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Published Articles >> Table of Contents >> Abstract
XIX Brazilian Symposium on Computer Graphics and Image Processing (SIBGRAPI'06)
pp. 53-60
Duality between the Watershed by Image Foresting Transform and the Fuzzy Connectedness Segmentation Approaches
Romaric Audigier, State University of Campinas - UNICAMP, Brazil
Roberto Lotufo, State University of Campinas - UNICAMP, Brazil
Full Article Text:
 
DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/SIBGRAPI.2006.14
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| Abstract |
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This paper makes a rereading of two successful image
segmentation approaches, the fuzzy connectedness (FC)
and the watershed (WS) approaches, by analyzing both by
means of the Image Foresting Transform (IFT). This graphbased
transform provides a sound framework for analyzing
and implementing these methods. This paradigm allows to
show the duality existing between the WS by IFT and the
FC segmentation approaches. Both can be modeled by an
optimal forest computation in a dual form (maximization of
the similarities or minimization of the dissimilarities), the
main difference being the input parameters: the weights associated
to each arc of the graph representing the image.
In the WS approach, such weights are based on the (possibly
filtered) image gradient values whereas they are based
on much more complex affinity values in the FC theory. An
efficient algorithm for both FC and IFT-WS computation is
proposed. Segmentation robustness issue is also discussed.
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 Additional Information
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Citation:
Romaric Audigier, Roberto Lotufo,
"Duality between the Watershed by Image Foresting Transform and the Fuzzy Connectedness Segmentation Approaches,"
sibgrapi,
pp. 53-60,
XIX Brazilian Symposium on Computer Graphics and Image Processing (SIBGRAPI'06),
2006
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