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Reference TypeConference Paper (Conference Proceedings)
Last Update2015: (UTC)
Metadata Last Update2016: (UTC) administrator
Citation KeyMansillaMira:2015:ImSeIm
TitleImage Segmentation by Image Foresting Transform with Non-smooth Connectivity Functions
Access Date2022, Jan. 24
Secondary TypeMaster's Work
Number of Files1
Size600 KiB
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Author1 Mansilla, Lucy Alsina Choque
2 Miranda, Paulo André Vechiatto de
EditorSegundo, Maurício Pamplona
Faria, Fabio Augusto
Conference NameConference on Graphics, Patterns and Images, 28 (SIBGRAPI)
Conference LocationSalvador
DateAug. 26-29, 2015
PublisherSociedade Brasileira de Computação
Publisher CityPorto Alegre
Book TitleProceedings
Tertiary TypeMaster's or Doctoral Work
History (UTC)2015-08-01 00:03:01 :: -> administrator ::
2016-06-03 21:18:38 :: administrator -> :: 2015
Content and structure area
Is the master or a copy?is the master
Content Stagecompleted
image foresting transform
oriented image foresting transform
non-smooth connectivity function
geodesic star convexity
AbstractImage segmentation, such as to extract an object from a background, is very useful for medical and biological image analysis. In this work, we propose new methods for interactive segmentation of multidimensional images, based on the Image Foresting Transform (IFT), by exploiting for the first time non-smooth connectivity functions (NSCF) with a strong theoretical background. The new algorithms provide global optimum solutions according to an energy function of graph cut, subject to high-level boundary constraints (polarity and shape), or consist in a sequence of paths' optimization in residual graphs. Our experimental results indicate substantial improvements in accuracy in relation to other state-of-the-art methods, by allowing the customization of the segmentation to a given target object. > SDLA > SIBGRAPI 2015 > Image Segmentation by...
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Next Higher Units8JMKD3MGPBW34M/3K24PF8
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