Detection of Human Skin in Near Infrared Hyperspectral Imagery

One of the difficulties in search and rescue missions is finding a small target, such as a person, in a large cluttered area. Airborne hyperspectral cameras are now being deployed to aid in this SAR mission. Motivated by the successes of such systems, we define a hyperspectral model of human skin in the visible and near infrared regions of the spectra so we can exploit knowledge gained during the modeling process to aid in human skin detection. Based on observations of the skin model results, an efficient and robust skin detection algorithm using channels in the near infrared region of the spectra is developed. Our algorithm is denoted the Normalized Difference Skin Index, motivated by the Normalized Difference Vegetation Index used in the literature for detecting vegetation in hyperspectral imagery. We demonstrate the capabilities of our skin detection methodology to detect skin amongst objects known to cause false detections for methodologies using three channel color data.