"Ratio regions": a technique for image segmentation

We develop a image segmentation algorithm in which the segmented region has both an exterior boundary cost and an interior benefit associated with it. Our segmentation method proceeds by minimizing the ratio between the exterior boundary cost and the enclosed interior benefit using a computationally...

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Published inProceedings of 13th International Conference on Pattern Recognition Vol. 2; pp. 557 - 564 vol.2
Main Authors Cox, I.J., Rao, S.B., Yu Zhong
Format Conference Proceeding
LanguageEnglish
Published IEEE 1996
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ISBN9780818672828
081867282X
ISSN1051-4651
DOI10.1109/ICPR.1996.546886

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Abstract We develop a image segmentation algorithm in which the segmented region has both an exterior boundary cost and an interior benefit associated with it. Our segmentation method proceeds by minimizing the ratio between the exterior boundary cost and the enclosed interior benefit using a computationally efficient graph partitioning algorithm. Our interest is motivated by very efficient algorithms for finding the globally optimum solution, and a desire to investigate how weak smoothness constraints may be globally imposed without disallowing very high local curvature. We analyze the performance of the approach, indicating both strengths and weaknesses, and discuss its connections with prior image partitioning algorithms. The relationship with snakes is discussed in detail and it is shown how to efficiently compute an approximation to common snakes under the additional constraint that it enclose a given point. When user interaction is available, there is a clear advantage to minimizing user interaction for purposes of improved speed and ease of use and for robustness. "Ratio regions" can accommodate several levels of user interaction and it is empirically shown that very coarse initializations can be tolerated. User interaction not only guides the algorithm to perceptually salient regions but can also be exploited to significantly reduce the computational cost.
AbstractList We develop a image segmentation algorithm in which the segmented region has both an exterior boundary cost and an interior benefit associated with it. Our segmentation method proceeds by minimizing the ratio between the exterior boundary cost and the enclosed interior benefit using a computationally efficient graph partitioning algorithm. Our interest is motivated by very efficient algorithms for finding the globally optimum solution, and a desire to investigate how weak smoothness constraints may be globally imposed without disallowing very high local curvature. We analyze the performance of the approach, indicating both strengths and weaknesses, and discuss its connections with prior image partitioning algorithms. The relationship with snakes is discussed in detail and it is shown how to efficiently compute an approximation to common snakes under the additional constraint that it enclose a given point. When user interaction is available, there is a clear advantage to minimizing user interaction for purposes of improved speed and ease of use and for robustness. "Ratio regions" can accommodate several levels of user interaction and it is empirically shown that very coarse initializations can be tolerated. User interaction not only guides the algorithm to perceptually salient regions but can also be exploited to significantly reduce the computational cost.
Author Rao, S.B.
Cox, I.J.
Yu Zhong
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Snippet We develop a image segmentation algorithm in which the segmented region has both an exterior boundary cost and an interior benefit associated with it. Our...
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StartPage 557
SubjectTerms Algorithm design and analysis
Computational efficiency
Computer applications
Cost function
Image analysis
Image segmentation
National electric code
Partitioning algorithms
Performance analysis
Robustness
Title "Ratio regions": a technique for image segmentation
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