Fechar
Metadados

1. Identificação
Tipo de ReferênciaArtigo em Evento (Conference Proceedings)
Sitesibgrapi.sid.inpe.br
Código do Detentoribi 8JMKD3MGPEW34M/46T9EHH
Identificador8JMKD3MGPBW34M/3JNHU48
Repositóriosid.inpe.br/sibgrapi/2015/06.24.21.28
Última Atualização2015:06.24.21.28.53 (UTC) administrator
Repositório de Metadadossid.inpe.br/sibgrapi/2015/06.24.21.28.53
Última Atualização dos Metadados2022:06.14.00.08.15 (UTC) administrator
DOI10.1109/SIBGRAPI.2015.29
Chave de CitaçãoLinaresBoteRodrBati:2015:AdErMe
TítuloAn Adjustable Error Measure for Image Segmentation Evaluation
FormatoOn-line
Ano2015
Data de Acesso09 maio 2025
Número de Arquivos1
Tamanho497 KiB
2. Contextualização
Autor1 Linares, Oscar Cuadros
2 Botelho, Glenda
3 Rodrigues, Francisco
4 Batista Neto, João
Afiliação1 University of São Paulo
2 Universidade Federal do Tocantins
3 University of São Paulo
4 University of São Paulo
EditorPapa, João Paulo
Sander, Pedro Vieira
Marroquim, Ricardo Guerra
Farrell, Ryan
Endereço de e-Mailocuadros@icmc.uso.br
Nome do EventoConference on Graphics, Patterns and Images, 28 (SIBGRAPI)
Localização do EventoSalvador, BA, Brazil
Data26-29 Aug. 2015
Editora (Publisher)IEEE Computer Society
Cidade da EditoraLos Alamitos
Título do LivroProceedings
Tipo TerciárioFull Paper
Histórico (UTC)2015-06-24 21:28:53 :: ocuadros@icmc.uso.br -> administrator ::
2022-06-14 00:08:15 :: administrator -> :: 2015
3. Conteúdo e estrutura
É a matriz ou uma cópia?é a matriz
Estágio do Conteúdoconcluido
Transferível1
Tipo de Versãofinaldraft
Palavras-Chaveerror measure
metric
evaluation
image segmentation
ResumoDue to the subjective nature of the segmentation process, quantitative evaluation of image segmentation methods is still a difficult task. Humans perceive image objects in different ways. Consequently, human segmentations may come in different levels of refinement, ie, under- and over-segmentations. Popular segmentation error measures in the literature (Arbelaez and OCE) are supervised methods (also called empirical discrepancy methods), in which error is computed by comparing objects in segmentations with a reference (ground-truth) image produced by humans. Since reference images can be many, the key issue for a segmentation error measure is to be consistent in the presence of both under- and over-segmentation. In general, the term consistency refers to the ability of the error measure to be low, when comparing similar segmentations, or high, when faced with different segmentations, while capturing under- or over-segmentations. In this paper we propose a new object-based empirical discrepancy error measure, called Adjustable Object- based Measure (AOM). We introduce a penalty parameter which gives the method the ability to be more (or less) responsive in the presence of over-segmentation. Hence, we extend the notion of consistency so as to include the applications need in the process. Some applications require segmentation to be extremely accurate, hence under- or over-segmentation should be well penalised. Others, do not. By changing the penalty parameter, AOM can deliver more consistent results not only in reference to the under- or over-segmentation issue alone, but also according to the nature of the application. We compare our method with Arbelaez (used as standard measure in the benchmark of Berkeley Segmentation Image Dataset) and OCE. Our results show that AOM not only is more consistent in the presence of over-segmentation, but is also faster to compute. Unlike Arbelaez and OCE, AOM also satisfies the metric axiom of symmetry.
Arranjo 1urlib.net > SIBGRAPI 2015 > An Adjustable Error...
Arranjo 2urlib.net > Full Index > An Adjustable Error...
Conteúdo da Pasta docacessar
Conteúdo da Pasta sourcenão têm arquivos
Conteúdo da Pasta agreement
agreement.html 24/06/2015 18:28 0.7 KiB 
4. Condições de acesso e uso
URL dos dadoshttp://urlib.net/ibi/8JMKD3MGPBW34M/3JNHU48
URL dos dados zipadoshttp://urlib.net/zip/8JMKD3MGPBW34M/3JNHU48
Idiomaen
Arquivo AlvoPID3768029.pdf
Grupo de Usuáriosocuadros@icmc.uso.br
Visibilidadeshown
Permissão de Atualizaçãonão transferida
5. Fontes relacionadas
Repositório Espelhosid.inpe.br/banon/2001/03.30.15.38.24
Unidades Imediatamente Superiores8JMKD3MGPBW34M/3K24PF8
8JMKD3MGPEW34M/4742MCS
Lista de Itens Citandosid.inpe.br/sibgrapi/2015/08.03.22.49 63
sid.inpe.br/sibgrapi/2022/06.10.21.49 7
sid.inpe.br/banon/2001/03.30.15.38.24 1
Acervo Hospedeirosid.inpe.br/banon/2001/03.30.15.38
6. Notas
Campos Vaziosarchivingpolicy archivist area callnumber contenttype copyholder copyright creatorhistory descriptionlevel dissemination edition electronicmailaddress group isbn issn label lineage mark nextedition notes numberofvolumes orcid organization pages parameterlist parentrepositories previousedition previouslowerunit progress project readergroup readpermission resumeid rightsholder schedulinginformation secondarydate secondarykey secondarymark secondarytype serieseditor session shorttitle sponsor subject tertiarymark type url volume


Fechar