The threat of bombs concealed in luggage is of paramount concern to the airline industry, and while dependable monitoring systems are in place at major airports, there is a need for more aggressive and precise means of screening concealed objects that can be taken aboard a plane. CMRI's Intelligent Systems team is exploring advanced image processing techniques to improve the process of detecting explosives hidden in luggage. Inc. CMRI's study emphasizes the use of advanced image processing techniques for accurate segmentation of explosives from these images. The goal is to distinguish between explosive and nonexplosive matter accurately enough to determine the explosive's mass. If you've ever watched your luggage pass through an airport X-ray system and seen its image on the operator's screen, you've probably been impressed by how cluttered the images can be.
People tend to stuff objects of all shapes, sizes and materials into their suitcases.
This means the image is the cumulative effect of the absorption of the X-rays by every object they pass through in the luggage. The result is a cross-sectional image of the suitcase contents, allowing a better view of what's inside. In spite of this increased clarity, the luggage can still contain enough clutter to make object boundaries difficult to discern. It is for such cases that CMRI is investigating novel algorithms for boundary detection and segmentation of explosives. One by one, each of the seed's surrounding pixels are tested to determine if they fit some measure of similarity to the seed.