Bidirectional imaging and modeling of skin texture. Academic Article uri icon

Overview

abstract

  • In this paper, we present a method of skin imaging called bidirectional imaging that captures significantly more properties of appearance than standard imaging. The observed structure of the skin's surface is greatly dependent on the angle of incident illumination and the angle of observation. Specific protocols to achieve bidirectional imaging are presented and used to create the Rutgers Skin Texture Database (clinical component). This image database is the first of its kind in the dermatology community. Skin images of several disorders under multiple controlled illumination and viewing directions are provided publicly for research and educational use. Using this skin texture database, we employ computational surface modeling to perform automated skin texture classification. The classification experiments demonstrate the usefulness of the modeling and measurement methods.

publication date

  • December 1, 2004

Research

keywords

  • Artificial Intelligence
  • Image Interpretation, Computer-Assisted
  • Imaging, Three-Dimensional
  • Models, Biological
  • Pattern Recognition, Automated
  • Skin
  • Skin Diseases

Identity

Scopus Document Identifier

  • 9644268890

PubMed ID

  • 15605862

Additional Document Info

volume

  • 51

issue

  • 12