Skin aging estimation scheme based on lifestyle and dermoscopy image analysis

Jehyeok Rew; Young Hwan Choi; Hyungjoon Kim; Eenjun Hwang

doi:10.3390/app9061228

Skin aging estimation scheme based on lifestyle and dermoscopy image analysis

Jehyeok Rew, Young Hwan Choi, Hyungjoon Kim, Eenjun Hwang

Research output: Contribution to journal › Article › peer-review

11 Citations (Scopus)

Abstract

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.

Original language	English
Article number	1228
Journal	Applied Sciences (Switzerland)
Volume	9
Issue number	6
DOIs	https://doi.org/10.3390/app9061228
Publication status	Published - 2019

Bibliographical note

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.

Keywords

Lifestyle analysis
Skin aging estimation
Skin aging simulation
Skin texture analysis

ASJC Scopus subject areas

General Materials Science
Instrumentation
General Engineering
Process Chemistry and Technology
Computer Science Applications
Fluid Flow and Transfer Processes

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10.3390/app9061228

Cite this

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title = "Skin aging estimation scheme based on lifestyle and dermoscopy image analysis",

abstract = "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.",

keywords = "Lifestyle analysis, Skin aging estimation, Skin aging simulation, Skin texture analysis",

author = "Jehyeok Rew and Choi, {Young Hwan} and Hyungjoon Kim and Eenjun Hwang",

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doi = "10.3390/app9061228",

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volume = "9",

journal = "Applied Sciences (Switzerland)",

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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.

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KW - Skin aging simulation

KW - Skin texture analysis

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ER -

Skin aging estimation scheme based on lifestyle and dermoscopy image analysis

Abstract

Bibliographical note

Keywords

ASJC Scopus subject areas

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