Interval type 2 intuitionistic FCM cluster with spatial information algorithm applied for histopathology images
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Abstract
Image segmentation plays an important role for diagnosis, treatment of diseases and research studies. The
objective of the segmentation is to investigate to separate the objects from the background image. The medical
image contains uncertainty and vagueness where it is handled by advanced fuzzy set theories. Clustering is one
of the ways to segment the image into different regions based upon similarity of pixels. The proposed algorithm
of color based interval intuitionistic type 2 fuzzy c means with spatial information is firstly used for medical cancer
histopathology images. this algorithm is extended for interval valued type 2 intuitionistic with spatial and lower
computational complexity. It works well compared to the existing algorithm by the quality measurements. The
image segmentation quality metrics are such as sensitivity, specificity and accuracy.
Keywords:
Interval intuitionistic type 2 FCM, spatial, image clustering.Mathematics Subject Classification:
Mathematics- Pages: 52-56
- Date Published: 01-01-2021
- Vol. 9 No. 01 (2021): Malaya Journal of Matematik (MJM)
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