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1. Identificação
Tipo de ReferênciaArtigo em Evento (Conference Proceedings)
Siteplutao.sid.inpe.br
Código do Detentorisadg {BR SPINPE} ibi 8JMKD3MGPCW/3DT298S
Identificador8JMKD3MGP3W/3MTMTJ3
Repositóriosid.inpe.br/plutao/2016/12.05.18.46.22
Última Atualização2016:12.13.15.19.30 (UTC) lattes
Repositório de Metadadossid.inpe.br/plutao/2016/12.05.18.46.23
Última Atualização dos Metadados2018:06.04.23.26.11 (UTC) administrator
DOI10.13140/RG.2.2.27778.27844
ISBN9789036542012
Rótulolattes: 5186139934330175 1 SoaresKörtFons:2016:FiExUs
Chave de CitaçãoSoaresKörtFons:2016:FiExUs
TítuloFirst experiments using the image foresting transform (IFT) algorithm for segmentation of remote sensing imagery
FormatoDVD
Ano2016
Data de Acesso27 nov. 2022
Tipo SecundárioPRE CI
Número de Arquivos1
Tamanho369 KiB
2. Contextualização
Autor1 Soares, Anderson Reis
2 Körting, Thales Sehn
3 Fonseca, Leila Maria Garcia
Identificador de Curriculo1
2
3 8JMKD3MGP5W/3C9JHLD
Grupo1 SER-SRE-SPG-INPE-MCTI-GOV-BR
2 DPI-OBT-INPE-MCTI-GOV-BR
3 OBT-OBT-INPE-MCTI-GOV-BR
Afiliação1 Instituto Nacional de Pesquisas Espaciais (INPE)
2 Instituto Nacional de Pesquisas Espaciais (INPE)
3 Instituto Nacional de Pesquisas Espaciais (INPE)
Endereço de e-Mail do Autor1 anderson.soares@inpe.br
2 thales.korting@inpe.br
3 leila.fonseca@inpe.br
Nome do EventoGEOBIA 2016 : Solutions and Synergies
Localização do EventoEnschede
Data14-16 sept.
Editora (Publisher)University of Twente Faculty of Geo-Information and Earth Observation (ITC)
Título do LivroProceedings
Tipo TerciárioPaper
Histórico (UTC)2016-12-05 19:37:41 :: lattes -> administrator :: 2016
2016-12-09 07:36:10 :: administrator -> lattes :: 2016
2016-12-13 15:19:30 :: lattes -> administrator :: 2016
2018-06-04 23:26:11 :: administrator -> simone :: 2016
3. Conteúdo e estrutura
É a matriz ou uma cópia?é a matriz
Estágio do Conteúdoconcluido
Transferível1
Tipo do ConteúdoExternal Contribution
Tipo de Versãopublisher
Palavras-ChaveImage Segmentation
Image Foresting Transform
Multiresolution Segmentation
Segmentation Comparison
ResumoImage segmentation is a traditional method in Remote Sensing and a fundamental problem in image processing applications. It has been widely used, especially with the emergence of the Geographic Object-Based Image Analysis (GEOBIA). The results of segmentation must create uniform areas, which must allow a simpler interpretation by the users and simpler representation for classification algorithms. Several algorithms were proposed through the years, using different approaches. One that is widely used in Remote Sensing applications is the Multiresolution algorithm, that is based on the region growing method. Other, which has great potential and is applied in other research areas, is available on the Image Foresting Transform (IFT) framework, which has several image operators developed primarily for medical images. The Watershed from Grayscale Marker operator uses an edge image to perform the segmentation, however, we propose an extension of the edge detection algorithm, by summing normalized gradients of each band. This work aims to evaluate and compare these two segmentation algorithms, by comparing their results through supervised segmentation from reference regions, that were defined manually by an expert user. Quality measures were evaluated by four metrics, that represent the positional adjustment based the center of gravity, intensities, size, and the amount of overlap between the segment created by the algorithms and the reference segment. We selected 21 objects of a WorldView-2 multispectral image that were used to compute the metrics. Both methods reached similar results, by comparing the aforementioned 4 metrics applied to the 21 reference regions, IFT achieved better results for majority of regions. The IFT generated segments with similar shape when compared with the references, and the multiresolution generated results with similar sizes and positional adjustments. It may be explained by the fact that IFT uses an edge image to perform the segmentation. Both algorithms obtained similar agreement for intensity.
ÁreaSRE
Arranjo 1urlib.net > BDMCI > Fonds > Produção anterior à 2021 > DIDPI > First experiments using...
Arranjo 2urlib.net > BDMCI > Fonds > Produção anterior à 2021 > CGOBT > First experiments using...
Arranjo 3urlib.net > BDMCI > Fonds > Produção pgr ATUAIS > SER > First experiments using...
Conteúdo da Pasta docacessar
Conteúdo da Pasta sourcenão têm arquivos
Conteúdo da Pasta agreementnão têm arquivos
4. Condições de acesso e uso
URL dos dadoshttp://urlib.net/ibi/8JMKD3MGP3W/3MTMTJ3
URL dos dados zipadoshttp://urlib.net/zip/8JMKD3MGP3W/3MTMTJ3
Idiomaen
Arquivo Alvosoares_first.pdf
Grupo de Leitoresadministrator
lattes
Visibilidadeshown
Permissão de Leituraallow from all
Permissão de Atualizaçãonão transferida
5. Fontes relacionadas
Repositório Espelhourlib.net/www/2011/03.29.20.55
Unidades Imediatamente Superiores8JMKD3MGPCW/3EQCCU5
8JMKD3MGPCW/3EU2H28
8JMKD3MGPCW/3F3NU5S
URL (dados não confiáveis)http://proceedings.utwente.nl/441/
Acervo Hospedeirodpi.inpe.br/plutao@80/2008/08.19.15.01
6. Notas
Campos Vaziosarchivingpolicy archivist callnumber copyholder copyright creatorhistory descriptionlevel dissemination e-mailaddress edition editor issn lineage mark nextedition notes numberofvolumes orcid organization pages parameterlist parentrepositories previousedition previouslowerunit progress project publisheraddress rightsholder secondarydate secondarykey secondarymark serieseditor session shorttitle sponsor subject tertiarymark type usergroup volume
7. Controle da descrição
e-Mail (login)simone
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