Neighbourhood weighted fuzzy c‐means clustering algorithm for image segmentation-Reference-Cited by-同舟云学术

Neighbourhood weighted fuzzy c‐means clustering algorithm for image segmentation

Published:2014-03 Issue:3 Volume:8 Page:150-161
ISSN:1751-9667
Container-title:IET Image Processing
language:en
Short-container-title:IET Image Processing

Author:

Zaixin Zhao¹²,Lizhi Cheng²,Guangquan Cheng³

Affiliation:

1. Technique DepartmentTaiyuan Satellite Launch CenterTaiyuan030027People's Republic of China

2. College of Science, National University of Defense TechnologyChangsha410073People's Republic of China

3. Science and Technology on Information Systems Engineering LaboratoryCollege of Information System and Management, National University of Defense TechnologyChangsha410073People's Republic of China

Funder

National Natural Science Foundation of China

Publisher

Institution of Engineering and Technology (IET)

Subject

Electrical and Electronic Engineering,Computer Vision and Pattern Recognition,Signal Processing,Software

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1049/iet-ipr.2011.0128

Reference38 articles.

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3. Active contours without edges

4. Polarimetric image segmentation via maximum likelihood approximation and efficient multiphase level sets;Ayed I.B.;IEEE Trans. Pattern Anal. Mach. Intell.,2006

5. 2006 IEEE ICIP I.B. Ayed A. Mitiche A partition constrained minimization scheme for efficient multiphase level set image segmentation 1641 1644

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