The Application of Principal Component Analysis to Boost The Performance of The Automated Fabric Fault Detector And Classifier
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F46747885%3A24410%2F14%3A%230003698" target="_blank" >RIV/46747885:24410/14:#0003698 - isvavai.cz</a>
Result on the web
<a href="http://www.fibtex.lodz.pl/2014/4/51.pdf" target="_blank" >http://www.fibtex.lodz.pl/2014/4/51.pdf</a>
DOI - Digital Object Identifier
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Alternative languages
Result language
angličtina
Original language name
The Application of Principal Component Analysis to Boost The Performance of The Automated Fabric Fault Detector And Classifier
Original language description
There is a growing need to replace visual fabric inspection with automated systems that detect and classify fabric defects. The digital processing of fabric images utilises different methods that offer a large set of image features. The correlation between those features lead to problems during fabric fault classification and reduces the performance of the classifiers. This work extracted a combination of statistical (spatial) and Fourier transform (spectral) features from fabric images of the most frequent faults. Principal component analysis (PCA) was implemented to reduce the dimensionality of the input feature dataset, which achieved a reduction to 36% of the original data size while preserving 99% of information in the original dataset. The features processed using the PCA were fed to an artificial neural network (ANN) to classify the fault categories and then compared to another ANN that worked with the whole feature dataset. The performance of the network that was implemented af
Czech name
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Czech description
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Classification
Type
J<sub>x</sub> - Unclassified - Peer-reviewed scientific article (Jimp, Jsc and Jost)
CEP classification
JS - Reliability and quality management, industrial testing
OECD FORD branch
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Result continuities
Project
<a href="/en/project/EE2.3.30.0065" target="_blank" >EE2.3.30.0065: Support of the creation of excellent research and development teams at the Technical University of Liberec</a><br>
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)
Others
Publication year
2014
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Name of the periodical
Fibres & Textiles in Eastern Europe
ISSN
1230-3666
e-ISSN
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Volume of the periodical
22
Issue of the periodical within the volume
4
Country of publishing house
PL - POLAND
Number of pages
7
Pages from-to
51-57
UT code for WoS article
000338825300008
EID of the result in the Scopus database
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