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An Enhanced Spatial Intuitionistic Fuzzy C-means Clustering for Image Segmentation

Published: 09 July 2024 Publication History

Abstract

Intuitionistic based Fuzzy clustering is a popular method in the field of image segmentation. The widely used Intuitionistic Fuzzy C-means (IFCM) based image segmentation is sensitive to noise since it uses only distance criterion in the feature space to segment the images. To overcome this, an enhanced spatial intuitionistic fuzzy c-means clustering algorithm is proposed that uses:- (i) an intuitionistic fuzzification of image to simplify the representation of the image (ii) an improved method to calculate the hesitation degree in the images. (iii) the spatial property of an image in order to make segmentation more robust and effective. The performance of the proposed method is evaluated for synthetic and real images. The result indicates the effectiveness of the proposed methodology over existing methodologies.

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Information & Contributors

Information

Published In

cover image Procedia Computer Science
Procedia Computer Science  Volume 167, Issue C
2020
2675 pages
ISSN:1877-0509
EISSN:1877-0509
Issue’s Table of Contents

Publisher

Elsevier Science Publishers B. V.

Netherlands

Publication History

Published: 09 July 2024

Author Tags

  1. Clustering
  2. Image Segmentation
  3. Fuzzy C-means
  4. Intuitionistic Fuzzy C-means

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