UC San Diego researchers could help US military thwart explosi...(e shoe boxes milk cartons cigarette cart...)

As part of their current research, Lanza di Scalea and his team will collect both visible and infrared signatures of an object and then analyze the images and extract certain features like shape, texture and material type. The third step will use statistical pattern recognition to determine whether an anomalous object is harmless or not.

Lanza di Scalea said advances in the field of multispectral surveillance over the last few years have aided in this type of research. Multispectral surveillance involves detecting objects and monitoring different wavelengths of radiation from an object going from visible to ultraviolet and infrared lights and combining all of those different radiation wavelengths to identify an object.

"Another area my research is benefiting from is statistical pattern recognition and being able to combine different features of an object to statistically classify it," said Lanza di Scalea, a world-renowned expert in structural health monitoring. "For example, the brain can look at a road and learn what a normal road looks like based on different features like shapes and colors. If you put an object on the road the brain would know there is something different even thought it hasn't seen that exact object before. It's that kind of statistical pattern recognition we want to use with computers to detect anomalous objects without prior training on the specific object."

Current explosive detection technology used by the U.S. government includes X-Ray machines; machine olfacation (gas chromatography and differential mobility spectrometry); neutron activation, in which the machines bombard the suspect explosives with neutrons and read the gamma radiation decay signatures to determine the chemical compositions of the sample; and specially trained dogs.

"The U.S. government is always looking for improved methodologies to detect explosives bo
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