Automated detection of inorganic powders in X-ray images of airport luggage

Danijela Vukadinovic, Miguel Ruiz Osés and David Anderson ()
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Danijela Vukadinovic: European Commission
Miguel Ruiz Osés: European Commission
David Anderson: European Commission

Journal of Transportation Security, 2023, vol. 16, issue 1, No 3, 28 pages

Abstract: Abstract At the checkpoint, the detection of illicit inorganic powders in passenger luggage using conventional X-ray can be challenging. An algorithm is presented for the automated detection of inorganic powder-like substances from complex X-ray images of highly cluttered passenger bags using computer vision. The proposed method utilizes support vector machine (SVM) classifiers built from local binary patterns (LBP) texture features. When tested on a dataset created in-house, the algorithm achieves a detection precision of 97% and a false positive rate of 3%. This is the first study performed on a realistic dataset, including different amounts and shapes of powders and electronic clutter, and where the success of the automated method is compared with inter-observer variability.

Keywords: Detection; Explosives; Inorganic powders; X-ray; Aviation security (search for similar items in EconPapers)
Date: 2023
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DOI: 10.1007/s12198-023-00261-5

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