Bidirectional imaging and modelling of skin texture

Oana G. Cula, Kristin J. Dana, Frank P. Murphy, Babar K. Rao

Research output: Contribution to journalArticlepeer-review

32 Scopus citations


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.

Original languageEnglish (US)
Pages (from-to)2148-2159
Number of pages12
JournalIEEE Transactions on Biomedical Engineering
Issue number12
StatePublished - Dec 2004

All Science Journal Classification (ASJC) codes

  • Biomedical Engineering


  • 3-D texture
  • Appearance-based modeling
  • BTF
  • Bidirectional texture function
  • Skin texture
  • Texture


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