Skin aging estimation scheme based on lifestyle and dermoscopy image analysis

Jehyeok Rew, Young Hwan Choi, Hyungjoon Kim, Een Jun Hwang

Research output: Contribution to journalArticle

1 Citation (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 languageEnglish
Article number1228
JournalApplied Sciences (Switzerland)
Volume9
Issue number6
DOIs
Publication statusPublished - 2019 Jan 1

Fingerprint

image analysis
Image analysis
Skin
Aging of materials
regression analysis
food intake
textures
drinking
habits
estimates
histograms
intersections
Textures
polynomials
sun
color
Sun
Polynomials
Color

Keywords

  • Lifestyle analysis
  • Skin aging estimation
  • Skin aging simulation
  • Skin texture analysis

ASJC Scopus subject areas

  • Materials Science(all)
  • Instrumentation
  • Engineering(all)
  • Process Chemistry and Technology
  • Computer Science Applications
  • Fluid Flow and Transfer Processes

Cite this

Skin aging estimation scheme based on lifestyle and dermoscopy image analysis. / Rew, Jehyeok; Choi, Young Hwan; Kim, Hyungjoon; Hwang, Een Jun.

In: Applied Sciences (Switzerland), Vol. 9, No. 6, 1228, 01.01.2019.

Research output: Contribution to journalArticle

@article{f634727140814deb9526c6d07f8381d7,
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 Hwang, {Een Jun}",
year = "2019",
month = "1",
day = "1",
doi = "10.3390/app9061228",
language = "English",
volume = "9",
journal = "Applied Sciences (Switzerland)",
issn = "2076-3417",
publisher = "Multidisciplinary Digital Publishing Institute",
number = "6",

}

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, Een Jun

PY - 2019/1/1

Y1 - 2019/1/1

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

UR - http://www.scopus.com/inward/citedby.url?scp=85063732360&partnerID=8YFLogxK

U2 - 10.3390/app9061228

DO - 10.3390/app9061228

M3 - Article

VL - 9

JO - Applied Sciences (Switzerland)

JF - Applied Sciences (Switzerland)

SN - 2076-3417

IS - 6

M1 - 1228

ER -