Classification of Dust Elements by Spatial Geometric Features

A. Proietti, M. Panella, E. D. Di Claudio, G. Jacovitti, G. Orlandi

2016

Abstract

Management of air quality is an important task in many human activities. It is carried out mainly by installing ventilation and filtering facilities. In order to ensure efficiency, these systems must be designed after the knowledge of key environmental parameters, such as size and type of particles and fibres present in the air. In this paper, we propose a new method for the classification of dust particles and fibres based on a minimal set of geometric features extracted from binary images of dust elements, captured by a very cheap imaging system. The proposed technique is discussed and tested. Experimental results obtained by real- measured data are presented, showing satisfactory performance by using several well-known classifiers.

Paper Citation

in Harvard Style

Proietti A., Panella M., Di Claudio E., Jacovitti G. and Orlandi G. (2016). Classification of Dust Elements by Spatial Geometric Features . In Proceedings of the 5th International Conference on Pattern Recognition Applications and Methods - Volume 1: ICPRAM, ISBN 978-989-758-173-1, pages 247-254. DOI: 10.5220/0005697502470254

in Bibtex Style

@conference{icpram16,
author={A. Proietti and M. Panella and E. D. Di Claudio and G. Jacovitti and G. Orlandi},
title={Classification of Dust Elements by Spatial Geometric Features},
booktitle={Proceedings of the 5th International Conference on Pattern Recognition Applications and Methods - Volume 1: ICPRAM,},
year={2016},
pages={247-254},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0005697502470254},
isbn={978-989-758-173-1},
}

in EndNote Style

TY - CONF
JO - Proceedings of the 5th International Conference on Pattern Recognition Applications and Methods - Volume 1: ICPRAM,
TI - Classification of Dust Elements by Spatial Geometric Features
SN - 978-989-758-173-1
AU - Proietti A.
AU - Panella M.
AU - Di Claudio E.
AU - Jacovitti G.
AU - Orlandi G.
PY - 2016
SP - 247
EP - 254
DO - 10.5220/0005697502470254