Efficient Marble Slab Classification using Simple Features

Mert Kilickaya, Umut Cinar, Sinan Ugurluoglu

Abstract

The marbles consist a large part of the buildings and widely used. Though, the manufacturing process for marbles are time consuming and inefficient: Human experts assign inconsistent labels to different marble classes causing a big loss of time and money. It arises the need for an automatic method of classifying marbles. In this paper we present a novel method which utilizes color, structural and textural representations of a marble. Once the representation is combined with an accurate segmentation step, it achieves an accuracy of 94% on a newly collected dataset of 1000 images. We suggest the best settings for an automatic marble classification system which is simple and fast enough to be used in a real-life environment like marble factories.

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Paper Citation


in Harvard Style

Kilickaya M., Cinar U. and Ugurluoglu S. (2016). Efficient Marble Slab Classification using Simple Features . In Proceedings of the 11th Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - Volume 4: VISAPP, (VISIGRAPP 2016) ISBN 978-989-758-175-5, pages 192-199. DOI: 10.5220/0005723201920199


in Bibtex Style

@conference{visapp16,
author={Mert Kilickaya and Umut Cinar and Sinan Ugurluoglu},
title={Efficient Marble Slab Classification using Simple Features},
booktitle={Proceedings of the 11th Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - Volume 4: VISAPP, (VISIGRAPP 2016)},
year={2016},
pages={192-199},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0005723201920199},
isbn={978-989-758-175-5},
}


in EndNote Style

TY - CONF
JO - Proceedings of the 11th Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - Volume 4: VISAPP, (VISIGRAPP 2016)
TI - Efficient Marble Slab Classification using Simple Features
SN - 978-989-758-175-5
AU - Kilickaya M.
AU - Cinar U.
AU - Ugurluoglu S.
PY - 2016
SP - 192
EP - 199
DO - 10.5220/0005723201920199