An image processing analysis of skin textures

TL;DR

This paper presents a statistical image processing method to analyze skin textures, focusing on quantifying differences in color and coarseness, evaluating grain size, anisotropy, and detecting pattern defects.

Contribution

It introduces a novel statistical approach for skin texture analysis, including measurements of grain size, anisotropy, and defect detection, enhancing quantitative skin evaluation.

Findings

Effective measurement of skin grain size and anisotropy.

Ability to identify pattern defects in skin textures.

Quantitative evaluation of skin color and coarseness.

Abstract

Colour and coarseness of skin are visually different. When image processing is involved in the skin analysis, it is important to quantitatively evaluate such differences using texture features. In this paper, we discuss a texture analysis and measurements based on a statistical approach to the pattern recognition. Grain size and anisotropy are evaluated with proper diagrams. The possibility to determine the presence of pattern defects is also discussed.