Date of Award

3-10-2010

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

Due to the general shift from conventional warfare to terrorism and urban warfare by enemies of the United States in the late 20th Century, locating and tracking individuals of interest have become critically important. Dismount detection and tracking are vital to provide security and intelligence in both combat and homeland defense scenarios including base defense, combat search and rescue (CSAR), and border patrol. This thesis focuses on exploiting recent advances in skin detection research to reliably detect dismounts in a scene. To this end, a signal-plus-noise model is developed to map modeled skin spectra to the imaging response of an arbitrary sensor, enabling an in-depth exploration of multispectral features as they are encountered in the real world for improved skin detection. Knowledge of skin locations within an image is exploited to cue a robust dismount detection algorithm, significantly improving dismount detection performance and efficiency. This research explores multiple spectral features and detection algorithms to find the best features and algorithms for detecting skin in multispectral visible and short wave infrared (SWIR) imagery. This study concludes that using SWIR imagery for skin detection and color information for false alarm suppression results in 95% probability of skin detection at a false alarm rate of only 0.4%. Skin detections are utilized to cue a dismount detector based on histograms of oriented gradients. This technique reduces the search space by nearly 3 orders of magnitude compared to searching an entire image, while reducing the average number of false positives per image by nearly 2 orders of magnitude at 95% probability of dismount detection. The skin-detection-cued dismount detector developed in this thesis has the potential to make significant contribution to the United States Air Force human measurement and signature intelligence and CSAR missions.

AFIT Designator

AFIT-GE-ENG-10-05

DTIC Accession Number

ADA518510

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