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.