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FUSION OF IMAGE SEGMENTATION ALGORITHMS USING CONSENSUS CLUSTERING
Date
2013-09-18
Author
Ozay, Mete
Yarman Vural, Fatoş Tunay
Kulkarni, Sanjeev R.
Poor, H. Vincent
Metadata
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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.
Subject Keywords
Segmentation
,
Clustering
,
Fusion
,
Consensus
,
Stochastic optimization
URI
https://hdl.handle.net/11511/53721
Collections
Department of Computer Engineering, Conference / Seminar