Spectral imaging systems use information from the entire electromagnetic spectrum to provide digital images with much greater information per pixel than traditional cameras.
Feature spaces in a spectral imaging system are vectors that numerically represent an object's characteristics. Researchers at the Air Force Institute of Technology (AFIT) in US have developed a novel two-dimensional feature space which uses the spectral absorption characteristics of
melanin, hemoglobin and water to better characterise human skin.
The researchers used feature spaces to key in on specific constituents of human tissue by using a skin index concerned with how water and melanin's presence in skin manifests at two different wavelengths in the near-infrared region.
This would cut the overall cost of hyperspectral-based search and rescue systems by a factor of seven. "The study represents a crossroads between physics and statistical pattern recognition," said Michael J Mendenhall, assistant professor at AFIT.
"The features were designed based on an understanding of the physics behind skin's spectral shape, but in such a way that the features separated skin and non-skin pixels in order to make the pattern recognition portion of the problem more effective," said Mendenhall.