A new and practical method to obtain grain size measurements in sandy shores based
Autor(a) principal: | |
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Data de Publicação: | 2012 |
Outros Autores: | , , |
Tipo de documento: | Artigo |
Idioma: | eng |
Título da fonte: | Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
Texto Completo: | http://hdl.handle.net/10174/7373 https://doi.org/10.1016/j.sedgeo.2012.10.005 |
Resumo: | Modern methods for the automated evaluation of sediment size in sandy shores relay on digital image processing algorithms as an alternative to time-consuming traditional sieving methodologies. However, the requirements necessary to guarantee that the considered image processing algorithm has a good grain identification success rate impose the need for dedicated hardware setups to capture the sand surface images. Examples are specially designed camera housings that maintain a constant distance between the camera lens and the sand surface, tripods to fix and maintain the camera angle orthogonal to the sand surface, external illumination systems that guarantee the light level necessary for the image processing algorithms, and special lenses and focusing systems for close proximity image capturing. In some cases, controlled image-capturing conditions can make the fieldwork more laborious which incurs in significant costs for monitoring campaigns considering large areas. To circumvent this problem, it is proposed a new automated image-processing algorithm that identifies sand grains in digital images acquired with a standard digital camera without any extra hardware attached to it. The accuracy and robustness of the proposed algorithm are evaluated in this work by means of a laboratory test on previously controlled grain samples, field tests where 64 samples (spread over a beach stretch of 65 km and with grain size ranging from 0.5 mm to 1.9 mm) were processed by both the proposed method and by sieving and finally by manual point count on all acquired images. The calculated root-mean-square (RMS) error between mean grain sizes obtained from the proposed image processing method and the sieve method (for the 64 samples) was 0.33 mm, and for the image processing method versus manual point counts comparison, with the same images, was 0.12 mm. The achieved correlation coefficients (r) were 0.91 and 0.96, respectively. |
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Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
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7160 |
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A new and practical method to obtain grain size measurements in sandy shores basedBeach sedimentAlgorithmImage acquisitionGrain-sizeMorphometricsModern methods for the automated evaluation of sediment size in sandy shores relay on digital image processing algorithms as an alternative to time-consuming traditional sieving methodologies. However, the requirements necessary to guarantee that the considered image processing algorithm has a good grain identification success rate impose the need for dedicated hardware setups to capture the sand surface images. Examples are specially designed camera housings that maintain a constant distance between the camera lens and the sand surface, tripods to fix and maintain the camera angle orthogonal to the sand surface, external illumination systems that guarantee the light level necessary for the image processing algorithms, and special lenses and focusing systems for close proximity image capturing. In some cases, controlled image-capturing conditions can make the fieldwork more laborious which incurs in significant costs for monitoring campaigns considering large areas. To circumvent this problem, it is proposed a new automated image-processing algorithm that identifies sand grains in digital images acquired with a standard digital camera without any extra hardware attached to it. The accuracy and robustness of the proposed algorithm are evaluated in this work by means of a laboratory test on previously controlled grain samples, field tests where 64 samples (spread over a beach stretch of 65 km and with grain size ranging from 0.5 mm to 1.9 mm) were processed by both the proposed method and by sieving and finally by manual point count on all acquired images. The calculated root-mean-square (RMS) error between mean grain sizes obtained from the proposed image processing method and the sieve method (for the 64 samples) was 0.33 mm, and for the image processing method versus manual point counts comparison, with the same images, was 0.12 mm. The achieved correlation coefficients (r) were 0.91 and 0.96, respectively.Sedimentary Geology2013-01-17T11:14:01Z2013-01-172012-12-01T00:00:00Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articlehttp://hdl.handle.net/10174/7373http://hdl.handle.net/10174/7373https://doi.org/10.1016/j.sedgeo.2012.10.005eng-Baptista, P.; Cunha, T.; Gama, C.; Bernardes, C. (2012)- A new and practical method to obtain grain size measurements in sandy shores based on digital image acquisition and processing. Sedimentary Geology, 282, 294–306.ndndndnd250Baptista, PauloCunha, TelmoGama, CristinaBernardes, Cristinainfo:eu-repo/semantics/openAccessreponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãoinstacron:RCAAP2024-01-03T18:47:36Zoai:dspace.uevora.pt:10174/7373Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-20T01:01:55.610308Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãofalse |
