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Authors: Konstantin Trambitckii ; Katharina Anding ; Lilli Haar and Gunther Notni

Affiliation: Institute of Mechanical Engineering, Department of Quality Assurance and Industrial Image Processing, Ilmenau University of Technology, Gustav-Kirchhoff-Platz 2, Ilmenau and Germany

Keyword(s): Quality Assurance, Image Processing, Texture Features, Roughness Parameters, Metal Parts.

Related Ontology Subjects/Areas/Topics: Feature Selection and Extraction ; Pattern Recognition ; Theory and Methods

Abstract: Fast developing of computer technologies led to vast improvements of image processing systems and algorithms. Nowadays these algorithms are widely used in different areas of computer and machine vision systems. In this research texture features were used to analyse metal surfaces using a set of images obtained with industrial camera with macro lens. This kind of contactless surface roughness estimation is cheaper and quicker in comparison with traditional methods. A set of 27 texture features were calculated for a set of surface images. Correlation coefficients between the texture features and 10 roughness parameters for the sample surfaces were estimated. Obtained results showed that texture features can be successfully used for quick surface quality estimation.

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Paper citation in several formats:
Trambitckii, K.; Anding, K.; Haar, L. and Notni, G. (2019). Estimation of Correlation between Texture Features and Surface Parameters for Milled Metal Parts. In Proceedings of the 8th International Conference on Pattern Recognition Applications and Methods - ICPRAM; ISBN 978-989-758-351-3; ISSN 2184-4313, SciTePress, pages 421-428. DOI: 10.5220/0007344104210428

@conference{icpram19,
author={Konstantin Trambitckii. and Katharina Anding. and Lilli Haar. and Gunther Notni.},
title={Estimation of Correlation between Texture Features and Surface Parameters for Milled Metal Parts},
booktitle={Proceedings of the 8th International Conference on Pattern Recognition Applications and Methods - ICPRAM},
year={2019},
pages={421-428},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0007344104210428},
isbn={978-989-758-351-3},
issn={2184-4313},
}

TY - CONF

JO - Proceedings of the 8th International Conference on Pattern Recognition Applications and Methods - ICPRAM
TI - Estimation of Correlation between Texture Features and Surface Parameters for Milled Metal Parts
SN - 978-989-758-351-3
IS - 2184-4313
AU - Trambitckii, K.
AU - Anding, K.
AU - Haar, L.
AU - Notni, G.
PY - 2019
SP - 421
EP - 428
DO - 10.5220/0007344104210428
PB - SciTePress

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