Paper Title
Automated Detection of Threat Object in X-Ray Images of Baggage

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 X-ray 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.