A Composite Algorithm for Optimized Baseline Correction in Raman Spectroscopy

2017 ◽  
Author(s):  
Andrew Atiogbe Huzortey ◽  
Benjamin Anderson ◽  
Alfred Owusu
Keyword(s):  
Raman Spectroscopy ◽  
Baseline Correction

Dynamic one-shot target detection and classification using pseudo-Siamese network and its application to Raman spectroscopy

The Analyst ◽  
2021 ◽  
Author(s):  
Jae-Hyeon Park ◽  
Hyeong-Geun Yu ◽  
Dong-Jo Park ◽  
Hyunwoo Nam ◽  
Dong Eui Chang
Keyword(s):  
Raman Spectroscopy ◽  
Chemical Defense ◽  
Target Detection ◽  
Baseline Correction ◽  
Military Operations ◽  
Siamese Network

Target detection and classification by Raman spectroscopy are important techniques for biological and chemical defense in military operations. Conventionally, these techniques preprocess the observed spectra using smoothing or baseline correction,...

scholarly journals Improved Baseline Correction Method Based on Polynomial Fitting for Raman Spectroscopy

2018 ◽  
Vol 8 (4) ◽  
pp. 332-340 ◽  
Author(s):  
Haibing Hu ◽  
Jing Bai ◽  
Guo Xia ◽  
Wenda Zhang ◽  
Yan Ma
Keyword(s):  
Raman Spectroscopy ◽  
Correction Method ◽  
Baseline Correction ◽  
Polynomial Fitting

A baseline correction algorithm for Raman spectroscopy by adaptive knots B-spline

2015 ◽  
Vol 26 (11) ◽  
pp. 115503 ◽  
Author(s):  
Xin Wang ◽  
Xian-guang Fan ◽  
Ying-jie Xu ◽  
Xiu-fen Wang ◽  
Hao He ◽  
...  
Keyword(s):  
Raman Spectroscopy ◽  
Baseline Correction ◽  
Correction Algorithm ◽  
B Spline

Quantification of an Active Substance in a Tablet by NIR and Raman Spectroscopy

1998 ◽  
Vol 6 (1) ◽  
pp. 279-289 ◽  
Author(s):  
Ingela Jedvert ◽  
Mats Josefson ◽  
Frans Langkilde
Keyword(s):  
Raman Spectroscopy ◽  
Active Substance ◽  
Reference Method ◽  
Spectroscopic Technique ◽  
Calibration Model ◽  
Baseline Correction ◽  
Spectroscopic Techniques ◽  
Long Term Stability ◽  
Calibration Models

Spectroscopic techniques in combination with chemometrics give opportunities to analyse tablets without time-consuming sample preparation. The aim of the present study was to develop a method to quantify the active substance, isosorbide-5-mononitrate, in Imdur® 120 mg tablets either by NIR diffuse reflectance or Raman spectroscopy. The calibration set was selected to simulate, with the available samples, as closely as possible a full factorial design with three factors. The reference method was liquid chromatography (LC). Calibration models with different baseline correction methods, different parts of wavelength range and different measures of weights have been evaluated. The calibration model found for each spectroscopic technique is discussed. The accuracy for the spectroscopic techniques were equal in merit to the LC method. Both the NIR and the Raman calibrations also showed a good long-term stability. With the baseline correction methods used for the spectra, it was possible to analyse tablets after 1.5 years. In conclusion it is possible to quantify Imdur® 120 mg with either NIR or Raman spectroscopy.

scholarly journals Raman Spectroscopy Study of Phosphorites Combined with PCA-HCA and OPLS-DA Models

Minerals ◽  
2019 ◽  
Vol 9 (10) ◽  
pp. 578 ◽  
Author(s):  
Xiyu Yao ◽  
Huayi Hou ◽  
Huan Liang ◽  
Kai Chen ◽  
Xiangbai Chen
Keyword(s):  
Principal Component Analysis ◽  
Raman Spectroscopy ◽  
Clustering Analysis ◽  
Significant Contribution ◽  
Vibrational Mode ◽  
Principal Component ◽  
Baseline Correction ◽  
Vibrational Modes ◽  
Hierarchical Clustering Analysis ◽  
Spectroscopy Study

Phosphorite is a nonrenewable strategic resource, a convenient and rapid method of phosphorite grade identification and classification is important to improve phosphate utilization. In this study, Raman spectroscopy has been combined with principal component analysis and hierarchical clustering analysis (PCA-HCA) and orthogonal partial least squares-discriminant analysis (OPLS-DA) models for an investigation of different grade phosphorite samples. Both the PCA-HCA and OPLS-DA models showed that different grade phosphorite samples can be clearly distinguished by statistically analyzing the Raman spectra after smoothing, baseline correction, and first derivation. In addition, the S-line study on the OPLS-DA model clearly demonstrated that the symmetrical stretching vibrational mode of phosphate near 960 cm−1 had a much more significant contribution than other vibrational modes for the differentiation of different grade phosphorite samples.

scholarly journals An Effective Baseline Correction Algorithm Using Broad Gaussian Vectors for Chemical Agent Detection with Known Raman Signature Spectra

Sensors ◽  
2021 ◽  
Vol 21 (24) ◽  
pp. 8260
Author(s):  
Hyeong Geun Yu ◽  
Dong Jo Park ◽  
Dong Eui Chang ◽  
Hyunwoo Nam
Keyword(s):  
Raman Spectroscopy ◽  
Raman Scattering ◽  
Linear Combination ◽  
Chemical Agent ◽  
Baseline Correction ◽  
Raman Scattering Spectrum ◽  
Correction Algorithm ◽  
Detection Algorithms ◽  
Scattering Spectrum ◽  
Gaussian Vectors

Raman spectroscopy, which analyzes a Raman scattering spectrum of a target, has emerged as a key technology for non-contact chemical agent (CA) detection. Many CA detection algorithms based on Raman spectroscopy have been studied. However, the baseline, which is caused by fluorescence generated when measuring the Raman scattering spectrum, degrades the performance of CA detection algorithms. Therefore, we propose a baseline correction algorithm that removes the baseline, while minimizing the distortion of the Raman scattering spectrum. Assuming that the baseline is a linear combination of broad Gaussian vectors, we model the measured spectrum as a linear combination of broad Gaussian vectors, bases of background materials and the reference spectra of target CAs. Then, we estimate the baseline and Raman scattering spectrum together using the least squares method. Design parameters of the broad Gaussian vectors are discussed. The proposed algorithm requires reference spectra of target CAs and the background basis matrix. Such prior information can be provided when applying the CA detection algorithm. Via the experiment with real CA spectra measured by the Raman spectrometer, we show that the proposed baseline correction algorithm is more effective for removing the baseline and improving the detection performance, than conventional baseline correction algorithms.

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