A Markov-Random-Field Approach for Extracting Straight-Line Segments of Roofs From High-Resolution Aerial Images

Detalhes bibliográficos
Autor(a) principal: Marcato Fernandes, Vanessa Jordao [UNESP]
Data de Publicação: 2016
Outros Autores: Dal Poz, Aluir Porfirio [UNESP]
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Repositório Institucional da UNESP
Texto Completo: http://dx.doi.org/10.1109/JSTARS.2016.2601068
http://hdl.handle.net/11449/162325
Resumo: This paper proposes a method for extracting groups of straight lines that represent roof boundary sides and roof ridgelines from high-resolution aerial images using corresponding airborne laser scanner (ALS) roof polyhedrons as initial approximations. Our motivation for this research is the possibility of future use of resulting image-space straight lines in several applications. For example, straight lines that represent roof boundary sides and precisely extracted from a high-resolution image can be back-projected onto the ALS-derived building polyhedron for refining the accuracy of its boundary. The proposed method is based on two main steps. First, straight lines that are candidates to represent roof ridgelines and roof boundary sides of a building are extracted from the aerial image. The ALS-derived roof boundary sides and roof ridgelines are projected onto the image space, and bolding boxes are constructed around the projected straight lines while considering the projection errors. This allows the extraction of straight lines within the bounding boxes. Second, a group of straight lines that represent roof boundary sides and roof ridgelines of a selected building is obtained through the optimization of a Markov random field-based energy function using the genetic algorithm optimization method. The formulation of this energy function considers several attributes, such as the proximity of the extracted straight lines to the corresponding projected ALS-derived roof polyhedron and the rectangularity (extracted straight lines that intersect at nearly 90 degrees). In order to validate the proposed method, four experiments were accomplished using high-resolution aerial images, along with interior and exterior orientation parameters, and available ALS-derived building roof polyhedrons. The obtained results have shown that the method works properly and this will be qualitatively and quantitatively demonstrated in this research.
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spelling A Markov-Random-Field Approach for Extracting Straight-Line Segments of Roofs From High-Resolution Aerial ImagesAirborne laser scanner (ALS)Markov random field (MRF)straight lineThis paper proposes a method for extracting groups of straight lines that represent roof boundary sides and roof ridgelines from high-resolution aerial images using corresponding airborne laser scanner (ALS) roof polyhedrons as initial approximations. Our motivation for this research is the possibility of future use of resulting image-space straight lines in several applications. For example, straight lines that represent roof boundary sides and precisely extracted from a high-resolution image can be back-projected onto the ALS-derived building polyhedron for refining the accuracy of its boundary. The proposed method is based on two main steps. First, straight lines that are candidates to represent roof ridgelines and roof boundary sides of a building are extracted from the aerial image. The ALS-derived roof boundary sides and roof ridgelines are projected onto the image space, and bolding boxes are constructed around the projected straight lines while considering the projection errors. This allows the extraction of straight lines within the bounding boxes. Second, a group of straight lines that represent roof boundary sides and roof ridgelines of a selected building is obtained through the optimization of a Markov random field-based energy function using the genetic algorithm optimization method. The formulation of this energy function considers several attributes, such as the proximity of the extracted straight lines to the corresponding projected ALS-derived roof polyhedron and the rectangularity (extracted straight lines that intersect at nearly 90 degrees). In order to validate the proposed method, four experiments were accomplished using high-resolution aerial images, along with interior and exterior orientation parameters, and available ALS-derived building roof polyhedrons. The obtained results have shown that the method works properly and this will be qualitatively and quantitatively demonstrated in this research.Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)Sao Paulo State Univ, BR-19060900 Presidente Prudente, BrazilSao Paulo State Univ, Dept Cartog, BR-19060900 Presidente Prudente, BrazilSao Paulo State Univ, BR-19060900 Presidente Prudente, BrazilSao Paulo State Univ, Dept Cartog, BR-19060900 Presidente Prudente, BrazilFAPESP: 2013/13138-0FAPESP: 2012/22332-2CNPq: 304879/2009-6Ieee-inst Electrical Electronics Engineers IncUniversidade Estadual Paulista (Unesp)Marcato Fernandes, Vanessa Jordao [UNESP]Dal Poz, Aluir Porfirio [UNESP]2018-11-26T17:15:38Z2018-11-26T17:15:38Z2016-12-01info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/article5493-5505application/pdfhttp://dx.doi.org/10.1109/JSTARS.2016.2601068Ieee Journal Of Selected Topics In Applied Earth Observations And Remote Sensing. Piscataway: Ieee-inst Electrical Electronics Engineers Inc, v. 9, n. 12, p. 5493-5505, 2016.1939-1404http://hdl.handle.net/11449/16232510.1109/JSTARS.2016.2601068WOS:000391468100020WOS000391468100020.pdfWeb of Sciencereponame:Repositório Institucional da UNESPinstname:Universidade Estadual Paulista (UNESP)instacron:UNESPengIeee Journal Of Selected Topics In Applied Earth Observations And Remote Sensing1,547info:eu-repo/semantics/openAccess2024-06-18T18:18:24Zoai:repositorio.unesp.br:11449/162325Repositório InstitucionalPUBhttp://repositorio.unesp.br/oai/requestopendoar:29462024-06-18T18:18:24Repositório Institucional da UNESP - Universidade Estadual Paulista (UNESP)false
