysis unit to divide the pre-cosmetic surgery image and the post-cosmetic surgery image collected by the big data collection unit into portions of the face, analyze the change of each portion of the pre-cosmetic surgery image and the post-cosmetic surgery image to extract a cosmetic surgery portion, and display the extracted cosmetic surgery portion on the pre-cosmetic surgery image and the post-cosmetic surgery image; a cosmetic surgery applicant analysis unit to receive a non-cosmetic surgery face image before cosmetic surgery from a cosmetic surgery applicant who wants to have cosmetic surgery, divide the face from the received non-cosmetic surgery face image into portions to provide the portions for the cosmetic surgery applicant, and receive a desired cosmetic surgery portion from the cosmetic surgery applicant; an image extraction unit to extract a plurality of pre-cosmetic surgery images similar to the non-cosmetic surgery face image from the big data connection unit, extract post-cosmetic surgery images corresponding to the extracted pre-cosmetic surgery images, and extract only post-cosmetic surgery images with a displayed cosmetic surgery portion matching the desired cosmetic surgery portion among the extracted plurality of post-cosmetic surgery images; and a big data prediction unit to apply the cosmetic surgery portion displayed on the post-cosmetic surgery images extracted by the image extraction unit to the non-cosmetic surgery face image to generate a cosmetic surgery prediction image, and provide the cosmetic surgery prediction image for the cosmetic surgery applicant.

Description

Big Data Molding Consulting System that provides the expected molding image and the expected lifestyle through the expected molding image {Big Data Molding Consulting System}

The present invention relates to a big data molding consulting system that provides an expected molding image and a lifestyle expected through the expected molding image.

Plastic surgery is a surgery that externally corrects a person's body or face. In the past, it was recognized as a surgery required by a special class, but as plastic surgery is gradually recognized as a beauty concept, it is now common and common among the general public. It is being established with human surgery.

People who wish to have plastic surgery are curious about their appearance after plastic surgery. In order to solve this curiosity, the created virtual post-molding image is provided to a person through a 3D virtual molding program or Photoshop. Through the image provided in this way, you can imagine the appearance after molding.

However, since the virtual post-molding image is only made as an imagination after the shaping, a lot of complaints occurred when it was different from the actual shape after shaping.

In addition, surgery is judged by looking at the actual plastic surgery, but due to differences in the shape of the face, color of the face, and facial features excluding surgery, the patient's appearance and the applicant's post-surgery are different. There was a problem with this occurring.

Republic of Korea Patent Publication 10-2019-0079215

The object of the present invention, conceived in order to solve the above-described problems, is to collect big data on the image before and after the plastic surgery of the plastic surgeon to extract the plasticized area, and to form the desired area of the plastic surgery. The performance of the big data predictor can be further improved by evaluating the predictive degree of the big data predictor based on the similarity between the face image and the predicted plastic image, as well as generating the predicted plastic image by applying the operator's plastic part to the unshaped face image. In addition to securing existing data, it generates motivation for plastic surgery for plastic surgery applicants, and improves the reliability of plastic surgery so that plastic surgery can be performed with a stable mind, and the expected life through the plastic surgery image. It is to provide a big data molding consulting system that provides style.

In addition, it is an object of the present invention to extract an online clothing image including the personal color of the cosmetic applicant from the online image so that the cosmetic candidate can find a better life after the cosmetic surgery, It is to provide a big data molding consulting system that provides the expected lifestyle through expected images.

In addition, the object of the present invention is to provide a cosmetic style, a clothing style, an accessory style, a food style, a travel style, and a specific user through online images and text data and comments uploaded to the SNS of a specific user similar to the face after the cosmetic surgery. By analyzing the lifestyle including the makeup style and providing it to the cosmetic applicant, the cosmetic applicant can refer in advance to the style of clothing, accessories, makeup, etc. that suits their changing face after cosmetic surgery through the lifestyle of others. If you are satisfied with the user's lifestyle, it will motivate plastic surgery, and a big data plastic surgery consulting system that provides a plastic surgery projected image that allows you to perform plastic surgery through trust in plastic surgery and a lifestyle expected through the plastic surgery projected image. It is to provide

