A Unifying View of Contour Length Bias Correction

Authors:
Christina Pavlopoulou;Stella X. Yu
Affiliations:
Computer Science Department, Boston College, Chestnut Hill, USA 02469;Computer Science Department, Boston College, Chestnut Hill, USA 02469
Venue:
ISVC '09 Proceedings of the 5th International Symposium on Advances in Visual Computing: Part I
Year:
2009

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Abstract

Original active contour formulations may become ill-posed especially for boundaries characterized by prominent features. Attempts to yield well-posed formulations lead to bias towards short contours. We provide a framework to unify existing bias correcting energy methods and propose a novel local bias correcting scheme similar to non-maximum suppression. Our method can be seen as an approximation to a well-known algorithm that transforms a graph with positive and negative weights to a graph with only positive weights while preserving the shortest paths among the nodes.