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Foreign Object Detection in Multispectral X-ray Images of Food Items using Sparse Discriminant Analysis

DTU Compute, Technical University of Denmark, released at the 20th Scandinavian Conference, SCIA 2017, Tromsø, Norway, June 12–14, 2017 a paper about MultiX detectors

As conclusion the authors say:

We have demonstrated that we can achieve robust detection of certain foreign objects in the data sets used in this work. This was done in a completely data-driven manner by applying a sparse classi er to the normalized data. There is great potential for using an approach similar to the one we present, which could help with storing fewer data and processing the results faster.

This work is supported by the Lundbeck foundation, the Technical University of Denmark and the NEXIM research project funded by the Danish Council for Strategic Research (contract no. 11-116226) within the Program Commission on Health, Food and Welfare.