Detecting Wires in Cluttered Urban Scenes Using a Gaussian Model

A novel wire detection algorithm for use by unmanned aerial vehicles (UAV) in low altitude urban reconnaissance is presented. This is of interest to urban search and rescue and military reconnaissance operations. Detection of wires plays an important role, because thin wires are hard to discern by tele-operators and automated systems. Our algorithm is based on identification of linear patterns in images. Most existing methods that search for linear patterns use a simple model of a line, which does not take into account the line surroundings. We propose the use of a robust Gaussian model to approximate the intensity profile of a line and its surroundings which allows effective discrimination of wires from other visually similar linear patterns. The algorithm is able to cope with highly cluttered urban backgrounds, moderate rain, and mist. Experimental results show a 17.7% detection improvement over the baseline.