According to the big data molding consulting system that provides the expected molding image of the present invention to achieve the above object and the lifestyle expected through the expected molding image, the image before and after the molding of the plastic surgeon who completed the molding. A big data collection unit that collects big data on images; The pre-molding image and the post-molding image collected by the big data collection unit are divided by parts based on the face, and the change of the pre-molding image and the post-molding image is analyzed to extract the molded part, and the extracted molded part is recalled. Big data analysis unit for displaying the image before and after the molding; Receives an unshaped face image before plastic surgery from a plastic surgeon who wishes to undergo plastic surgery, divides the received non-shape face image by part based on the face and provides it to the plastic surgery candidate, and provides the desired plastic surgery area from the plastic surgery candidate. A plastic surgery candidate analysis unit receiving input; Extracting a plurality of pre-molding images similar to the unmolded face image from the big data collection unit, extracting a post-molding image corresponding to the extracted pre-molding image, and forming a shape matching the desired area of the extracted multiple post-molding images An image extracting unit that extracts only the post-molded image in which the portion is displayed; A big data prediction unit for generating a shaping prediction image by applying the shaping portion displayed in the post-molding image extracted from the image extracting unit to the unmolded face image, and providing it to the shaping applicant; And a first degree of similarity between the cosmetic face image and the expected cosmetic image after the cosmetic candidate, and a second degree of similarity for each of the cosmetic regions of the cosmetic face image and the expected cosmetic image. And a big data evaluation unit that calculates a weighted average by setting the weight higher, and evaluates the predictability of the big data prediction unit through the weighted average.

In addition, a lifestyle that extracts an online similar image similar to the expected cosmetic image from among online images uploaded and published on SNS, analyzes the lifestyle of a specific user who uploaded the online similar image, and provides it to the cosmetic applicant. It further includes;

In addition, a color information analysis unit that analyzes color information for each part of the pre-shaping image, post-shaping image, and unshaped face image; further comprising, the big data prediction unit, forming the post-shaping image extracted from the image extracting unit. After converting the part and the desired part of the unformed face image into grayscale, the converted part of the grayscale that is desired to be formed is replaced with the molding part, and the replaced part of the grayscale is replaced with the desired part of the unformed face image. It is characterized in that by converting the color information of the region to generate a color predictive image.

In addition, a contour line extracting unit for extracting the first facial contour line of the unshaped face image, and overlapping a plurality of colors on the outer portion based on the first facial contour line, and selecting any one color from the cosmetic applicant. A specific color extracting unit that is selected and extracts a specific color, and the seasonal colors pre-classified by four season types are overlapped on the outer portion of the first facial contour line to select one or more seasonal colors from the cosmetic applicant. The extracted seasonal color extraction unit and the detailed colors pre-categorized into 1 to 8 seasonal colors extracted by the seasonal color extraction unit according to changes in brightness and saturation are overlapped on the outer part of the first facial contour line, A personal color selection unit including a detailed color extraction unit for selecting and extracting at least one detailed color from the; further comprising, the lifestyle providing unit, the seasonal color extracted by the seasonal color extraction unit from the online image and the detailed color extraction unit It characterized in that the on-line clothing image including the clothing color corresponding to the detailed color is extracted and provided to the cosmetic applicant.

In addition, the contour line extracting unit extracts a second facial contour line from the online clothing image, and extracts a third facial contour line from the molding predicted image, and the online clothing image is based on the second facial contour line. By overlapping the face of the expected plastic image, which is the inner part based on the third facial contour line, on the inner part, the face of the expected plastic image of the desired person is synthesized with the face of the online clothing image. .

In addition, the lifestyle providing unit is a lifestyle including the makeup style, clothing style, accessory style, food style, travel style and makeup style of the specific user through online images and text data and comments uploaded to the SNS of the specific user. It is characterized by analyzing the style.

In addition, the cosmetic candidate analysis unit extracts the online image uploaded to the SNS account of the cosmetic applicant after the cosmetic applicant completes the cosmetic, and among the extracted online images, the number of online images similar to the unformed face image of the cosmetic applicant And extracting the number of online images similar to the cosmetic face image and the expected cosmetic image, and analyzing the upload increase/decrease rate of the online image before and after the cosmetic surgery

The lifestyle providing unit is characterized in that it evaluates the appearance confidence of the cosmetic candidate through the upload increase/decrease rate, and provides an evaluation of the appearance confidence of the cosmetic applicant after forming to another cosmetic applicant.

In addition, the big data collection unit analyzes the degree of similarity between the pre-molding image and the molded portion displayed on the post-molding image, and classifies the pre-molding image and the post-molding image into a plurality of groups according to the similarity, and the image extracting unit includes the When extracting the post-molding image, the big data collection unit extracts only the post-molding image displaying the shaping area matching the desired shaping area for each group classified by the big data collection unit, and the big data prediction unit is formed according to the shaping image extracted for each group. It is characterized in that the predicted image is generated for each group and provided to the desired person.

The effect of the present invention as described above is to collect big data about the image before and after the plastic surgery of the plastic surgeon to extract the plastic surgery area, and to unshape the plastic surgery area on the desired area that the plastic surgeon desires. Not only does it apply to the face image to generate the expected plasticity image, but also by evaluating the predictive degree of the big data prediction unit based on the similarity between the formed face image and the expected plasticity image, not only does it secure data that can further improve the performance of the big data prediction unit. , Big data plastic surgery that generates the motivation for plastic surgery of plastic surgery applicants, and provides a plastic surgery projected image that enables plastic surgery to proceed with a stable mind by improving the reliability of plastic surgery and a lifestyle expected through the plastic surgery projected image. A consulting system can be provided.

