KR-20260062259-A - ARTIFICIAL INTELLIGENCE-BASED SKIN DIAGNOSIS SYSTEM AND OPERATING METHOD USING THE SAME

KR20260062259AKR 20260062259 AKR20260062259 AKR 20260062259AKR-20260062259-A

Abstract

A method of operation for an artificial intelligence-based skin diagnosis system according to the present embodiment comprises: receiving at least one macro-photographed image information associated with a user's face from a personal mobile terminal device; generating face modeling information based on a plurality of feature points automatically recognized based on at least one macro-photographed image, wherein a plurality of face regions for the face modeling information are set; generating skin patch information for each of the plurality of face regions based on at least one macro-photographed image information; receiving at least one micro-photographed image information for each of the plurality of face regions; performing a face mapping operation for a user based on the skin patch information and at least one micro-photographed image information; and generating customized skin care solution information for a user based on mapping information and at least one micro-photographed image information according to the face mapping operation.

Inventors

임태호
최창영

Assignees

헬스클라우드(주)

Dates

Publication Date: 20260507
Application Date: 20241028

Claims (9)

In a method of operation for an artificial intelligence-based skin diagnosis system, A step of receiving at least one macro-photographed image information associated with the user's face from a personal mobile terminal device; Face modeling information is generated based on a plurality of automatically recognized feature points based on at least one macro-captured image, wherein A step of setting a plurality of face regions for the above-mentioned face modeling information; A step of generating skin patch information for each of the plurality of face regions based on at least one macro-captured image information; A step of receiving at least one micro-captured image information for each of the plurality of face regions; A step of performing a facial mapping operation for the user based on the above skin patch information and the above at least one micro-captured image information; and A method comprising the step of generating customized skin care solution information for the user based on mapping information according to the above facial mapping operation and at least one micro-captured image information.
In Article 1, The above artificial intelligence is implemented based on a pre-trained learning model, and, A method characterized by the fact that the plurality of feature points are implemented to be recognized by the learning model in a predetermined number.
In Article 1, In each of the above plurality of face zones, a plurality of skin patch units according to a predetermined number are set, and A method characterized in that the above skin patch information includes a plurality of skin condition prediction data corresponding to the plurality of skin patch units.
In Paragraph 3, The above plurality of skin condition prediction data are generated based on R, G, and B information included in the at least one macro-captured image information, and A method characterized in that the plurality of skin condition prediction data are associated with pore condition information, acne condition information, sebum condition information, pigmentation condition information, wrinkle condition information, and sensitivity information of the facial area.
In Paragraph 3, The step of performing the above facial mapping operation is, A method comprising the step of searching for a skin patch unit corresponding to the skin condition prediction data that has the highest similarity to at least one skin condition measurement data obtained from at least one micro-photographic image information among the plurality of skin condition prediction data.
In Article 5, The above at least one skin condition measurement data is generated based on R, G, and B information included in the above at least one micro-imaging image information, and A method characterized in that the above-mentioned at least one skin condition measurement data is associated with the pore condition indicator, acne condition indicator, sebum condition indicator, pigmentation indicator, wrinkle condition indicator, and sensitivity indicator of the facial area.
In Article 5, A method characterized by the fact that the above mapping information is implemented to indicate the above-mentioned searched skin patch unit.
In Article 7, A method characterized by generating the above customized skin care solution information based on the above mapping information and the above at least one skin condition measurement data.
At least one personal mobile terminal device of the user; At least one individual skin diagnostic terminal device linked to the above at least one personal portable terminal device; and A server device linked to at least one personal mobile terminal device, wherein The above server device is, It is implemented to receive at least one macro-shot image information associated with the facial portion of the user from the personal mobile terminal device, and It is implemented to generate face modeling information in which a plurality of face regions are set according to a plurality of feature points automatically recognized based on at least one macro-captured image, and It is implemented to generate skin patch information for each of the plurality of face regions based on at least one macro-captured image information, and It is implemented to receive at least one micro-captured image information for each of the plurality of face regions above, and It is implemented to perform a facial mapping operation for the user based on the above skin patch information and the above at least one micro-captured image information, and An artificial intelligence-based skin diagnostic system implemented to generate customized skin care solution information for the user based on mapping information according to the above facial mapping operation and at least one micro-captured image information.

