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Infrared Image Segmentation Based on Improved Fuzzy Kernel Clustering

  • 2013-09-19
  • 209.42KB
  • Points it Requires : 2

Aiming at the problems existing in traditional fuzzy kernel clustering in infrared image segmentation, an improved fuzzy kernel clustering infrared image segmentation algorithm is proposed. On the basis of fuzzy kernel clustering, the spatial constraint relationship and neighborhood membership correlation of infrared image pixels are introduced, and the membership constraint strength index modified membership function is defined, which can effectively suppress the noise and outliers in the infrared image segmentation results. Experimental results show that compared with the traditional segmentation results, this spatial constraint fuzzy kernel clustering algorithm considering the neighborhood membership correlation can effectively segment infrared images, accurately and completely segment the target, and achieve satisfactory results.

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