In addition, the effect of the present invention is to extract the online clothing image including the person's personal color from the online image so that the cosmetic applicant can find a better life after the cosmetic surgery, It is possible to provide a big data molding consulting system that provides an expected lifestyle through expected images.

In addition, the effect of the present invention is the cosmetic style, clothing style, accessory style, food style, travel style, and the online image and text data uploaded to the SNS of a specific user, and By analyzing the lifestyle including the makeup style and providing it to the cosmetic applicant, the cosmetic applicant can refer in advance to the style of clothing, accessories, makeup, etc. that suits their changing face after cosmetic surgery through the lifestyle of others. If you are satisfied with the user's lifestyle, it will motivate plastic surgery, and a big data plastic surgery consulting system that provides a plastic surgery projected image that allows you to perform plastic surgery through trust in plastic surgery and a lifestyle expected through the plastic surgery projected image. Can provide.

In addition, the effect of the present invention is that, rather than a consultation based on the subjective criteria of a consultant who consults for plastic surgery, the system provides an objective and professional consultation of the shape after plastic surgery. It is possible to provide a big data molding consulting system that provides a lifestyle expected through images.

1 is a block diagram showing a big data molding consulting system that provides an expected molding image and a lifestyle expected through the expected molding image according to a preferred embodiment of the present invention.
Figure 2 is an exemplary view showing the formation of an expected molding image of a big data molding consulting system that provides a predicted molding image and a lifestyle expected through the expected molding image according to a preferred embodiment of the present invention.

Advantages and features of the present invention, and a method of achieving them will become apparent with reference to the embodiments described below in detail together with the accompanying drawings. However, the present invention is not limited to the embodiments disclosed below, but may be implemented in a variety of different forms, and only these embodiments make the disclosure of the present invention complete, and are common knowledge in the technical field to which the present invention pertains. It is provided to completely inform the scope of the invention to those who have, and the invention is only defined by the scope of the claims. The same reference numerals refer to the same components throughout the specification.

Hereinafter, the present invention will be described with reference to the drawings for explaining a molding projected image and a big data molding consulting system that provides a lifestyle expected through the molding projected image according to embodiments of the present invention.

1 and 2, a big data molding consulting system that provides a predicted molding image 51 according to the present invention and a lifestyle expected through the predicted molding image 51 is, a big data collecting unit 10 , A big data analysis unit 20, a cosmetic candidate analysis unit 30, an image extraction unit 40, a big data prediction unit 50, and a big data evaluation unit 60.

The big data collection unit 10 collects big data about the image before and after the plastic surgery 11 of the plastic surgeon who has completed the plastic surgery.

At this time, big data is collected from a number of plastic surgery clinics. At this time, the pre-molding image and the post-molding image 11 include plastic surgery information such as the collected plastic surgeon, doctor, cost, and plastic surgery site 21.

In addition, the big data collection unit 10 converts the unshaped face image 31 of the person who will be described later into big data by adding a pre-molding image as a pre-molding image and a shaping face image as a post-molding image 11.

In addition, the unshaped face image 31, the molded face image, the pre-molded image and the post-molded image 11 are all photographed under the same environmental conditions, such as the same angle, lighting, and the proportion of the face on the image. This is a picture taken from a position such as the middle of the side. In addition, the plastic surgery applicant and the plastic surgeon are photographed with the same expression before and after the plastic surgery, but by taking multiple pictures before and after the plastic surgery with different facial expressions, it is possible to more easily grasp the changes before and after the plastic surgery.

The big data analysis unit 20 divides each part based on the face of the image before and after the molding 11 collected by the big data collection unit 10. Here, the segmented portion is forehead, brow, eyebrows, eyes, side cheekbones, front cheekbones, nose bridge, nose tip, nose cheek, cheek, Indian line, aegyosal, eyelid, nasolabial folds, chin, side chin, etc., but is not limited thereto.

In addition, the unshaped face image 31 of the person who wishes to undergo a cosmetic surgery, which will be described later, is also partitioned by region. The reason for partitioning the face by region is that the positions of the divided regions of the post-plastic image 11 and the unshaped face image 31 are the same By doing so, the image extracting unit 40 to be described later can extract the forming area 21 that matches the exact forming desired area 32, as well as the big data predicting unit 50 to obtain the expected forming image 51 This is to be able to create more accurately. In addition, the unmolded face image 31, the molded face image, the pre-molded image, and the post-molded image 11 are photographed under the same environmental conditions, so that extraction and application of each part are more easily performed.

In addition, the big data analysis unit 20 extracts the molded part 21 by analyzing the changes for each part of the image before and after the molding 11. In addition, the cosmetic site 21 may be extracted from the cosmetic surgery information. In analyzing the change, it is possible to analyze the amount of change (for example, change in size, change in position, etc.) to change the image before molding into the image after molding 11, and how to analyze the amount of change in the image is known. Since this is a technology, detailed description will be omitted.

