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Please use this identifier to cite or link to this item: https://ptsldigital.ukm.my/jspui/handle/123456789/578182
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dc.contributor.authorJemain A. A. (UKM)
dc.date.accessioned2023-11-06T02:58:59Z-
dc.date.available2023-11-06T02:58:59Z-
dc.date.issued2017-07
dc.identifier.issn0128-7680
dc.identifier.otherukmvital:113366
dc.identifier.urihttps://ptsldigital.ukm.my/jspui/handle/123456789/578182-
dc.descriptionSpectral data is often required to be pre-processed prior to applying a multivariate modelling technique. Baseline correction of spectral data is one of the most important and frequently applied pre-processing procedures. This preliminary study aims to investigate the impacts of six types of baseline correction algorithms on classifying 150 infrared spectral data of three varieties of paper. The algorithms investigated were Iterative Restricted Least Squares, Asymmetric Least Squares (ALS), Low-pass FFT Filter, Median Window (MW), Fill Peaks and Modified Polynomial Fitting. Processed spectral data were then analysed using Principal Component Analysis (PCA) to visually examine the clustering among the three varieties of paper. Results show that separation among the three varieties of paper is greatly improved after baseline correction via ALS, FP and MW algorithms.
dc.language.isoen
dc.publisherUniversiti Putra Malaysia Press
dc.relation.haspartPertanika Journals
dc.relation.urihttp://www.pertanika.upm.edu.my/view_archives.php?journal=JST-25-3-7
dc.rightsUKM
dc.subjectForensic science
dc.subjectPaper
dc.subjectBaseline correction
dc.subjectPrincipal component analysis (PCA)
dc.subjectIR spectroscopy
dc.titleEffects of baseline correction algorithms on forensic classification of paper based on ATR-FTIR spectrum and principal component analysis (PCA)
dc.typeJournal Article
dc.format.volume25
dc.format.pages767-774
dc.format.issue3
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