Detail publikačního výsledku

Research of Image Features for Classification of Wear Debris

MACHALÍK, S.; JURÁNEK, R.; ZEMČÍK, P.

Originální název

Research of Image Features for Classification of Wear Debris

Anglický název

Research of Image Features for Classification of Wear Debris

Druh

Článek recenzovaný mimo WoS a Scopus

Originální abstrakt

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.

Anglický abstrakt

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.

Klíčová slova

Wear Debris, Classification, Supervised Machine Learning, SVM, Linear Regression,
Features, PCA, HOG, LBP

Klíčová slova v angličtině

Wear Debris, Classification, Supervised Machine Learning, SVM, Linear Regression,
Features, PCA, HOG, LBP

Autoři

MACHALÍK, S.; JURÁNEK, R.; ZEMČÍK, P.

Rok RIV

2013

Vydáno

01.02.2012

ISSN

1230-0535

Periodikum

Machine Graphics and Vision

Svazek

20

Číslo

1

Stát

Polská republika

Strany od

479

Strany do

493

Strany počet

15

BibTex

@article{BUT91470,
  author="Stanislav {Machalík} and Roman {Juránek} and Pavel {Zemčík}",
  title="Research of Image Features for Classification of Wear Debris",
  journal="Machine Graphics and Vision",
  year="2012",
  volume="20",
  number="1",
  pages="479--493",
  issn="1230-0535"
}