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Hybrid KFCM-PSO Clustering Technique for Image Segmentation

  • Jyoti AroraEmail author
  • Meena Tushir
Conference paper
  • 8 Downloads
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 1164)

Abstract

In this paper, an image segmentation algorithm is proposed which is Kernel-based Fuzzy c-means using Particle Swarm Optimization (KFCM-PSO). This algorithm uses kernel function as it is a generalized distance metric that maps data points into high-dimensional plane where the data points are more clearly separable. Kernel-based Fuzzy c-means are integrated with Particle Swarm Optimization because the traditional Fuzzy c-means algorithm falls into local optima problem whereas PSO is a global optimization algorithm. Comparison of the proposed algorithm with existing FCM, KFCM, and FCM-PSO algorithms is done and the results show that the proposed algorithm gives better results than others.

Keywords

Fuzzy C-Means Particle Swarm Optimization Kernel metrics Image segmentation 

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Copyright information

© The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2021

Authors and Affiliations

  1. 1.Department of Information TechnologyMaharaja Surajmal Institute of Technology, GGSIPUNew DelhiIndia
  2. 2.Department of Electrical and Electronics EngineeringMaharaja Surajmal Institute of Technology, GGSIPUNew DelhiIndia

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