A modified fuzzy dual-local information c-mean clustering algorithm using quadratic surface as prototype for image segmentation

作者：

Highlights：

• Fuzzy local information clustering with quadratic surface prototype is proposed.

• Further fused with local membership to form dual local information constraints.

• The convergence is analyzed by Zangwill theorem and bordered Hessian matrxi.

• Experimental results show that the proposed algorithm has better robustness.

摘要

•Fuzzy local information clustering with quadratic surface prototype is proposed.•Further fused with local membership to form dual local information constraints.•The convergence is analyzed by Zangwill theorem and bordered Hessian matrxi.•Experimental results show that the proposed algorithm has better robustness.

论文关键词：Image segmentation,Fuzzy c-mean clustering,Fuzzy local information factor,Local membership,Quadratic polynomial surface

论文评审过程：Received 16 August 2021, Revised 4 January 2022, Accepted 27 March 2022, Available online 1 April 2022, Version of Record 20 April 2022.

论文官网地址：https://doi.org/10.1016/j.eswa.2022.117019