Paper Title
Automated Detection of Threat Object in X-Ray Images of Baggage
Abstract
To reduce the risk of crime and terrorist attacks we require a priority task Baggage inspection using X-ray
screening. Identification of threat is very difficult in manual procedure because you require high concentration and very few
bags contain threat. If we have automated solution for this query then it would be a great for this field. By using single X-ray
images we found method for automatic detection of threat objects. Our approach is an adaptation of SURF detector and
descriptor methodology which when applied to an image detects the threat substance with different sections, primarily scale
and rotation. This detection method is near about similar or even base on previously proposed schemes regarding with
distinctiveness, repeatability, and robustness, compared much faster and yet can be computed. Single views of grayscale Xray
images obtained using a single energy acquisition system is also done by this procedure. Three different detection of
threat carried in this project: 1) razor blades; 2) shuriken (ninja stars) 3) handguns.