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Detection of regular objects in baggage using multiple X-ray views

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In order to reduce the security risk of a commercial aircraft, passengers are not allowed to take certain items in carry-on baggage. For this reason, human operators are trained to detect prohibited items using a manually controlled baggage screening process. In this paper, we propose the use of a method based on multiple X-ray views to detect some regular prohibited items with very defined shapes and sizes. The method consists of two steps: 'structure estimation', to obtain a geometric model of the multiple views from the object to be inspected (baggage); and 'parts detection', to detect the parts of interest (prohibited items). The geometric model is estimated using a structure from a motion algorithm. The detection of the parts of interest is performed by an ad-hoc segmentation algorithm (object dependent) followed by a general tracking algorithm based on geometric and appearance constraints. In order to illustrate the effectiveness of the proposed method, experimental results on detecting regular objects – razor blades and guns – are shown yielding promising results.
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Keywords: BAGGAGE SCREENING; COMPUTER VISION; LUGGAGE SCAN; MULTIPLE VIEW IMAGING; X-RAY TESTING

Document Type: Research Article

Publication date: 2013-01-01

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