Concealed Target Detection with Fusion of Visible and Infrared

Concealed or buried improvised explosive devices (IEDs) are a major cause of fatalities for both civilians and soldiers. For detecting hidden targets, many technologies have been considered such as ground penetrating radar (GPR), infrared cameras, and even visible wavelength cameras. In this work, we propose fusing visible and infrared sensors for automatic detection of shallowly buried (< 10cm) or above ground targets. We use Gaussian Mixture Models (GMMs) to create a base model of the temperature and color variation of the background scene and dynamically update our models for new scenes. Anomalous temperatures and colors are identified using the GMM components. Fusion is performed at the pixel level, confidence map level, and decision level for comparison. Data was collected with a Xenics Gobi 480 long wave infrared camera and a Canon Powershot A1200 visible wavelength camera with metal targets placed in various concealed configurations. The observed results show that infrared can detect shallowly buried targets and targets above ground "out in the open" effectively, but cannot detect metal targets nearby bushes. Visible cameras, on the other hand, can detect the metal targets in the bushes effectively. Confidence map and decision level fusion led to the best results when there was a mix of buried targets and targets hidden in bushes.