FUSION OF IMAGE SEGMENTATION ALGORITHMS USING CONSENSUS CLUSTERING

Ozay M., YARMAN VURAL F. T., Kulkarni S. R., Poor H. V.

20th IEEE International Conference on Image Processing (ICIP), Melbourne, Avustralya, 15 - 18 Eylül 2013, ss.4049-4053 identifier

  • Yayın Türü: Bildiri / Tam Metin Bildiri
  • Basıldığı Şehir: Melbourne
  • Basıldığı Ülke: Avustralya
  • Sayfa Sayıları: ss.4049-4053
  • Orta Doğu Teknik Üniversitesi Adresli: Evet

Özet

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.