At this time, the big data analysis unit 20 displays the molding part 21 on the pre-molding image and the post-molding image 11, or the molding part 21 extracted from the cosmetic surgery information and the extracted molding by analyzing the change of each part. If the parts 21 match, the matching molding parts 21 are displayed on the pre-molding image and the post-molding image 11.

Here, the molding part 21 refers to a part desired to be formed in the image before molding, and the post-molding image 11 refers to a part changed by actual molding.

In this way, the marking of the molding part 21 through the matching of the molding part 21 is applied to the molding part 21 of the plastic surgeon to the molding desired part 32 of the person who will be described later, and It is to make this clearer because it creates an expected image.

The plastic surgery candidate analysis unit 30 receives the unshaven face image 31 before plastic surgery from the plastic surgery candidate who wishes to undergo plastic surgery, and divides the received non-shaped face image 31 based on the face into each part To provide.

In addition, the molding desired person analysis unit 30 receives the desired molding region 32 from the molding desired person. Here, by making the number of inputted desired areas 32 to be received less than two, the overall change of the expected shaping image 51 and the unmolded face image 31 generated by the big data prediction unit 50 to be described later is reduced.

The plastic surgery candidate analysis unit 30 extracts the online image uploaded to the plastic surgery applicant's SNS account after the plastic surgery applicant has completed the plastic surgery, and among the extracted online images, an online image similar to the non-shaping face image 31 of the plastic surgery applicant. By extracting the number, and extracting the number of online images similar to the cosmetic face image and the expected cosmetic image 51, it is possible to analyze the increase/decrease rate of uploading of the online image before and after the forming of the desired person.

This can be analyzed whether or not a person wanting to be formed has public confidence in appearance after molding rather than before molding.

In addition, the molding applicant analysis unit 30 periodically analyzes the upload increase/decrease rate of the molding applicant who has completed the molding. By performing periodic analysis, it can be confirmed that appearance confidence changes immediately after plastic surgery.

The SNS in the present invention is to be able to upload photos, articles, comments, etc. to'Social Network Services/Sites', and the online image is an image that is disclosed to an unspecified number of people.

The image extracting unit 40 extracts a number of pre-molding images similar to the unmolded face image 31 from the big data collection unit 10, and extracts the post-molding image 11 corresponding to the extracted pre-molding image, Among the extracted plurality of post-molding images 11, only the post-molding image 11 in which the shaping portion 21 matching the desired shaping portion 32 is displayed is extracted.

In other words, the image extracting unit 40 extracts a pre-molding image that is generally similar to the face of a person who wishes to be formed, and among them, a post-molding image in which the forming area 21 matching the desired area 32 input by the forming person is displayed. Only (11) is extracted again.

Accordingly, the post-molding image 11 extracted through the image extracting unit 40 is generally similar to the face of a plastic surgeon, and is an image of a plastic surgeon who has undergone plastic surgery on the area that the plastic surgeon wishes for plastic surgery. By extracting the image of the plastic surgeon similar to the face of the desired plastic surgeon without extracting a random plastic surgeon image, and extracting the post-molding image 11 that matches the desired area 32 and the plastic area 21, It is possible to more accurately predict the predicted molding image after molding in a state that matches the desired conditions as much as possible.

The big data prediction unit 50 applies the shaping area 21 displayed in the post-molding image 11 extracted from the image extracting unit 40 to the unmolded face image 31 to generate a shaping predicted image 51. .

In addition, the big data prediction unit 50 provides a formed prediction image 51 to a person who wishes to undergo a surgery. At this time, the person who wishes to undergo molding can virtually confirm the after molding through the expected molding image 51.

On the other hand, the big data collection unit 10 analyzes the similarity of the molding area 21 displayed on the pre-molding image and the post-molding image 11, and converts a plurality of pre-molding and post-molding images 11 according to the similarity. Classify into groups. For example, according to the ratio of similarity, 0-30% can be classified into large groups, 31-70% are classified into medium groups, and 71-100% can be classified into small groups.

The large group is a group with large changes before and after surgery due to small similarity, the small group is a group with little change, and the middle group is a middle group between large and small groups.

And, the image extracting unit 40, when extracting the image after the molding 11, the big data collection unit 10 classified by groups, the molding area 21 matching the desired area 32 and the molding is displayed. Only the rear image 11 is extracted.

In addition, the big data prediction unit 50 generates a molding predicted image 51 for each group according to the post-molding image 11 extracted for each group, and provides it to the desired person for molding.

Accordingly, the plastic surgery applicant can check the predicted degree of change by group through the before and after molding projection images 51 provided for each group, and select a group suitable for the plastic surgery applicant.

