Title :
Smoothing gamma ray spectra to improve outlier detection
Author :
Barnabe-Lortie, Vincent ; Bellinger, Colin ; Japkowicz, Nathalie
Author_Institution :
Sch. of Electr. Eng. & Comput. Sci., Univ. of Ottawa, Ottawa, ON, Canada
Abstract :
Rapid detection of radioisotopes in gamma-ray data can, in some situations, be an important security concern. The task of designing an automated system for this purpose is complex due to, amongst other factors, the noisy nature of the data. The method described herein consists of preprocessing the data by applying a smoothing method tailored to gamma ray spectra, hoping that this should decrease their variance. Given that the number of counts at a given energy level in a spectrum should follow a Poisson distribution, smoothing may allow us to estimate the true photon arrival rate. Our experiments suggest that the added data preprocessing step can have large impact on the performance of anomaly detection algorithms on this particular domain.
Keywords :
Poisson distribution; gamma-ray spectra; national security; radioisotopes; smoothing methods; Poisson distribution; anomaly detection algorithms; data preprocessing step; gamma ray spectra; outlier detection; radiation level monitoring; radioisotope detection; security concerns; smoothing method; Gamma-rays; Noise measurement; Smoothing methods; Splines (mathematics); Support vector machines; Testing; Training;
Conference_Titel :
Computational Intelligence for Security and Defense Applications (CISDA), 2014 Seventh IEEE Symposium on
Conference_Location :
Hanoi
DOI :
10.1109/CISDA.2014.7035633
