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http://dx.doi.org/10.5573/ieek.2013.50.9.164

Background Removal from XRF Spectrum using the Interval Partitioning and Classifying  

Yang, Sanghoon (Department of Electronic Engineering, Chonbuk National University)
Lee, Jaehwan (Department of Electronic Engineering, Chonbuk National University)
Yoon, Sook (Department of Multimedia Engineering, Mokpo National University)
Park, Dong Sun (IT Convergence Research Center, Chonbuk National University)
Publication Information
Journal of the Institute of Electronics and Information Engineers / v.50, no.9, 2013 , pp. 164-171 More about this Journal
Abstract
XRF spectrum data of a material include a lot of background signals which are not related to its components. Since an XRF analyzer analyzes components and concentrations of an analyte using the locations and magnitudes of gaussian-shaped peaks extracted from a spectrum, its background signals need to be removed completely from the spectrum for the accurate analysis. Morphology-based method, SNIP-based method and thresholding-based method have been used to remove background signals. In the paper, a background removal method, an improved version of an interval-thresholding-based method, is proposed. The proposed method consists of interval partitioning, interval classifying, and background estimation. Experimental results show that the proposed method has better performance on background removal from the spectrum than the existing methods, morphology-based method and SNIP-based method.
Keywords
XRF; Background removal; Background Estimation; Interval thresholding; Interval partitioning;
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Times Cited By KSCI : 1  (Citation Analysis)
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