dc.title.none.fl_str_mv |
A new and practical method to obtain grain size measurements in sandy shores based |
title |
A new and practical method to obtain grain size measurements in sandy shores based |
spellingShingle |
A new and practical method to obtain grain size measurements in sandy shores based Baptista, Paulo Beach sediment Algorithm Image acquisition Grain-size Morphometrics |
title_short |
A new and practical method to obtain grain size measurements in sandy shores based |
title_full |
A new and practical method to obtain grain size measurements in sandy shores based |
title_fullStr |
A new and practical method to obtain grain size measurements in sandy shores based |
title_full_unstemmed |
A new and practical method to obtain grain size measurements in sandy shores based |
title_sort |
A new and practical method to obtain grain size measurements in sandy shores based |
author |
Baptista, Paulo |
author_facet |
Baptista, Paulo Cunha, Telmo Gama, Cristina Bernardes, Cristina |
author_role |
author |
author2 |
Cunha, Telmo Gama, Cristina Bernardes, Cristina |
author2_role |
author author author |
dc.contributor.author.fl_str_mv |
Baptista, Paulo Cunha, Telmo Gama, Cristina Bernardes, Cristina |
dc.subject.por.fl_str_mv |
Beach sediment Algorithm Image acquisition Grain-size Morphometrics |
topic |
Beach sediment Algorithm Image acquisition Grain-size Morphometrics |
description |
Modern methods for the automated evaluation of sediment size in sandy shores relay on digital image processing algorithms as an alternative to time-consuming traditional sieving methodologies. However, the requirements necessary to guarantee that the considered image processing algorithm has a good grain identification success rate impose the need for dedicated hardware setups to capture the sand surface images. Examples are specially designed camera housings that maintain a constant distance between the camera lens and the sand surface, tripods to fix and maintain the camera angle orthogonal to the sand surface, external illumination systems that guarantee the light level necessary for the image processing algorithms, and special lenses and focusing systems for close proximity image capturing. In some cases, controlled image-capturing conditions can make the fieldwork more laborious which incurs in significant costs for monitoring campaigns considering large areas. To circumvent this problem, it is proposed a new automated image-processing algorithm that identifies sand grains in digital images acquired with a standard digital camera without any extra hardware attached to it. The accuracy and robustness of the proposed algorithm are evaluated in this work by means of a laboratory test on previously controlled grain samples, field tests where 64 samples (spread over a beach stretch of 65 km and with grain size ranging from 0.5 mm to 1.9 mm) were processed by both the proposed method and by sieving and finally by manual point count on all acquired images. The calculated root-mean-square (RMS) error between mean grain sizes obtained from the proposed image processing method and the sieve method (for the 64 samples) was 0.33 mm, and for the image processing method versus manual point counts comparison, with the same images, was 0.12 mm. The achieved correlation coefficients (r) were 0.91 and 0.96, respectively. |
publishDate |
2012 |
dc.date.none.fl_str_mv |
2012-12-01T00:00:00Z 2013-01-17T11:14:01Z 2013-01-17 |
dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/article |
format |
article |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
http://hdl.handle.net/10174/7373 http://hdl.handle.net/10174/7373 https://doi.org/10.1016/j.sedgeo.2012.10.005 |
url |
http://hdl.handle.net/10174/7373 https://doi.org/10.1016/j.sedgeo.2012.10.005 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
-Baptista, P.; Cunha, T.; Gama, C.; Bernardes, C. (2012)- A new and practical method to obtain grain size measurements in sandy shores based on digital image acquisition and processing. Sedimentary Geology, 282, 294–306. nd nd nd nd 250 |
dc.rights.driver.fl_str_mv |
info:eu-repo/semantics/openAccess |
eu_rights_str_mv |
openAccess |
dc.publisher.none.fl_str_mv |
Sedimentary Geology |
publisher.none.fl_str_mv |
Sedimentary Geology |
dc.source.none.fl_str_mv |
reponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação instacron:RCAAP |
instname_str |
Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação |
instacron_str |
RCAAP |
institution |
RCAAP |
reponame_str |
Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
collection |
Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
repository.name.fl_str_mv |
Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação |
repository.mail.fl_str_mv |
|
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1799136503145693184 |