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Cell segmentation based on spatial information improved intuitionistic fcm combined with FOPSO

  • Beihang University

科研成果: 书/报告/会议事项章节会议稿件同行评审

摘要

Fuzzy c-means clustering (FCM) algorithm has been proved to be effective for image segmentation. However, it is sensitive to the noises and initialization. FCM could not effectively segment cell images with inhomogeneity and complicate adhesives. Aimed to overcome these disadvantages, this paper proposes a cell image segmentation algorithm using spatial information improved intuitionistic fuzzy c-means clustering (SI-IFCM) combined with fractional-order velocity based particle swarm optimization (FOPSO). SI-IFCM and FOPSO will iterate alternately with different object functions to obtain the clustering result. Experimental results demonstrate the advantages of our algorithm for cell segmentation comparing with state-of-arts algorithms.

源语言英语
主期刊名2017 IEEE International Conference on Image Processing, ICIP 2017 - Proceedings
出版商IEEE Computer Society
4457-4461
页数5
ISBN(电子版)9781509021758
DOI
出版状态已出版 - 2 7月 2017
活动24th IEEE International Conference on Image Processing, ICIP 2017 - Beijing, 中国
期限: 17 9月 201720 9月 2017

出版系列

姓名Proceedings - International Conference on Image Processing, ICIP
2017-September
ISSN(印刷版)1522-4880

会议

会议24th IEEE International Conference on Image Processing, ICIP 2017
国家/地区中国
Beijing
时期17/09/1720/09/17

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