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

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 (a baggage), and ‘parts detection’, to detect the parts of interest (prohibited items). The geometric model is estimated using a structure from motion algorithm. The detection of the parts of interest is performed by an adhoc 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.