dc.title.none.fl_str_mv A Markov-Random-Field Approach for Extracting Straight-Line Segments of Roofs From High-Resolution Aerial Images
title A Markov-Random-Field Approach for Extracting Straight-Line Segments of Roofs From High-Resolution Aerial Images
spellingShingle A Markov-Random-Field Approach for Extracting Straight-Line Segments of Roofs From High-Resolution Aerial Images
Marcato Fernandes, Vanessa Jordao [UNESP]
Airborne laser scanner (ALS)
Markov random field (MRF)
straight line
title_short A Markov-Random-Field Approach for Extracting Straight-Line Segments of Roofs From High-Resolution Aerial Images
title_full A Markov-Random-Field Approach for Extracting Straight-Line Segments of Roofs From High-Resolution Aerial Images
title_fullStr A Markov-Random-Field Approach for Extracting Straight-Line Segments of Roofs From High-Resolution Aerial Images
title_full_unstemmed A Markov-Random-Field Approach for Extracting Straight-Line Segments of Roofs From High-Resolution Aerial Images
title_sort A Markov-Random-Field Approach for Extracting Straight-Line Segments of Roofs From High-Resolution Aerial Images
author Marcato Fernandes, Vanessa Jordao [UNESP]
author_facet Marcato Fernandes, Vanessa Jordao [UNESP]
Dal Poz, Aluir Porfirio [UNESP]
author_role author
author2 Dal Poz, Aluir Porfirio [UNESP]
author2_role author
dc.contributor.none.fl_str_mv Universidade Estadual Paulista (Unesp)
dc.contributor.author.fl_str_mv Marcato Fernandes, Vanessa Jordao [UNESP]
Dal Poz, Aluir Porfirio [UNESP]
dc.subject.por.fl_str_mv Airborne laser scanner (ALS)
Markov random field (MRF)
straight line
topic Airborne laser scanner (ALS)
Markov random field (MRF)
straight line
description This paper proposes a method for extracting groups of straight lines that represent roof boundary sides and roof ridgelines from high-resolution aerial images using corresponding airborne laser scanner (ALS) roof polyhedrons as initial approximations. Our motivation for this research is the possibility of future use of resulting image-space straight lines in several applications. For example, straight lines that represent roof boundary sides and precisely extracted from a high-resolution image can be back-projected onto the ALS-derived building polyhedron for refining the accuracy of its boundary. The proposed method is based on two main steps. First, straight lines that are candidates to represent roof ridgelines and roof boundary sides of a building are extracted from the aerial image. The ALS-derived roof boundary sides and roof ridgelines are projected onto the image space, and bolding boxes are constructed around the projected straight lines while considering the projection errors. This allows the extraction of straight lines within the bounding boxes. Second, a group of straight lines that represent roof boundary sides and roof ridgelines of a selected building is obtained through the optimization of a Markov random field-based energy function using the genetic algorithm optimization method. The formulation of this energy function considers several attributes, such as the proximity of the extracted straight lines to the corresponding projected ALS-derived roof polyhedron and the rectangularity (extracted straight lines that intersect at nearly 90 degrees). In order to validate the proposed method, four experiments were accomplished using high-resolution aerial images, along with interior and exterior orientation parameters, and available ALS-derived building roof polyhedrons. The obtained results have shown that the method works properly and this will be qualitatively and quantitatively demonstrated in this research.
publishDate 2016
dc.date.none.fl_str_mv 2016-12-01
2018-11-26T17:15:38Z
2018-11-26T17:15:38Z
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://dx.doi.org/10.1109/JSTARS.2016.2601068
Ieee Journal Of Selected Topics In Applied Earth Observations And Remote Sensing. Piscataway: Ieee-inst Electrical Electronics Engineers Inc, v. 9, n. 12, p. 5493-5505, 2016.
1939-1404
http://hdl.handle.net/11449/162325
10.1109/JSTARS.2016.2601068
WOS:000391468100020
WOS000391468100020.pdf
url http://dx.doi.org/10.1109/JSTARS.2016.2601068
http://hdl.handle.net/11449/162325
identifier_str_mv Ieee Journal Of Selected Topics In Applied Earth Observations And Remote Sensing. Piscataway: Ieee-inst Electrical Electronics Engineers Inc, v. 9, n. 12, p. 5493-5505, 2016.
1939-1404
10.1109/JSTARS.2016.2601068
WOS:000391468100020
WOS000391468100020.pdf
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv Ieee Journal Of Selected Topics In Applied Earth Observations And Remote Sensing
1,547
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv 5493-5505
application/pdf
dc.publisher.none.fl_str_mv Ieee-inst Electrical Electronics Engineers Inc
publisher.none.fl_str_mv Ieee-inst Electrical Electronics Engineers Inc
dc.source.none.fl_str_mv Web of Science
reponame:Repositório Institucional da UNESP
instname:Universidade Estadual Paulista (UNESP)
instacron:UNESP
instname_str Universidade Estadual Paulista (UNESP)
instacron_str UNESP
institution UNESP
reponame_str Repositório Institucional da UNESP
collection Repositório Institucional da UNESP
repository.name.fl_str_mv Repositório Institucional da UNESP - Universidade Estadual Paulista (UNESP)
repository.mail.fl_str_mv
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