Effects of scatter-correction pre-processing methods and spectral derivative algorithms on forensic classification of paper

Infrared (IR) spectral data are always influenced by undesired random and systematic variations. As such, pre-processing of spectral data is normally required before chemometric modeling. Two most widely used pre-processing techniques, i.e. scatter-correction methods and spectral derivatives, were u...

Full description

Saved in:
Bibliographic Details
Main Authors: Lee, Loong-Chuen, Liong, Choong-Yeun, Osman, Khairul, Jemain, Abdul Aziz
Format: Conference Proceeding
Language:English
Subjects:
Algorithms
Clustering
Forensic engineering
Infrared spectroscopy
Principal components analysis
Scattering
Spectra
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:Infrared (IR) spectral data are always influenced by undesired random and systematic variations. As such, pre-processing of spectral data is normally required before chemometric modeling. Two most widely used pre-processing techniques, i.e. scatter-correction methods and spectral derivatives, were used to pre-process 150 IR spectral data of paper. The algorithms investigated in this preliminary study are Standard Normal Variate (SNV), Multiplicative Scatter Correction (MSC), Savitzky-Golay (SG) and Gap-Segment (GS). The visual examination of the clustering among three studied varieties of paper, i.e. IK Yellow, One Paper and Save Pack, is accomplished via Principal Component Analysis (PCA). Overall, separation of the three varieties of paper is greatly enhanced after pre-processing. The most significant improvement is obtained with pre-processing via 1st derivative using SG algorithms.
ISSN:0094-243X
1551-7616
DOI:10.1063/1.4954618