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Multi-Spectral Imaging for Weed Identification in Herbicides Testing
Volume 33, Issue 4 (2022), pp. 771–793
Pub. online: 30 November 2022      Type: Research Article      Open accessOpen Access
Received
1 February 2022
Accepted
1 November 2022
Published
30 November 2022

Abstract

A new methodology to help to improve the efficiency of herbicide assessment is explained. It consists of an automatic tool to quantify the percentage of weeds and plants of interest (sunflowers) that are present in a given area. Images of the crop field taken from Sequoia camera were used. Firstly, the quality of the images of each band is improved. Later, the resulting multi-spectral images are classified into several classes (soil, sunflower and weed) through a novel algorithm implemented in e-Cognition software. Obtained results of the proposed classifications have been compared with two deep learning-based segmentation methods (U-Net and FPN).

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Biographies

López Luis O.
lol766@inlumine.ual.es

L.O. López is a predoctoral researcher at the Informatics Department at University of Almería, Spain. He obtained his master’s degree in computer engineering from the University of Almería. His research interests include image processing and high performance-computing. Personal web page: https://github.com/Heikelol/SegmentationForPlants.

Ortega Gloria
https://orcid.org/0000-0002-6563-2717
gloriaortega@ual.es

G. Ortega is an assistant professor at the Informatics Department at the University of Almería, Spain. She obtained her PhD from the University of Almería. Her publications can be found on https://www.scopus.com/authid/detail.uri?authorId=36624080600. Her research interests include high performance-computing, quantum computing and modelling optimization problems. Personal web page: https://sites.google.com/site/gloriaortegalopez/.

Agüera-Vega Francisco
https://orcid.org/0000-0003-0709-3388
faguera@ual.es

F. Agüera-Vega is a full professor at the Department of Engineering at the University of Almería, Spain. He obtained her PhD from the University of Almería, Spain. His publications can be found on https://www.scopus.com/authid/detail.uri?authorId=57201033449. His research interests include UAV photogrammetry and remote sensing for the analysis and evaluation of productive and natural resources. Personal web page: http://brujula.ual.es/authors/7.html.

Carvajal-Ramírez Fernando
https://orcid.org/0000-0001-7791-0991
carvajal@ual.es

F. Carvajal-Ramírez is an assistant professor at the Department of Engineering at the University of Almería, Spain. He obtained his PhD from the University of Almería. His publications can be found on https://www.scopus.com/authid/detail.uri?authorId=57201031500. His research interests include UAV Photogrammetry and Remote Sensing for Agriculture Precision. Personal web page: https://w3.ual.es/~carvajal/.

Martínez-Carricondo Patricio
pmc824@ual.es

P. Martínez-Carricondo is an assistant professor at the Department of Engineering at the University of Almería, Spain. He obtained his PhD from the University of Almería. His publications can be found on https://www.scopus.com/authid/detail.uri?authorId=57191432058. His research interests include the application of drones to precision agricultural engineering, civil engineering and archaeology and remote sensing for the analysis and evaluation of productive and natural resources. Personal web page: https://www.researchgate.net/profile/Patricio-Martinez-Carricondo.

Garzón Ester M.
https://orcid.org/0000-0002-0568-5470
gmartin@ual.es

E.M. Garzón is a full professor at the Informatics Department at the University of Almería, Spain. She obtained her PhD from the University of Almería, Spain. Her publications can be found on https://www.scopus.com/authid/detail.uri?authorId=6603580566. Her research interests include sparse matrix computation, image processing and high-performance computing. Personal web page: https://hpca.ual.es/~gmartin/.


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Keywords
multi-spectral images multi-spectral classification herbicide assessment deep learning segmentation e-Cognition

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