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Camera Calibration for Water-Biota Research: The Projected Area of Vegetation

Imaging systems have an indisputable role in revealing vegetation posture under diverse flow conditions, image sequences being generated with off the shelf digital cameras. Such sensors are cheap but introduce a range of distortion effects, a trait only marginally tackled in hydraulic studies focusi...

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Detalles Bibliográficos
Autores principales: Wackrow, Rene, Ferreira, Edgar, Chandler, Jim, Shiono, Koji
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2015
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4721719/
https://www.ncbi.nlm.nih.gov/pubmed/26633423
http://dx.doi.org/10.3390/s151229798
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author Wackrow, Rene
Ferreira, Edgar
Chandler, Jim
Shiono, Koji
author_facet Wackrow, Rene
Ferreira, Edgar
Chandler, Jim
Shiono, Koji
author_sort Wackrow, Rene
collection PubMed
description Imaging systems have an indisputable role in revealing vegetation posture under diverse flow conditions, image sequences being generated with off the shelf digital cameras. Such sensors are cheap but introduce a range of distortion effects, a trait only marginally tackled in hydraulic studies focusing on water-vegetation dependencies. This paper aims to bridge this gap by presenting a simple calibration method to remove both camera lens distortion and refractive effects of water. The effectiveness of the method is illustrated using the variable projected area, computed for both simple and complex shaped objects. Results demonstrate the significance of correcting images using a combined lens distortion and refraction model, prior to determining projected areas and further data analysis. Use of this technique is expected to increase data reliability for future work on vegetated channels.
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spelling pubmed-47217192016-01-26 Camera Calibration for Water-Biota Research: The Projected Area of Vegetation Wackrow, Rene Ferreira, Edgar Chandler, Jim Shiono, Koji Sensors (Basel) Article Imaging systems have an indisputable role in revealing vegetation posture under diverse flow conditions, image sequences being generated with off the shelf digital cameras. Such sensors are cheap but introduce a range of distortion effects, a trait only marginally tackled in hydraulic studies focusing on water-vegetation dependencies. This paper aims to bridge this gap by presenting a simple calibration method to remove both camera lens distortion and refractive effects of water. The effectiveness of the method is illustrated using the variable projected area, computed for both simple and complex shaped objects. Results demonstrate the significance of correcting images using a combined lens distortion and refraction model, prior to determining projected areas and further data analysis. Use of this technique is expected to increase data reliability for future work on vegetated channels. MDPI 2015-12-03 /pmc/articles/PMC4721719/ /pubmed/26633423 http://dx.doi.org/10.3390/s151229798 Text en © 2015 by the authors; licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons by Attribution (CC-BY) license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Wackrow, Rene
Ferreira, Edgar
Chandler, Jim
Shiono, Koji
Camera Calibration for Water-Biota Research: The Projected Area of Vegetation
title Camera Calibration for Water-Biota Research: The Projected Area of Vegetation
title_full Camera Calibration for Water-Biota Research: The Projected Area of Vegetation
title_fullStr Camera Calibration for Water-Biota Research: The Projected Area of Vegetation
title_full_unstemmed Camera Calibration for Water-Biota Research: The Projected Area of Vegetation
title_short Camera Calibration for Water-Biota Research: The Projected Area of Vegetation
title_sort camera calibration for water-biota research: the projected area of vegetation
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4721719/
https://www.ncbi.nlm.nih.gov/pubmed/26633423
http://dx.doi.org/10.3390/s151229798
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