Unsupervised colour image segmentation by low-level perceptual grouping
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Mostrar el registro completo del ítemcomunitat-uji-handle:10234/9
comunitat-uji-handle2:10234/43662
comunitat-uji-handle3:10234/43643
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Título
Unsupervised colour image segmentation by low-level perceptual groupingFecha de publicación
2013-11Editor
SpringerISSN
1433-7541; 1433-755XTipo de documento
info:eu-repo/semantics/articleVersión de la editorial
http://link.springer.com/content/pdf/10.1007%2Fs10044-011-0259-1.pdfVersión
info:eu-repo/semantics/acceptedVersionPalabras clave / Materias
Resumen
This paper proposes a new unsupervised
approach for colour image segmentation. A hierarchy of
image partitions is created on the basis of a function that
merges spatially connected regions according to primary
p ... [+]
This paper proposes a new unsupervised
approach for colour image segmentation. A hierarchy of
image partitions is created on the basis of a function that
merges spatially connected regions according to primary
perceptual criteria. Likewise, a global function that measures the goodness of each defined partition is used to
choose the best low-level perceptual grouping in the hierarchy. Contributions also include a comparative study with
five unsupervised colour image segmentation techniques.
These techniques have been frequently used as a reference
in other comparisons. The results obtained by each method
have been systematically evaluated using four well-known
unsupervised measures for judging the segmentation
quality. Our methodology has globally shown the best
performance, obtaining better results in three out of four of
these segmentation quality measures. Experiments will also
show that our proposal finds low-level perceptual solutions
that are highly correlated with the ones provided by
humans [-]
Publicado en
Pattern Analysis and Applications, november 2013, Volume 16, Issue 4, pp 581-594Derechos de acceso
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