In addition, the plastic surgery applicant can grasp and select the ratio with other facial areas through the degree of change through the three groups of expected plastic images 51, and according to the selection, the satisfaction of plastic surgery can be improved.

In addition, as the molding expected image is replaced with a molding part, the cosmetic surgery information of the post-molding image in which the molding part is displayed is included.

Accordingly, when a plastic surgery applicant selects a plastic surgery prediction image, it is possible to check the plastic surgery information included in the plastic surgery prediction image, and check the plastic surgery clinic, doctor, cost, etc. who can perform plastic surgery suitable for them.

In addition, the Big Data Prediction Department, when a cosmetic surgery reservation is requested for a cosmetic surgery image from a cosmetic applicant, transfers the cosmetic surgery image and personal information of the cosmetic surgery candidate to the plastic surgery clinic through the cosmetic surgery information included in the cosmetic surgery image to make a reservation. To achieve this, connect the plastic surgeon and the plastic candidate.

In addition, when a plastic surgery applicant selects a plastic surgery prediction image, they can check the plastic surgery information corresponding to the plastic surgery part included in the plastic surgery prediction image, and check the plastic surgery clinic, doctor, and cost that can perform plastic surgery suitable for them. .

The big data evaluation unit 60 analyzes the overall first similarity of the cosmetic face image and the anticipated cosmetic image 51 after the cosmetic candidate, and the second similarity with respect to each forming part of the cosmetic face image and the anticipated cosmetic image. . Here, the shaping applicant analysis unit 30 receives the shaping face image after shaping from the shaping hope.

At this time, the big data evaluation unit 60 calculates a weighted average by setting the weight of the second similarity higher than that of the first similarity degree, and evaluates the predictive degree of the big data prediction unit 50 through the weighted average.

Here, since there are parts that change on the face, such as losing weight due to diet after plastic surgery, rather than evaluating the predictive degree of the big data prediction unit 50 through only the first similarity that analyzed the similarity of the overall face, only the molded area Further evaluation by adding a second degree of similarity analyzed intensively for similarity can more accurately evaluate the predicted degree of the molding predicted image 51.

In this way, by numerically converting the predicted degree of the expected plastic image 51, the plastic candidate can have more confidence in his/her expected plastic image 51 and the face after the plastic surgery, and can be used to determine whether or not the plastic surgery is performed.

In addition, the deep learning unit automatically performs machine learning to extract the differences by comparing the molding part 21 of the molding face image and the molding hope part 32 of the expected molding image 51, and to reduce the difference. Thus, the algorithm of the big data prediction unit 50 that generates the predicted image 51 is updated.

At this time, the big data prediction unit 50 generates a molding predictive image 51 of another plastic candidate with the updated algorithm, and the big data evaluation unit 60 increases the prediction degree of the big data prediction unit 50. Evaluation, and the big data molding consulting system of the present invention is improved.

On the other hand, the big data molding consulting system, which provides a predicted molding image 51 and a lifestyle expected through the predicted molding image 51 according to the present invention, includes a lifestyle providing unit 70, a color information analyzing unit 80 ) And a personal color selection unit 90.

The lifestyle providing unit extracts an online similar image similar to the expected cosmetic image 51 from among online images uploaded and published on SNS, and analyzes the lifestyle of a specific user who uploaded the online similar image and provides it to the cosmetic applicant. do. In addition, the lifestyle providing unit 70 may additionally provide an online similar image of a specific user.

A specific user is the shape of the future of a person who wishes to undergo plastic surgery, and provides a lifestyle after plastic surgery in addition to the expected image 51 for plastic surgery, thereby motivating the plastic surgery and giving an expectation for a change in life.

In addition, the lifestyle providing unit 70 analyzes the lifestyle of a specific user through online images, text data and comments uploaded to the SNS of the specific user.

At this time, the lifestyle includes a makeup style, a clothing style, an accessory style, a food style, and a travel style. In addition, it is possible to analyze the lifestyle by further extracting brands such as cosmetics, clothing, and accessories. In this case, the lifestyle of a specific user may be the content analyzed by the lifestyle consultant.

The makeup style can be analyzed from the color of a specific user's face in the online image, the clothing style can be analyzed by types such as coat, hat, scarf, pants, shoes, and the accessory style can be analyzed by the size of earrings, necklaces, etc. can do. In addition, in the case of a brand, it can be analyzed through images similar to clothing and accessories recommended by a lifestyle consultant or worn by a specific user online.

In addition, the lifestyle providing unit 70 may provide a lifestyle for a plurality of specific users.

The cosmetic applicant may think of a lifestyle similar to or similar to that of a specific user as the appearance after the cosmetic surgery, and may have an opportunity to change the lifestyle of the cosmetic applicant in a better direction by referring to the lifestyle of a specific user. In addition, plastic surgery applicants may be motivated for plastic surgery through the lifestyle of a specific user, further improve the confidence in plastic surgery, reduce the feeling of lightness after plastic surgery, and engage in plastic surgery.

