Automatic Detection of Potential Threat Objects in X-ray Luggage Scan Images

Abstract

The detection of threat objects using X-ray luggage scan images has become an important means of aviation security. Most airport screening is still based on the manual detection of potential threat objects by human experts. This paper presents a system for the automatic detection of potential threat objects in X-ray luggage scan images. Segmentation and edge-based feature vectors form the basis of the automatic detection system. The system is illustrated using handguns as the threat objects in question. The experimental results show that the system can effectively detect the handguns in X-ray luggage scan images with minimal amounts of false positives. Also, apart from the initial setup of the classification database, the algorithm is suitable for real-time applications.