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Human Skin Surface Evaluation by Image Processing

  • Liangen Zhu*
  • , Xuemin Zhan
  • , Fengying Xie
  • *Corresponding author for this work
  • Beihang University
  • Hubei Polytechnic University

Research output: Contribution to journalConference articlepeer-review

Abstract

Human skin gradually lose its tension and becomes very dry as time flies by. Use of cosmetics is effective to prevent skin aging. Recently, there are many choices of products of cosmetics. To show their effects, It is desirable to develop a way to evaluate quantificationally skin surface condition. In this paper, An automatic skin evaluating method is proposed. The skin surface has the pattern called grid-texture. This pattern is composed of the valleys that spread vertically, horizontally, and obliquely and the hills separated by them. Changes of the grid are closely linked to the skin surface condition. They can serve as a good indicator for the skin condition. By measuring the skin grid using digital image processing technologies, we can evaluate skin surface about its aging, health, and alimentary status. In this method, the skin grid is first detected to form a closed net. Then, some skin parameters such as Roughness, tension, scale and gloss can be calculated from the statistical measurements of the net. Through analyzing these parameters, the condition of the skin can be monitored.

Original languageEnglish
Pages (from-to)362-367
Number of pages6
JournalProceedings of SPIE - The International Society for Optical Engineering
Volume5254
StatePublished - 2003
EventThird International Conference on Photonics and Imaging in Biology and Medicine - Wuhan, China
Duration: 8 Jun 200311 Jun 2003

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 3 - Good Health and Well-being
    SDG 3 Good Health and Well-being

Keywords

  • Curvature analysis
  • Energy transformation
  • Morphological filtering
  • Roof-edge detection
  • Skin image processing
  • Skin parameter measurements
  • Skin surface evaluation

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