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PRL
2006

Improving image segmentation quality through effective region merging using a hierarchical social metaheuristic

13 years 7 months ago
Improving image segmentation quality through effective region merging using a hierarchical social metaheuristic
This paper proposes a new evolutionary region merging method in order to efficiently improve segmentation quality results. Our approach starts from an oversegmented image, which is obtained by applying a standard morphological watershed transformation on the original image. Next, each resulting region is represented by its centroid. The oversegmented image is described by a simplified undirected weighted graph, where each node represents one region and weighted edges measure the dissimilarity between pairs of regions (adjacent and non-adjacent) according to their intensities, spatial locations and original sizes. Finally, the resulting graph is iteratively partitioned in a hierarchical fashion into two subgraphs, corresponding to the two most significant components of the actual image, until a termination condition is met. This graph-partitioning task is solved by a variant of the min-cut problem (normalized cut) using a Hierarchical Social (HS) metaheuristic. We have efficiently appli...
Abraham Duarte, Miguel Ángel Sánchez
Added 14 Dec 2010
Updated 14 Dec 2010
Type Journal
Year 2006
Where PRL
Authors Abraham Duarte, Miguel Ángel Sánchez Vidales, Felipe Fernández, Antonio S. Montemayor
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