About: Research of Imgae Features for Classification of Wear Debris

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An Entity of Type : http://linked.opendata.cz/ontology/domain/vavai/Vysledek, within Data Space : linked.opendata.cz associated with source document(s)

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rdf:type	skos:Concept http://linked.opendata.cz/ontology/domain/vavai/Vysledek
Description	The wear debris of various engineering equipment (such as combustion engines, gearboxes, etc.) consists of particles of metal which can be obtained from lubricants used in such machine parts. The analysis the wear particles is very important for early detection and prevention of failures in engineering equipment. The analysis is often done through classification of individual wear particles obtained by analytical ferrography. In this paper, we present a study of feature extraction methods for a classification of the wear particles based on visual similarity (using supervised machine learning). The main contribution of the paper is the comparison of nine selected feature types in the context of three state-of-the-art learning models. Another contribution is the large public database of binary images of particles which can be used for further experiments. The wear debris of various engineering equipment (such as combustion engines, gearboxes, etc.) consists of particles of metal which can be obtained from lubricants used in such machine parts. The analysis the wear particles is very important for early detection and prevention of failures in engineering equipment. The analysis is often done through classification of individual wear particles obtained by analytical ferrography. In this paper, we present a study of feature extraction methods for a classification of the wear particles based on visual similarity (using supervised machine learning). The main contribution of the paper is the comparison of nine selected feature types in the context of three state-of-the-art learning models. Another contribution is the large public database of binary images of particles which can be used for further experiments. (en)
Title	Research of Imgae Features for Classification of Wear Debris Research of Imgae Features for Classification of Wear Debris (en)
skos:prefLabel	Research of Imgae Features for Classification of Wear Debris Research of Imgae Features for Classification of Wear Debris (en)
skos:notation	RIV/00216305:26230/12:PU98178!RIV13-MSM-26230___
http://linked.open...avai/riv/aktivita	P S
http://linked.open...avai/riv/aktivity	P(ED1.1.00/02.0070), S
http://linked.open...iv/cisloPeriodika	1
http://linked.open...vai/riv/dodaniDat	2013
http://linked.open...aciTvurceVysledku	Machalík, Stanislav Juránek, Roman Zemčík, Pavel
http://linked.open.../riv/druhVysledku	J - Článek v odborném periodiku
http://linked.open...iv/duvernostUdaju	S - Úplné a pravdivé údaje nepodléhající ochraně podle zvláštních právních předpisů
http://linked.open...titaPredkladatele	Vysoké učení technické v Brně / Fakulta informačních technologií
http://linked.open...dnocenehoVysledku	165132
http://linked.open...ai/riv/idVysledku	RIV/00216305:26230/12:PU98178
http://linked.open...riv/jazykVysledku	eng - angličtina
http://linked.open.../riv/klicovaSlova	Wear Debris, Classification, Supervised Machine Learning, SVM, Linear Regression,Features, PCA, HOG, LBP (en)
http://linked.open.../riv/klicoveSlovo	LBP SVM Wear Debris PCA Classification Linear Regression Supervised Machine Learning Features HOG
http://linked.open...odStatuVydavatele	PL - Polská republika
http://linked.open...ontrolniKodProRIV	[1467F7232315]
http://linked.open...i/riv/nazevZdroje	Machine Graphics and Vision
http://linked.open...in/vavai/riv/obor	JC
http://linked.open...ichTvurcuVysledku	3 (xsd:int)
http://linked.open...cetTvurcuVysledku	3 (xsd:int)
http://linked.open...vavai/riv/projekt	IT4Innovations Centre of Excellence
http://linked.open...UplatneniVysledku	2012
http://linked.open...v/svazekPeriodika	21
http://linked.open...iv/tvurceVysledku	Juránek, Roman Machalík, Stanislav Zemčík, Pavel
issn	1230-0535
number of pages	15 (xsd:int)
http://localhost/t...ganizacniJednotka	26230

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