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FUSION OF IMAGE SEGMENTATION ALGORITHMS USING CONSENSUS CLUSTERING

2013-09-18
Ozay, Mete
Yarman Vural, Fatoş Tunay
Kulkarni, Sanjeev R.
Poor, H. Vincent
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This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.
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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.
Segmentation, Clustering, Fusion, Consensus, Stochastic optimization
https://hdl.handle.net/11511/53721
Department of Computer Engineering, Conference / Seminar
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