The lifestyle providing unit 70 evaluates the appearance confidence of the cosmetic candidate through the upload increase/decrease rate, and provides an evaluation of the cosmetic appearance confidence of the cosmetic applicant to another cosmetic applicant. Evaluation can be provided as an increase, a maintenance, a decrease, etc., depending on the upload rate.

Accordingly, if another plastic surgery applicant confirms that the evaluation of the appearance confidence of the plastic surgery candidate or the plastic surgeon has increased, it may be a motivation for the plastic surgery. You can take the time to consider carefully. For this reason, it is possible to make an objective judgment on plastic surgery, and it is possible not to perform excessive plastic surgery.

In addition, the lifestyle providing unit 70 may also provide information of a hospital or a doctor who directly performed surgery on a person who wishes to undergo a plastic surgery or a plastic surgeon.

In addition, the lifestyle providing unit 70 also periodically evaluates the appearance confidence according to the upload increase/decrease rate analyzed periodically, and provides the appearance confidence assessment for a certain period of time. During a certain period, if the upload increase/decrease rate increases rapidly, the cosmetic surgeon's appearance confidence has risen. Therefore, not only is it judged as satisfaction with the cosmetic surgery, but also swelling after plastic surgery is removed from the point when the upload increase/decrease rate increases rapidly, etc. It is judged as the period until disappears and becomes natural.

Plastic surgery applicants can check the change in appearance confidence of the plastic surgeon or the plastic surgeon who had previously undergone surgery, and anticipate the period of a sudden increase in upload increase or decrease after the plastic surgery.

Ordinary plastic surgeons have anxiety immediately after plastic surgery because they think that plastic surgery is wrong due to swelling and surgical marks on the surgical site. This anxiety can be relieved and stabilized through changes in the appearance confidence of the plastic surgeon who has formed the same area as the plastic surgery candidate, and the plastic surgery candidate lives a stable daily life immediately after the plastic surgery, and can wait until the surgery site becomes natural.

The color information analysis unit 80 analyzes the color information for each part of the pre-molding image, the post-molding image 11 and the unmolded face image 31. In this case, the pre-molding image and the post-molding image 11 are the shaping area 21, and the unmolded face image 31 is the desired shaping area 32, but is not limited thereto.

The big data prediction unit 50 converts the shaping portion 21 of the post-molded image 11 extracted from the image extracting unit 40 and the desired shaping portion 32 of the unformed face image 31 into gray scale. After that, the converted gray-scale shaping portion 32 is replaced with the shaping portion 21, and the gray-scale shaping portion 21 replaced with the unmolded face image 31 is replaced with the unmolded face image 31. The desired area 32 is converted into color information to generate a color predicted image 51.

This is because the color of the face of the plastic surgeon is different from that of the plastic surgeon, so the color of the shaping area 21 replaced in the unshaped face image 31 is converted to the color of the desired area 32, so that the expected shaping image 51 is maximized. This is to make it look natural. And by looking at the expected plastic image 51 in which only the desired area 32 has been changed while maintaining the color of his face in his unshaped face image 31, the person who wishes to undergo plastic surgery can have more confidence in plastic surgery.

The personal color selection unit 90 may analyze the personal color of the person who wishes to undergo cosmetic surgery and provide it to the person who wishes to undergo cosmetic surgery to help them have a lifestyle.

The personal color selection unit 90 classifies a specific color as a seasonal color, and selects a personal color using a color classified as a detailed color by changing the brightness and saturation of the seasonal color.

The personal color selection unit 90 includes an outline line extraction unit, a specific color extraction unit, and a detailed color extraction unit.

The contour line extracting unit extracts the first facial contour line of the unformed face image 31.

The specific color extracting unit overlaps a plurality of colors on the outer portion based on the first facial contour line, and extracts a specific color by selecting any one color from a person who wishes to form the shape.

At this time, the specific color refers to primary colors such as red, pink, yellow, green, blue, and brown, and may include another color. With this specific color, it is possible to grasp the color that suits the person who wishes to make a cosmetic.

The seasonal color extracting unit extracts one or more seasonal colors selected from a cosmetic applicant by overlapping the seasonal colors pre-categorized by four season types on the outer portion of the first facial contour line. At this time, through the specific color, it is possible to grasp the seasonal color that suits the person who wishes to make a cosmetic.

For example, if the specific color is yellow, the seasonal colors classified yellow into four seasons according to the Japanese color research color scheme are compared to those who wish to make cosmetic products to determine which season colors match.

It is classified into the seasonal colors of spring, summer, autumn, and winter through the Japanese PCCS (Japanese Color Research Coloration System) color table.

The colors of spring are vivid, strong, light, and pale.

