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arXiv · 1502.05435

Fusion of Image Segmentation Algorithms using Consensus Clustering

Mete Ozay·Fatos T. Yarman Vural·Sanjeev R. Kulkarni·H. Vincent Poor
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Abstract

A new segmentation fusion method is proposed that ensembles the output of several segmentation algorithms applied on a remotely sensed image. The candidate segmentation sets are processed to achieve a consensus segmentation using a stochastic optimization algorithm based on the Filtered Stochastic BOEM (Best One Element Move) method. For this purpose, Filtered Stochastic BOEM is reformulated as a segmentation fusion problem by designing a new distance learning approach. The proposed algorithm also embeds the computation of the optimum number of clusters into the segmentation fusion problem.

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Mete Ozay, Fatos T. Yarman Vural, Sanjeev R. Kulkarni, H. Vincent Poor. 2015-02-18. Fusion of Image Segmentation Algorithms using Consensus Clustering. https://doi.org/10.1109/icip.2013.6738834

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