@inproceedings{97fdf41ceb1e458e90ffe03c9e0bc6d2,
title = "Fusion of image segmentation algorithms using consensus clustering",
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.",
keywords = "Segmentation, clustering, consensus, fusion, stochastic optimization",
author = "Mete Ozay and Vural, {Fatos T Yarman} and Kulkarni, {Sanjeev R.} and Poor, {H. Vincent}",
year = "2013",
doi = "10.1109/ICIP.2013.6738834",
language = "English (US)",
isbn = "9781479923410",
series = "2013 IEEE International Conference on Image Processing, ICIP 2013 - Proceedings",
publisher = "IEEE Computer Society",
pages = "4049--4053",
booktitle = "2013 IEEE International Conference on Image Processing, ICIP 2013 - Proceedings",
address = "United States",
note = "2013 20th IEEE International Conference on Image Processing, ICIP 2013 ; Conference date: 15-09-2013 Through 18-09-2013",
}