Summer colors are dull, grayish, soft, light grayish, pale, and white.

The colors of autumn are soft, dull, dark, and deep colors.

Winter colors are white, soft, vivid, blackish, and dark.

The detailed color extraction unit overlaps the outer portion of the first facial contour line with the detailed colors pre-categorized into 1 to 8 seasonal colors extracted by the seasonal color extraction unit according to the change in brightness and saturation to obtain one or more detailed colors from the shaper. Select and extract.

For example, when comparing the four season colors of yellow, if a person who wants to make a shape selects a summer season color, the yellow color of the selected summer season is compared with the detailed colors classified by changes in brightness and saturation. And the cosmetic applicant chooses one of the detailed colors.

In this way, the seasonal colors and detailed colors that suit the cosmetic applicant become the personal color of the cosmetic applicant.

The lifestyle providing unit 70 extracts an online clothing image including a seasonal color extracted by the seasonal color extraction unit and a clothing color corresponding to the detailed color extracted by the detailed color extraction unit from the online image and provides it to a cosmetic applicant.

Accordingly, a person who desires to make a cosmetic can look at clothing that suits him or her through the online clothing image provided by the lifestyle providing unit 70, and change his or her lifestyle through personal color and online clothing image. have.

On the other hand, the contour line extracting unit extracts the second facial contour line from the online clothing image, and extracts the third facial contour line from the molding predicted image 51.

At this time, the big data prediction unit 50 predicts the online clothing image by overlapping the face of the plastic predicted image 51, which is an inner part, based on the third facial contour line on the inner part based on the second facial contour line. .

The predicted online clothing image is an image in which the face of the predicted plastic image 51, which is an inner part based on the third facial contour line, overlaps with the inner part based on the second facial contour line. In other words, the online clothing image is a state in which the face of the expected cosmetic image 51 of a cosmetic candidate is synthesized with the face of the online clothing image.

Through this, a person who wishes to undergo plastic surgery can indirectly check his or her appearance after plastic surgery, while also viewing the appearance of wearing clothing of a color that suits them.

Through the big data molding consulting system that provides the expected molding image 51 of the present invention and the expected lifestyle through the expected molding image 51, not only the molding but also the future shape after molding is predicted. In addition to motivating them, they have a sense of trust in plastic surgery.

On the other hand, the unshaped face image is the image before the cosmetic candidate puts on makeup.

In addition, the big data analysis unit extracts the online image uploaded to SNS before the plastic surgery applicant is plasticized, and compares the unshaped face image with the online image.

At this time, the big data analysis unit divides the unshaped face image and the online image for each part based on the face, and then compares the degree of difference for each divided part. And, the area with the largest difference is selected as the expected plasticity area.

At this time, the big data prediction unit may also deliver the expected plastic surgery area to the plastic surgery clinic.

In addition, the plastic surgeon who received the expected area of plastic surgery can grasp the individual beauty standards of the desired person through the expected area, determine whether or not plastic surgery is possible considering the expected area and the area desired for plastic surgery, and have a more smooth consultation with the desired plastic surgery. have.

Those of ordinary skill in the art to which the present invention pertains will appreciate that the present invention can be implemented in other specific forms without changing the technical spirit or essential features thereof. Therefore, it should be understood that the embodiments described above are illustrative in all respects and not limiting. The scope of the present invention is indicated by the scope of the claims to be described later rather than the detailed description, and all changes or modified forms derived from the meaning and scope of the claims and their equivalent concepts are included in the scope of the present invention. Must be interpreted. In addition, the order of operation of the configurations described in the above-described process does not necessarily need to be performed in a time-series order, and even if the execution order of each configuration and step is changed, if the gist of the present invention is satisfied, such a process will fall within the scope of the present invention. Of course you can.

10: Big data collection unit 11: Image after molding
20: big data analysis unit 21: molding area
30: plastic surgery candidate analysis unit 31: unshaped face image
32: desired area for forming 40: image extraction unit
50: big data prediction unit 51: expected plastic surgery image
60: Big Data Evaluation Department 70: Lifestyle Provision Department
80: color information analysis department 90: personal color selection department

Claims (8)

