Fusion of image segmentation algorithms using consensus clustering

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

研究成果: Conference contribution

5 被引用数 (Scopus)

抄録

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.

本文言語English
ホスト出版物のタイトル2013 IEEE International Conference on Image Processing, ICIP 2013 - Proceedings
ページ4049-4053
ページ数5
DOI
出版ステータスPublished - 2013
イベント2013 20th IEEE International Conference on Image Processing, ICIP 2013 - Melbourne, VIC, Australia
継続期間: 2013 9 152013 9 18

出版物シリーズ

名前2013 IEEE International Conference on Image Processing, ICIP 2013 - Proceedings

Other

Other2013 20th IEEE International Conference on Image Processing, ICIP 2013
CountryAustralia
CityMelbourne, VIC
Period13/9/1513/9/18

ASJC Scopus subject areas

  • Computer Vision and Pattern Recognition

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