Research of Imgae Features for Classification of Wear Debris

Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216305%3A26230%2F12%3APU98178" target="_blank" >RIV/00216305:26230/12:PU98178 - isvavai.cz</a>
Result on the web
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DOI - Digital Object Identifier
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Result language
angličtina
Original language name
Research of Imgae Features for Classification of Wear Debris
Original language 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.
Czech name
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Czech description
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Type
J<sub>x</sub> - Unclassified - Peer-reviewed scientific article (Jimp, Jsc and Jost)
CEP classification
JC - Computer hardware and software
OECD FORD branch
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Project
<a href="/en/project/ED1.1.00%2F02.0070" target="_blank" >ED1.1.00/02.0070: IT4Innovations Centre of Excellence</a><br>
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)<br>S - Specificky vyzkum na vysokych skolach

Publication year
2012
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

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