Illicit Material Detection using Dual-Energy X-Ray Images

Abstract

Dual energy X-ray inspection systems are widely used in security and controlling systems. The performance of these systems however, degrades with the poor performance of human operators. Computer vision based systems are of vital importance in improving the detection rate of illicit materials, while keeping false alarms at a reasonably low level. In this study, a novel method is proposed for detecting material overlapping and reconstructing multiple images by alleviating these overlaps. Evaluation tests were conducted on images taken from luggage inspection X-ray screening devices used in shopping centres. The experimental results indicate that the reconstructed images are much easier to inspect by human operators than the unprocessed original images.