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Authors: Jean Fabrício Batista Santos ; Jocival Dantas Dias Junior ; André Ricardo Backes and Maurício Cunha Escarpinati

Affiliation: School of Computer Science, Federal University of Uberlândia, Brazil

Keyword(s): Precision Agriculture, Plant Segmentation, Vegetation Indices.

Abstract: Identifying and segmenting plants from the background in agricultural images is of great importance for precision agriculture. It serves as a basis for several tasks such as identification of planting lines, identification of weed plants, agricultural automation, among others. Given this importance, in this paper, we evaluated the application of five vegetation indices for RGB images together with two binarization techniques for the plant/background segmentation process. The results showed promising performance in all evaluated indices. It was also possible to identify a relationship between the performance obtained in each index and the capture conditions in each dataset.

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Paper citation in several formats:
Santos, J.; Dias Junior, J.; Backes, A. and Escarpinati, M. (2021). Segmentation of Agricultural Images using Vegetation Indices. In Proceedings of the 16th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2021) - Volume 4: VISAPP; ISBN 978-989-758-488-6; ISSN 2184-4321, SciTePress, pages 506-511. DOI: 10.5220/0010325005060511

@conference{visapp21,
author={Jean Fabrício Batista Santos. and Jocival Dantas {Dias Junior}. and André Ricardo Backes. and Maurício Cunha Escarpinati.},
title={Segmentation of Agricultural Images using Vegetation Indices},
booktitle={Proceedings of the 16th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2021) - Volume 4: VISAPP},
year={2021},
pages={506-511},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0010325005060511},
isbn={978-989-758-488-6},
issn={2184-4321},
}

TY - CONF

JO - Proceedings of the 16th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2021) - Volume 4: VISAPP
TI - Segmentation of Agricultural Images using Vegetation Indices
SN - 978-989-758-488-6
IS - 2184-4321
AU - Santos, J.
AU - Dias Junior, J.
AU - Backes, A.
AU - Escarpinati, M.
PY - 2021
SP - 506
EP - 511
DO - 10.5220/0010325005060511
PB - SciTePress

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