@article{Mery2017:Insight,
  title={Object recognition in X-ray testing using an efficient search algorithm in multiple views},
author={Mery, D. and Riffo, V. and Zuccar, I. and Pieringer, C.}, 
  journal={Insight - Non-Destructive Testing and Condition Monitoring},
  volume=59,
  number = 2,
  pages  ={85-92},
  year = 2017,
  abstract = {In order to reduce the security risk of a commercial aircraft, passengers are not allowed to take certain items in their 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 an automated method based on multiple X-ray views to recognize certain regular objects with highly defined shapes and sizes. The method consists of two steps: `monocular analysis', to obtain possible detections in each view of a sequence, and `multiple view analysis', to recognize the objects of interest using matchings in all views. The search for matching candidates is efficiently performed using a lookup table that is computed off-line. In order to illustrate the effectiveness of the proposed method, experimental results on recognizing regular objects -clips, springs and razor blades- in pen cases are shown achieving high precision and recall ($Pr =$   95.7\% , $Re =$ 92.5\%) for 120 objects. We believe that it would be possible to design an automated aid in a target detection task using the proposed algorithm.},
    url = {http://dmery.sitios.ing.uc.cl/Prints/ISI-Journals/2017-Insight-MultiX-ray.pdf},
}

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