Robust skin-roughness estimation based on co-occurrence matrix

Ji Sang Bae, Sang Ho Lee, Kang Sun Choi, Jong-Ok Kim

Research output: Contribution to journalArticle

Abstract

As the interest in one's appearance has recently increased, the demand for diagnosing skin conditions has also increased. However, conventional specialized skin diagnostic devices are generally expensive, and people have to visit a skin-care shop to diagnose their skin condition. This is time consuming and troublesome. In this paper, we propose a skin-roughness estimation method that uses a mobile-phone camera in daily environments. In order to achieve accurate evaluation, the illumination variation is alleviated using texture components of the facial skin image. We also propose a new feature-extraction method based on the gray-level co-occurrence matrix, which effectively measures the skin roughness from the texture components. The performance of the proposed method is compared with the conventional commonly used features, and we verify the superiority of the proposed method.

Original languageEnglish
Pages (from-to)13-22
Number of pages10
JournalJournal of Visual Communication and Image Representation
Volume46
DOIs
Publication statusPublished - 2017 Jul 1

Fingerprint

Skin
Surface roughness
Textures
Mobile phones
Feature extraction
Lighting
Cameras

Keywords

  • Gray-level co-occurrence matrix (GLCM)
  • Skin image
  • Skin roughness
  • Texture domain

ASJC Scopus subject areas

  • Signal Processing
  • Media Technology
  • Computer Vision and Pattern Recognition
  • Electrical and Electronic Engineering

Cite this

Robust skin-roughness estimation based on co-occurrence matrix. / Bae, Ji Sang; Lee, Sang Ho; Choi, Kang Sun; Kim, Jong-Ok.

In: Journal of Visual Communication and Image Representation, Vol. 46, 01.07.2017, p. 13-22.

Research output: Contribution to journalArticle

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