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Metadados

1. Identificação
Tipo de ReferênciaResumo em Evento (Conference Proceedings)
Sitemtc-m21b.sid.inpe.br
Código do Detentorisadg {BR SPINPE} ibi 8JMKD3MGPCW/3DT298S
Identificador8JMKD3MGP5W34M/3GHDDDB
Repositóriosid.inpe.br/mtc-m21b/2014/06.25.22.54
Última Atualização2014:06.25.22.54.06 (UTC) administrator
Repositório de Metadadossid.inpe.br/mtc-m21b/2014/06.25.22.54.06
Última Atualização dos Metadados2018:06.04.03.04.20 (UTC) administrator
Rótuloself-archiving-INPE-MCTI-GOV-BR
Chave de CitaçãoMusciFeitCostAlme:2014:ImInMe
TítuloAn Image Interpretation Methodology Using Independent Class Specific Segmentations
Ano2014
Data de Acesso11 maio 2024
Tipo SecundárioPRE CI
Número de Arquivos1
Tamanho3017 KiB
2. Contextualização
Autor1 Musci, Marcelo
2 Feitosa, Raul Queiroz
3 Costa, Gilson Alexandre Ostwald Pedro da
4 Almeida, Cláudia Maria de
Identificador de Curriculo1
2
3
4 8JMKD3MGP5W/3C9JGS3
Grupo1
2
3
4 DSR-OBT-INPE-MCTI-GOV-BR
Afiliação1
2
3
4 Instituto Nacional de Pesquisas Espaciais (INPE)
Endereço de e-Mail do Autor1
2
3
4 almeida@dsr.inpe.br
Endereço de e-Mailalmeida@dsr.inpe.br
Nome do EventoConference on Geographic Object-Based Image Analysis, 5 (GEOBIA 2014).
Localização do EventoTessalônica, Grécia
Data21-24 maio, 2014
Páginas116
Título do LivroAbstracts
Histórico (UTC)2014-06-25 22:54:06 :: almeida@dsr.inpe.br -> administrator ::
2018-06-04 03:04:20 :: administrator -> marcelo.pazos@inpe.br :: 2014
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-Chavesegmentation
hierarchical segmentation
parameter tuning
ResumoHierarchical Segmentation (HS) has been a dominant methodology within the GEOBIA community in the last years. In essence, it involves the segmentation of the input image in a number of distinct scales, whereby each segment at a finer scale lies entirely within a segment of a coarser scale. Such methodology implies at least two difficulties. First, inaccuracies of the first segmentation step propagate to the scale levels segmented subsequently. Second, and even more important, it is generally difficult to find a single set of segmentation parameter values that optimises spatial accuracy for all object classes present at the same scale. In general, the user chooses for each scale level the parameter values that yield an acceptable trade-off for all object-classes coexisting at that level, which are generally non optimal for all those object classes. This work proposes and evaluates an alternative to HS, so-called class specific segmentation (CSS). Basically CSS consists of performing a separate and independent, optimised segmentation for each object class. This may be achieved by tuning the segmentation parameters individually for each object class, by running different segmentation algorithms for each class, or a mixture of both, so as to obtain (near) optimum segmentation for each class. The benefit of CSS relative to HS is twofold. First, image objects of each class are expected to be more precisely delineated, improving, therefore, the overall spatial accuracy. Second, since the borders of image objects will be more accurate, morphological features will be more discriminative, contributing as well to a better thematic accuracy. However, CSS brings about a problem not present in HS. Multiple potentially contradictory segmentation results will coexist in some phases of the interpretation procedure. This problem is handled by CSS in the classification stage in the following way. For each given object class a specific detector is designed, which searches the corresponding segmentation outcome for instances of its object class. As a result some image regions will possibly be assigned to more than one class, giving rise to what we call spatial conflicts. Besides delivering a class/non class logical label for each segment, the class specific detectors also yield a membership or a probability value that expresses how well a segment fits the detectors class. Spatial conflicts are then resolved by assigning regions of conflict to the class with the highest membership or likelihood. Three segmentation algorithms in combination with two alternative detector designs have been tested upon three very-high resolution images. The results indicated unanimously that CSS performs significantly better than, or sporadically as good as, the HS approach, both in terms of spatial as well as thematic accuracy.
ÁreaSRE
Arranjourlib.net > BDMCI > Fonds > Produção anterior à 2021 > DIDSR > An Image Interpretation...
Conteúdo da Pasta docacessar
Conteúdo da Pasta sourcenão têm arquivos
Conteúdo da Pasta agreement
agreement.html 25/06/2014 19:54 1.0 KiB 
4. Condições de acesso e uso
URL dos dadoshttp://urlib.net/ibi/8JMKD3MGP5W34M/3GHDDDB
URL dos dados zipadoshttp://urlib.net/zip/8JMKD3MGP5W34M/3GHDDDB
Idiomaen
Arquivo AlvoGeobia_2014_Abstract_Book_Musci et al.pdf
Grupo de Usuáriosalmeida@dsr.inpe.br
marcelo.pazos@inpe.br
Grupo de Leitoresadministrator
marcelo.pazos@inpe.br
Visibilidadeshown
Permissão de Leituraallow from all
Permissão de Atualizaçãonão transferida
5. Fontes relacionadas
Repositório Espelhoiconet.com.br/banon/2006/11.26.21.31
Unidades Imediatamente Superiores8JMKD3MGPCW/3ER446E
Lista de Itens Citandosid.inpe.br/mtc-m21/2012/07.13.14.43.49 2
Acervo Hospedeirosid.inpe.br/mtc-m21b/2013/09.26.14.25.20
6. Notas
Campos Vaziosarchivingpolicy archivist callnumber copyholder copyright creatorhistory descriptionlevel dissemination doi edition editor format isbn issn lineage mark nextedition notes numberofvolumes orcid organization parameterlist parentrepositories previousedition previouslowerunit progress project publisher publisheraddress rightsholder schedulinginformation secondarydate secondarykey secondarymark serieseditor session shorttitle sponsor subject tertiarymark tertiarytype type url volume
7. Controle da descrição
e-Mail (login)marcelo.pazos@inpe.br
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