Title :
A NRF Spectra Signature Detection Model Using Local-Global Graphs
Author :
Bourbakis, N. ; Pantelopoulos, A. ; Kannavara, R.
Author_Institution :
ATR Center, Wright State Univ., Dayton, OH
Abstract :
The objective of this paper is to develop an NRF signature classifier scheme in order to efficiently and accurately detect and recognize NRF signatures of nuclear material inside a cargo container. In response to this problem we have developed a local-global (LG) graph as the NRF signal representation scheme for efficient matching and on which to build the NRF signature library. Here we also assume that the NRF signals will be "free" of noise after passing a preprocessing step at a previous stage. Thus, the proposed scheme is based on the analysis of an incoming NRF signal and determining its min and max; Then we create the local triangles and express them in a form of local graphs; at the last step we combine local graphs for creating the Local-Global graphs that hold the desirable pattern (signature) of certain material.
Keywords :
freight handling; graph theory; nuclear resonances; production engineering computing; radiography; signal processing; NRF signal representation; NRF signature classifier scheme; NRF signature library; NRF spectra signature detection model; cargo container; efficient matching; local global graphs; nuclear material; Artificial intelligence; Computational modeling; Containers; Educational institutions; Image segmentation; Monte Carlo methods; Shape; Signal analysis; Signal processing algorithms; Signal synthesis; Local global graphs; NRF signal processing;
Conference_Titel :
Tools with Artificial Intelligence, 2008. ICTAI '08. 20th IEEE International Conference on
Conference_Location :
Dayton, OH
Print_ISBN :
978-0-7695-3440-4
DOI :
10.1109/ICTAI.2008.125