Interval type 2 intuitionistic FCM cluster with spatial information algorithm applied for histopathology images
Authors :
P. Amsini 1 * and R. Uma Rani 2
Author Address :
1,2 Department of Computer Science, Sri Sarada College for Women (Autonomous), Salem-636016, Tamil Nadu, India.
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.
DOI :
Article Info :
Received : November 24, 2020; Accepted : December 30, 2020.
