Neural network assisted drug detection in X-ray images

A drug detection system using neural networks is applied to the problem of detecting cocaine simulants in backscatter and transmission images of baggage generated by the AS&E 101 X-ray mobile van. This system automatically locates and evaluates potential targets of interest by merging intensify and geometric data from backscatter and transmission X-ray images and outlines the suspicious regions in red. Two neural networks are used to analyze the combination of both backscatter and transmission data; the first network analyzes suspicious regions from the images and outputs a probability that the region contains drugs, and the second network integrates all such regions from a bag and outputs a probability that the bag contains drugs. The system performance approaches that of expert human operators in detecting drugs. It can benefit inspection by reducing the number of bags that the human needs to inspect, thereby increasing the number of bags that a human can process in a given time