Fast Classification of Brick Samples by Combination of
Principal Component Analysis and Linear Discriminant Analysis
Using Standoff Laser-Induced Breakdown Spectroscopy

a 2013

Fast Classification of Brick Samples by Combination of Principal Component Analysis and Linear Discriminant Analysis Using Standoff Laser-Induced Breakdown Spectroscopy

VÍTKOVÁ, Gabriela; Lubomír PROKEŠ; Karel NOVOTNÝ; Aleš HRDLIČKA; Jan NOVOTNÝ et. al.

Basic information

Original name

Fast Classification of Brick Samples by Combination of Principal Component Analysis and Linear Discriminant Analysis Using Standoff Laser-Induced Breakdown Spectroscopy

Authors

VÍTKOVÁ, Gabriela (203 Czech Republic, belonging to the institution); Lubomír PROKEŠ (203 Czech Republic, belonging to the institution); Karel NOVOTNÝ (203 Czech Republic, guarantor, belonging to the institution); Aleš HRDLIČKA (203 Czech Republic, belonging to the institution); Jan NOVOTNÝ (203 Czech Republic) and Jozef KAISER (203 Czech Republic)

Edition

Euro-Mediterranean Symposium on Laser Induced Breakdown Spectroscopy 2013, 2013

Other information

Language

English

Type of outcome

Conference abstract

Field of Study

10406 Analytical chemistry

Country of publisher

Italy

Confidentiality degree

is not subject to a state or trade secret

RIV identification code

RIV/00216224:14740/13:00070570

Organization unit

Central European Institute of Technology

Keywords in English

Stand-off LIBS; PCA; LDA; ANN; Geomaterials; Archeology

Changed: 14/2/2014 14:18, doc. Mgr. Karel Novotný, Ph.D.

Abstract

V originále

LDA is a multivariate statistical method for discrimination of objects up to a finite number of categories, based on a certain subset of all objects (training set). The principle of this method is maximizing the ratio of the between-class variance to the within-class variance. The decision rules obtained by classification of training set are later applied to the testing set. PCA was applied to reduce a dimensionality and the scores were computed from whole spectra (200 – 1000 nm) of 29 brick samples obtained by stand-off LIBS. After dividing the sample set into training and test samples first few principal components were used as inputs to LDA and the predictions of localities were computed. The results suggest that stand-off LIBS in combination with advanced statistical methods has a big potential for archaeological in-field measurements. By examining of PCA scores there was also discovered a dependence of firing temperature of bricks. Spectra of bricks fired on 300 – 1000 Celsius differs and this property is reflected significantly in only one of the principal components.

Links

ED1.1.00/02.0068, research and development project

Name: CEITEC - central european institute of technology

Cite

VÍTKOVÁ, Gabriela; Lubomír PROKEŠ; Karel NOVOTNÝ; Aleš HRDLIČKA; Jan NOVOTNÝ and Jozef KAISER. Fast Classification of Brick Samples by Combination of Principal Component Analysis and Linear Discriminant Analysis Using Standoff Laser-Induced Breakdown Spectroscopy. In Euro-Mediterranean Symposium on Laser Induced Breakdown Spectroscopy 2013. 2013.

@proceedings{1137328,
   author = {Vítková, Gabriela and Prokeš, Lubomír and Novotný, Karel and Hrdlička, Aleš and Novotný, Jan and Kaiser, Jozef},
   booktitle = {Euro-Mediterranean Symposium on Laser Induced Breakdown Spectroscopy 2013},
   keywords = {Stand-off LIBS; PCA; LDA; ANN; Geomaterials; Archeology},
   language = {eng},
   title = {Fast Classification of Brick Samples by Combination of Principal Component Analysis and Linear Discriminant Analysis Using Standoff Laser-Induced Breakdown Spectroscopy},
   year = {2013}
}

TY  - CONF
ID  - 1137328
AU  - Vítková, Gabriela - Prokeš, Lubomír - Novotný, Karel - Hrdlička, Aleš - Novotný, Jan - Kaiser, Jozef
PY  - 2013
TI  - Fast Classification of Brick Samples by Combination of Principal Component Analysis and Linear Discriminant Analysis Using Standoff Laser-Induced Breakdown Spectroscopy
KW  - Stand-off LIBS
KW  - PCA
KW  - LDA
KW  - ANN
KW  - Geomaterials
KW  - Archeology
N2  - LDA is a multivariate statistical method for discrimination of objects up to a finite number of categories, based on a certain subset of all objects (training set). The principle of this method is maximizing the ratio of the between-class variance to the within-class variance. The decision rules obtained by classification of training set are later applied to the testing set. PCA was applied to reduce a dimensionality and the scores were computed from whole spectra (200 – 1000 nm) of 29 brick samples obtained by stand-off LIBS. After dividing the sample set into training and test samples first few principal components were used as inputs to LDA and the predictions of localities were computed. The results suggest that stand-off LIBS in combination with advanced statistical methods has a big potential for archaeological in-field measurements. By examining of PCA scores there was also discovered a dependence of firing temperature of bricks. Spectra of bricks fired on 300 – 1000 Celsius differs and this property is reflected significantly in only one of the principal components.
ER  -

VÍTKOVÁ, Gabriela; Lubomír PROKEŠ; Karel NOVOTNÝ; Aleš HRDLIČKA; Jan NOVOTNÝ and Jozef KAISER. Fast Classification of Brick Samples by Combination of Principal Component Analysis and Linear Discriminant Analysis Using Standoff Laser-Induced Breakdown Spectroscopy. In \textit{Euro-Mediterranean Symposium on Laser Induced Breakdown Spectroscopy 2013}. 2013.

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