A big data collection unit that collects big data on the image before and after the plastic surgery of the plastic surgeon who has completed the plastic surgery;
The pre-molding image and the post-molding image collected by the big data collection unit are divided by parts based on the face, and the change of the pre-molding image and the post-molding image is analyzed to extract the molded part, and the extracted molded part is recalled. Big data analysis unit for displaying the image before and after the molding;
Receives an unshaped face image before plastic surgery from a plastic surgeon who wishes to undergo plastic surgery, divides the received non-shape face image by part based on the face and provides it to the plastic surgery candidate, and provides the desired plastic surgery area from the plastic surgery candidate. A plastic surgery candidate analysis unit receiving input;
Extracting a plurality of pre-molding images similar to the unmolded face image from the big data collection unit, extracting a post-molding image corresponding to the extracted pre-molding image, and forming a shape matching the desired area of the extracted multiple post-molding images An image extracting unit that extracts only the post-molded image in which the portion is displayed;
A big data prediction unit for generating a shaping prediction image by applying the shaping portion displayed in the post-molding image extracted from the image extracting unit to the unmolded face image, and providing it to the shaping applicant; And
Analyzing the overall first similarity of the cosmetic face image and the expected cosmetic image after the cosmetic candidate, and the second similarity for each cosmetic part of the cosmetic face image and the cosmetic predicted image, and the weight of the second similarity rather than the first similarity Including; a big data evaluation unit for calculating a weighted average by setting to higher, and evaluating the predictability of the big data prediction unit through the weighted average,
Further comprising a; color information analysis unit for analyzing the color information for each part of the pre-molding image, the post-molding image and the unmolded face image,
The big data prediction unit converts the shaping portion of the post-molded image extracted from the image extracting unit and the desired shaping portion of the unformed face image into gray scale, and then replaces the shaping desired portion of the converted gray scale with a shaping portion. , A molding projected image characterized in that the replacement grayscale molding part is converted into color information of the molding desired part of the unformed face image to generate a color molding projected image and a lifestyle expected through the molding projected image. Big data molding consulting system provided.
The method of claim 1,
A lifestyle providing unit that extracts an online similar image similar to the expected cosmetic image from among online images uploaded and published on SNS, analyzes the lifestyle of a specific user who uploaded the online similar image, and provides it to the cosmetic applicant A big data molding consulting system that provides an anticipated plastic surgery image and a lifestyle expected through the expected plastic surgery image.
delete The method of claim 2,
An outline line extracting unit for extracting a first facial outline line of the unshaped face image,
A specific color extracting unit that overlaps a plurality of colors on an outer portion based on the first facial contour line, and extracts a specific color by selecting one color from the person who wishes to form the shape;
A seasonal color extracting unit that selects and extracts one or more seasonal colors from the cosmetic applicant by overlapping the seasonal colors pre-categorized by four season types on the first facial contour line;
By overlapping the outer portion of the first facial contour line, the detailed colors, pre-categorized into 1 to 8 seasonal colors extracted by the seasonal color extracting unit according to the change in brightness and saturation, one or more detailed colors are selected from the cosmetic applicant. Further comprising; a personal color selection unit including a detailed color extraction unit to be extracted,
The lifestyle providing unit extracts an online clothing image including a seasonal color extracted by the seasonal color extraction unit and a clothing color corresponding to the detailed color extracted by the detailed color extraction unit from the online image and provides it to the cosmetic applicant. A big data plastic surgery consulting system that provides an expected plastic surgery image and a lifestyle expected through the expected plastic surgery image.
The method of claim 4,
The outline line extracting unit extracts a second facial contour line from the online clothing image, and extracts a third facial contour line from the molding predicted image,
The online clothing image overlaps the face of the expected shaping image, which is an inner part based on the third facial contour line, on the inner part based on the second facial contour line, so that the face of the shaping prospective image A big data cosmetic consulting system that provides an expected cosmetic image and a lifestyle predicted through the cosmetic image, characterized in that it is synthesized on the face of an online clothing image.
The method of claim 2,
The lifestyle providing unit,
Analyzing the lifestyle including the makeup style, clothing style, accessory style, food style, travel style, and makeup style of the specific user through the online image and text data and comments uploaded to the specific user's SNS. A big data plastic surgery consulting system that provides an expected plastic surgery image and a lifestyle expected through the expected plastic surgery image.
The method of claim 6,
The cosmetic candidate analysis unit,
After the cosmetic applicant completes the cosmetic surgery, extract the online image uploaded to the SNS account of the cosmetic applicant, extract the number of online images similar to the unformed face image of the cosmetic applicant among the extracted online images, and By extracting the number of online images similar to the expected cosmetic image, analyze the upload increase/decrease rate of the online image before and after the molding of the cosmetic candidate,
The lifestyle providing unit,
An expected cosmetic image and a lifestyle predicted through the cosmetic image, characterized in that it evaluates the appearance confidence of the cosmetic candidate through the upload increase/decrease rate, and provides an evaluation of the appearance confidence of the cosmetic applicant to another cosmetic applicant. Big data molding consulting system that provides.
The method of claim 1,
The big data collection unit analyzes the similarity of the molding area displayed on the pre-molding image and the post-molding image, and classifies the pre-molding image and the post-molding image into a plurality of groups according to the similarity,
The image extracting unit, when extracting the post-molding image, extracts only the post-molding image in which the shaping portion matching the desired shaping portion is displayed for each group classified by the big data collection unit,
The big data prediction unit generates a molding predicted image for each group according to the post-molding image extracted for each group and provides it to the desired person. Data molding consulting system.

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