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Authors: Jocival Dantas Dias Junior ; André Ricardo Backes and Maurício Cunha Escarpinati

Affiliation: Faculty of Computing, Federal University of Uberlândia, Uberlândia/MG and Brazil

Keyword(s): Image Registration, Unmanned Aerial Vehicle, Multispectral Image, Feature Descriptors.

Related Ontology Subjects/Areas/Topics: Computer Vision, Visualization and Computer Graphics ; Features Extraction ; Image and Video Analysis ; Image Registration

Abstract: The popularization of the Unmanned Aerial Vehicle (UAV) and the development of new sensors has enabled the acquisition and use of multispectral and hyperspectral images in precision agriculture. However, performing the image registration process is a complex task due to the lack of image characteristics among the various spectra and the distortions created by the use of the UAV during the acquisition process. Therefore, the objective of this work is to evaluate different techniques for obtaining control points in multispectral images of soybean plantations obtained by UAVs and to investigate if combining features obtained by different techniques generates better results than when used individually. In this work Were evaluated 3 different feature detection algorithms (KAZE, MEF and BRISK) and their combinations. Results shown that the KAZE technique, achieve better results.

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Paper citation in several formats:
Dias Junior, J.; Backes, A. and Escarpinati, M. (2019). Detection of Control Points for UAV-Multispectral Sensed Data Registration through the Combining of Feature Descriptors. In Proceedings of the 14th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2019) - Volume 4: VISAPP; ISBN 978-989-758-354-4; ISSN 2184-4321, SciTePress, pages 444-451. DOI: 10.5220/0007580204440451

@conference{visapp19,
author={Jocival Dantas {Dias Junior}. and André Ricardo Backes. and Maurício Cunha Escarpinati.},
title={Detection of Control Points for UAV-Multispectral Sensed Data Registration through the Combining of Feature Descriptors},
booktitle={Proceedings of the 14th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2019) - Volume 4: VISAPP},
year={2019},
pages={444-451},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0007580204440451},
isbn={978-989-758-354-4},
issn={2184-4321},
}

TY - CONF

JO - Proceedings of the 14th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2019) - Volume 4: VISAPP
TI - Detection of Control Points for UAV-Multispectral Sensed Data Registration through the Combining of Feature Descriptors
SN - 978-989-758-354-4
IS - 2184-4321
AU - Dias Junior, J.
AU - Backes, A.
AU - Escarpinati, M.
PY - 2019
SP - 444
EP - 451
DO - 10.5220/0007580204440451
PB - SciTePress

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