Date of Award
3-24-2016
Document Type
Thesis
Degree Name
Master of Science in Electrical Engineering
Department
Department of Electrical and Computer Engineering
First Advisor
Michael J. Mendenhall, PhD.
Abstract
Human detection is an important first step in locating and tracking people in many missions including SAR and ISR operations. Recent detection systems utilize hyperspectral and multispectral technology to increase the acquired spectral content in imagery and subsequently better identify targets. This research demonstrates human detection through a multispectral skin detection system to exploit the unique optical properties of human skin. At wavelengths in the VIS and NIR regions of the electromagnetic spectrum, an individual can be identified by their unique skin parameters. Current detection methods base the skin pixel selection criteria on a diffuse skin reflectance model; however, it can be observed that human skin exhibits a combination of specular and diffuse reflectance. The objective of this effort is to better characterize human skin reflectance by collecting image-based BRDF skin measurements for future model incorporation in the existing multispectral skin detection system. Integrating multispectral BRDF data should reduce misdetections and better describe skin reflectance as a function of illumination source, target, and detector orientation.
AFIT Designator
AFIT-ENG-MS-16-M-004
DTIC Accession Number
AD1054435
Recommended Citation
Bintz, Jeffrey R., "Image-Based Bidirectional Reflectance Distribution Function of Human Skin in the Visible and Near Infrared" (2016). Theses and Dissertations. 288.
https://scholar.afit.edu/etd/288