Automated Detection of Threat Objects Using Adapted Implicit Shape Model
- 12 June 2015
- journal article
- Published by Institute of Electrical and Electronics Engineers (IEEE) in IEEE Transactions on Systems, Man, and Cybernetics: Systems
- Vol. 46 (4), 472-482
- https://doi.org/10.1109/tsmc.2015.2439233
Abstract
Baggage inspection using X-ray screening is a priority task that reduces the risk of crime and terrorist attacks. Manual detection of threat items is tedious because very few bags actually contain threat items and the process requires a high degree of concentration. An automated solution would be a welcome development in this field. We propose a methodology for automatic detection of threat objects using single X-ray images. Our approach is an adaptation of a methodology originally created for recognizing objects in photographs based on implicit shape models. Our detection method uses a visual vocabulary and an occurrence structure generated from a training dataset that contains representative X-ray images of the threat object to be detected. Our method can be applied to single views of grayscale X-ray images obtained using a single energy acquisition system. We tested the effectiveness of our method for the detection of three different threat objects: 1) razor blades; 2) shuriken (ninja stars); and 3) handguns. The testing dataset for each threat object consisted of 200 X-ray images of bags. The true positive and false positive rates (TPR and FPR) are: (0.99 and 0.02) for razor blades, (0.97 and 0.06) for shuriken, and (0.89 and 0.18) for handguns. If other representative training datasets were utilized, we believe that our methodology could aid in the detection of other kinds of threat objects.Keywords
Funding Information
- Fondecyt through CONICYT, Chile (1130934)
This publication has 26 references indexed in Scilit:
- Automated X-Ray Object Recognition Using an Efficient Search Algorithm in Multiple ViewsPublished by Institute of Electrical and Electronics Engineers (IEEE) ,2013
- Improving feature-based object recognition for X-ray baggage security screening using primed visualwordsPublished by Institute of Electrical and Electronics Engineers (IEEE) ,2013
- Object Detection in Multi-view X-Ray ImagesLecture Notes in Computer Science, 2012
- Active X-ray testing of complex objectsInsight - Non-Destructive Testing and Condition Monitoring, 2012
- Visual Words on Baggage X-Ray ImagesLecture Notes in Computer Science, 2011
- View synthesis of KDEX imagery for 3D security X-ray imagingPublished by Institution of Engineering and Technology (IET) ,2011
- VlfeatPublished by Association for Computing Machinery (ACM) ,2010
- Enhanced color coding scheme for kinetic depth effect X-ray (KDEX) imagingPublished by Institute of Electrical and Electronics Engineers (IEEE) ,2010
- The Pascal Visual Object Classes (VOC) ChallengeInternational Journal of Computer Vision, 2009
- Distinctive Image Features from Scale-Invariant KeypointsInternational Journal of Computer Vision, 2004