TY - JOUR
T1 - Skin aging estimation scheme based on lifestyle and dermoscopy image analysis
AU - Rew, Jehyeok
AU - Choi, Young Hwan
AU - Kim, Hyungjoon
AU - Hwang, Eenjun
N1 - Funding Information:
Author Contributions: Conceptualization, J.R. and Y.C.; investigation, H.K.; methodology, J.R. and Y.C.; software, J.R.; visualization, J.R.; writing—original draft preparation, J.R.; writing—review and editing, E.H.; supervision, E.H.; Funding: This research was supported by the Brain Korea 21 Plus Project in 2019, and by the Basic Science Research Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Education (NRF-2016R1D1A1A09919590).
Publisher Copyright:
© 2019 by the authors.
PY - 2019
Y1 - 2019
N2 - Besides genetic characteristics, people also undergo a process of skin aging under the influence of diverse factors such as sun exposure, food intake, sleeping patterns, and drinking habits, which are closely related to their personal lifestyle. So far, many studies have been conducted to analyze skin conditions quantitatively. However, to describe the current skin condition or predict future skin aging effectively, we need to understand the correlation between skin aging and lifestyle. In this study, we first demonstrate how to trace people's skin condition accurately using scale-invariant feature transform and the color histogram intersection method. Then, we show how to estimate skin texture aging depending on the lifestyle by considering various features from face, neck, and hand dermoscopy images. Lastly, we describe how to predict future skin conditions in terms of skin texture features. Based on the Pearson correlation, we describe the correlation between skin aging and lifestyle, and estimate skin aging according to lifestyle using the polynomial regression and support vector regression models. We evaluate the performance of our proposed scheme through various experiments.
AB - Besides genetic characteristics, people also undergo a process of skin aging under the influence of diverse factors such as sun exposure, food intake, sleeping patterns, and drinking habits, which are closely related to their personal lifestyle. So far, many studies have been conducted to analyze skin conditions quantitatively. However, to describe the current skin condition or predict future skin aging effectively, we need to understand the correlation between skin aging and lifestyle. In this study, we first demonstrate how to trace people's skin condition accurately using scale-invariant feature transform and the color histogram intersection method. Then, we show how to estimate skin texture aging depending on the lifestyle by considering various features from face, neck, and hand dermoscopy images. Lastly, we describe how to predict future skin conditions in terms of skin texture features. Based on the Pearson correlation, we describe the correlation between skin aging and lifestyle, and estimate skin aging according to lifestyle using the polynomial regression and support vector regression models. We evaluate the performance of our proposed scheme through various experiments.
KW - Lifestyle analysis
KW - Skin aging estimation
KW - Skin aging simulation
KW - Skin texture analysis
UR - http://www.scopus.com/inward/record.url?scp=85063732360&partnerID=8YFLogxK
U2 - 10.3390/app9061228
DO - 10.3390/app9061228
M3 - Article
AN - SCOPUS:85063732360
SN - 2076-3417
VL - 9
JO - Applied Sciences (Switzerland)
JF - Applied Sciences (Switzerland)
IS - 6
M1 - 1228
ER -