Description

Artificial Intelligence-Based Skin Diagnosis System and Operating Method Using the Same The present specification relates to an artificial intelligence-based skin diagnosis system and a method of operation using the same, and more specifically, to an artificial intelligence-based skin diagnosis system and a method of operation using the same that utilizes macro image information captured by a personal mobile terminal device and micro image information captured by an individual skin diagnosis terminal device. With the recent advancement of artificial intelligence (AI) technology, research on skin disease diagnosis and management systems is actively underway. Traditional skin diagnostic methods relied primarily on the experience of doctors or experts and visual evaluation, but these methods had limitations in terms of diagnostic accuracy and consistency. To overcome this, an AI-based skin diagnostic system has been introduced, and not only is the diagnostic accuracy being improved through the use of image processing, machine learning algorithms, and deep learning algorithms, but the reliability of the diagnosis is also being enhanced by learning various skin types and disease data in conjunction with big data. Meanwhile, technology that monitors the user's skin condition in real time and suggests customized skincare solutions is also being introduced. Refer to Korean Published Patent No. 10-2023-0161131, which mentions an 'artificial intelligence-based skin diagnosis method' as a prior proposal. FIG. 1 is a conceptual diagram for an artificial intelligence-based skin diagnosis system according to the present embodiment. FIG. 2 is a block diagram for a server device for an artificial intelligence-based skin diagnosis system according to the present embodiment. FIG. 3 is an example diagram showing face modeling information according to the present embodiment. FIG. 4 is an illustrative diagram for explaining the facial mapping process according to the present embodiment. FIG. 5 is a flowchart illustrating a method of operation for an artificial intelligence-based skin diagnosis system according to the present embodiment. FIG. 6 is a block diagram illustrating a computing environment including a computing device suitable for use in an exemplary embodiment. The aforementioned characteristics and the detailed description below are all exemplary matters to aid in the explanation and understanding of this specification. That is, this specification is not limited to such embodiments and may be embodied in other forms. The following embodiments are merely examples to fully disclose this specification and are intended to convey this specification to those skilled in the art to which this specification belongs. Accordingly, if there are multiple methods for implementing the components of this specification, it is necessary to make clear that the specification can be implemented by any of these specific methods or any method identical thereto. Where in this specification it is mentioned that a configuration includes specific elements, or that a process includes specific steps, it implies that other elements or steps may be additionally included. That is, the terms used in this specification are intended only to describe specific embodiments and are not intended to limit the concept of this specification. Furthermore, the examples described to aid in understanding the invention also include complementary embodiments. The terms used in this specification have the meanings generally understood by those skilled in the art to which this specification pertains. Commonly used terms should be interpreted in a consistent sense according to the context of this specification. Furthermore, terms used in this specification should not be interpreted in an overly idealistic or formal sense unless their meaning is clearly defined. Embodiments of this specification are described below with reference to the attached drawings. FIG. 1 is a conceptual diagram for an artificial intelligence-based skin diagnosis system according to the present embodiment. Referring to FIG. 1, an artificial intelligence-based skin diagnosis system (100) according to the present embodiment may include a personal mobile terminal device (110_1), an individual skin diagnosis terminal device (110_2), and a server device (120). The personal mobile terminal device (110_1) of FIG. 1 may correspond to a user's mobile terminal that has a predetermined application app installed for the artificial intelligence-based skin diagnosis system (100) according to the present embodiment. For example, a personal mobile terminal device (110_1) can generate at least one macro-photographed image information associated with the user's face. Here, at least one macro-shot image information may include R, G, B information according to a preset image quality (e.g., 4K). In this case, at least one macro-shot image information can be obtained by taking at least one shot in a predetermined dir