Detection of Control Points for UAV-Multispectral Sensed Data Registration through the Combining of Feature Descriptors

Jocival Dantas Dias Junior, André Ricardo Backes, Maurício Cunha Escarpinati

2019

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.

Paper Citation

in Harvard Style

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, SciTePress, pages 444-451. DOI: 10.5220/0007580204440451

in Bibtex Style

@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},
}

in EndNote Style

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
AU - Dias Junior J.
AU - Backes A.
AU - Escarpinati M.
PY - 2019
SP - 444
EP - 451
DO - 10.5220/0007580204440451
PB - SciTePress