Automatic lane detection in chromatography images

Detalhes bibliográficos
Autor(a) principal: Bruno M. Moreira
Data de Publicação: 2011
Outros Autores: António V. Sousa, Ana M. Mendonça, Aurélio C. Campilho
Tipo de documento: Livro
Idioma: eng
Título da fonte: Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
Texto Completo: https://hdl.handle.net/10216/85680
Resumo: This paper proposes a method for automating the detection of lanes in Thin-Layer Chromatography images. Our approach includes a preprocessing step to detect the image region of interest, followed by background estimation and removal. This image is then projected onto the horizontal direction to integrate the information into a one-dimensional profile. A smoothing filter is applied to this profile and the outcome is the input of the lane detection process, which is performed in three phases. The first one aims at obtaining an initial set of candidate lanes that are further validated or removed in the second phase. The last phase is a refinement step that allows the inclusion of lanes that are not clearly distinguishable in the profile and that were not included in the initial set. The method was evaluated in 66 chromatography images and achieved values of recall, precision and F ß -measure of 97.0%, 99.4% and 98.2%, respectively.
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spelling Automatic lane detection in chromatography imagesThis paper proposes a method for automating the detection of lanes in Thin-Layer Chromatography images. Our approach includes a preprocessing step to detect the image region of interest, followed by background estimation and removal. This image is then projected onto the horizontal direction to integrate the information into a one-dimensional profile. A smoothing filter is applied to this profile and the outcome is the input of the lane detection process, which is performed in three phases. The first one aims at obtaining an initial set of candidate lanes that are further validated or removed in the second phase. The last phase is a refinement step that allows the inclusion of lanes that are not clearly distinguishable in the profile and that were not included in the initial set. The method was evaluated in 66 chromatography images and achieved values of recall, precision and F ß -measure of 97.0%, 99.4% and 98.2%, respectively.20112011-01-01T00:00:00Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/bookapplication/pdfhttps://hdl.handle.net/10216/85680eng10.1007/978-3-642-31298-4_22Bruno M. MoreiraAntónio V. SousaAna M. MendonçaAurélio C. Campilhoinfo: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:RCAAP2023-11-29T13:47:07Zoai:repositorio-aberto.up.pt:10216/85680Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-19T23:47:31.756866Repositório 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 Automatic lane detection in chromatography images
title Automatic lane detection in chromatography images
spellingShingle Automatic lane detection in chromatography images
Bruno M. Moreira
title_short Automatic lane detection in chromatography images
title_full Automatic lane detection in chromatography images
title_fullStr Automatic lane detection in chromatography images
title_full_unstemmed Automatic lane detection in chromatography images
title_sort Automatic lane detection in chromatography images
author Bruno M. Moreira
author_facet Bruno M. Moreira
António V. Sousa
Ana M. Mendonça
Aurélio C. Campilho
author_role author
author2 António V. Sousa
Ana M. Mendonça
Aurélio C. Campilho
author2_role author
author
author
dc.contributor.author.fl_str_mv Bruno M. Moreira
António V. Sousa
Ana M. Mendonça
Aurélio C. Campilho
description This paper proposes a method for automating the detection of lanes in Thin-Layer Chromatography images. Our approach includes a preprocessing step to detect the image region of interest, followed by background estimation and removal. This image is then projected onto the horizontal direction to integrate the information into a one-dimensional profile. A smoothing filter is applied to this profile and the outcome is the input of the lane detection process, which is performed in three phases. The first one aims at obtaining an initial set of candidate lanes that are further validated or removed in the second phase. The last phase is a refinement step that allows the inclusion of lanes that are not clearly distinguishable in the profile and that were not included in the initial set. The method was evaluated in 66 chromatography images and achieved values of recall, precision and F ß -measure of 97.0%, 99.4% and 98.2%, respectively.
publishDate 2011
dc.date.none.fl_str_mv 2011
2011-01-01T00:00:00Z
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dc.identifier.uri.fl_str_mv https://hdl.handle.net/10216/85680
url https://hdl.handle.net/10216/85680
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv 10.1007/978-3-642-31298-4_22
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