LG-Graph Based Detection of NRF Spectrum Signatures: Initial Results and Comparison (original) (raw)

2009 21st IEEE International Conference on Tools with Artificial Intelligence, 2009

Abstract

ABSTRACT In this paper we present an enhanced version of our NRF spectra classifier based on local-global graphs (LG-graphs) and provide a comparison with other possible alternative detection schemes. Experimental results verify our claims that the proposed nuclear resonance fluorescence (NRF) signature detection methodology is favorable over other widely employed conventional feature extraction and signal representation methods. The LG-graph methodology is based on the representation of the signal's peaks as triangle-like shapes and then on extracting significant geometrical features from these triangles to derive a concise representation of the peaks that correspond to specific NRF signatures of interest. These features are used to enable the matching of the materials of interest in a new unknown NRF spectrum.

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