Oriented image foresting transform segmentation with connectivity constraints

Oriented image foresting transform segmentation with connectivity constraints

Author Mansilla, Lucy A. C. Google Scholar
Miranda, Paulo A. V. Google Scholar
Cappabianco, Fabio A. M. Autor UNIFESP Google Scholar
Abstract A new algorithm, named Connected Oriented Image Foresting Transform (COIFT), is proposed, which provides global optimum solutions according to a graph-cut measure, subject to high-level boundary constraints. COEFT incorporates the connectivity constraint in the Oriented Image Foresting Transform (OIFT), ensuring the generation of connected objects, and can also handle simultaneously the boundary polarity. While the connectivity constraint usually leads to NP hard problems in other frameworks, such as the min-cut/max-flow algorithm, COIFT conserves the low complexity of the OIFT algorithm. Experiments show that COEFT can improve the segmentation of thin and elongated objects, for the same amount of user interaction.
Keywords Image Segmentation
Connectivity Constraint
Boundary Polarity
Image Foresting TransformRelative Fuzzy Connectedness
Language English
Date 2016
Published in 2016 Ieee International Conference On Image Processing (ICIP). New york, p. 2554-2558, 2016.
ISSN 1522-4880 (Sherpa/Romeo, impact factor)
Publisher Revista Biota Neotropica
Extent 2554-2558
Origin http://dx.doi.org/10.1109/ICIP.2016.7532820
Access rights Closed access
Type Conference paper
Web of Science ID WOS:000390782002120
URI http://repositorio.unifesp.br/handle/11600/49307

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