What is
Skin MBTI Type Analysis?
A high-precision AI analysis system that decomposes
skin surface images into multidimensional data to quantify skin conditions.
A high-precision AI analysis system
that decomposes skin surface images
into multidimensional data to quantify skin conditions.
Automatically separates skin areas
from high-resolution images,
removes lighting and noise,
and refines data for analysis.
Decomposes skin data
into pigmentation, moisture-oil balance,
elasticity, and texture structure to model
multidimensional characteristic vectors.
Converts analysis results
into standardized skin condition vectors
and integrates with aging prediction and
personalized recommendation systems
RGB-D 3D Aging
Analysis Engine
Applies RGB-D 3D sensors and 3D reconstruction
algorithms to detect hidden wrinkles beyond
surface image analysis, based on structural
depth data. Quantifies the degree of skin sagging,
volume changes, wrinkle depth and directionality
into 3D coordinate data to measure aging progression
from multiple angles.
3D Facial Skin Diagnosis
that even measures
volume changes
Goes beyond 2D image-based analysis
with RGB-D based 3D scanning to analyze
skin surface topography, wrinkle depth and direction,
and volume changes in three dimensions.
With precision within 0.5mm, it captures skin
topography data and 3D structural changes
to improve accuracy.
Environment-Adaptive
Auto Calibration Technology
Detects environmental variables such
as lighting brightness, color temperature, screen
luminance, and skin reflectance in real-time
to automatically calibrate analysis values.
Provides stable color analysis results even
in various offline environments.
High-Resolution Skin Data
Quantitative Collection
Utilizes high-resolution image data to quantify spectral reflection characteristics
and color dispersion of the skin surface. The AI analysis engine decomposes melanin concentration,
spatial patterns of pigment distribution, and regional color temperature deviations in multiple layers
to precisely model non-visible pigment changes on a data-driven basis.
Utilizes high-resolution image data
to quantify spectral reflection characteristics
and color dispersion of the skin surface. The AI analysis
engine decomposes melanin concentration,
spatial patterns of pigment distribution, and regional
color temperature deviations in multiple layers
to precisely model non-visible pigment changes
on a data-driven basis.
Pigmentation AI Diagnosis
Skin Balance
Profile Generation
Converts analyzed pigment data into standardized pigment vectors to generate individual pigment profiles. Derives management priorities based on pigment
density and diffusion patterns.
Moisture-Oil AI Diagnosis
Moisture-Oil Balance
Profile Generation
Collected data is structurally interpreted
through AI algorithms. Comprehensively
analyzes moisture retention, oil excess
potential, and regional balance.
Clearly proven business impact
by many cases
+14%
Sales
Contribution
Of the total store sales, the share generated
from purchases after Twinit
experience averaged 14%.
×3
Walk-in
Customer Increase
The number of visitors to offline stores
that adopted Twinit AI increased
to an average of 200% compared to before.
+67%
Online Traffic
Connection Rate
Average monthly sales increased by 67% per
store during the Twinit solution
deployment period.
