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A non-iterative clustering based soft segmentation approach for a class of fuzzy images
Wang ZZ(王振洲); Yang YM(杨永明)
作者部门机器人学研究室
关键词Clustering Slope Difference Distribution Interval Type-2 Fuzzy Logic Non-iterative Iterative
发表期刊APPLIED SOFT COMPUTING
ISSN1568-4946
2018-09-01
卷号70页码:988-999
收录类别SCI ; EI
EI收录号20172103694499
WOS记录号WOS:000443296000066
产权排序1
摘要

Many machine vision applications require to compute the size of the fuzzy object in the captured image sequences robustly. The size variation with the change of time is then utilized for the different purposes, e.g. data analysis, diagnosis and feedback control. To this end, robust image segmentation is required in the first place. Many state-of-the-art segmentation methods are based on iterative clustering, e.g. the expectation maximization (EM) method, the K-means method and the fuzzy C-means method. One drawback of the iterative learning based clustering methods is that they perform poorly when there are severe noise or outliers. Consequently, the hard segmentation results for the fuzzy images by these segmentation results are not robust enough and the computed sizes based on the hard segmentation results are not accurate either. In this paper, we propose a non-iterative clustering based approach to segment the fuzzy object from the fuzzy images. Instead of yielding a hard segmentation result, we utilize interval type-2 fuzzy logic to assign membership to the final segmentation result. Accordingly, we compute the size of the object based on the soft segmentation result. Experimental results show that the proposed non-iterative soft segmentation approach is more robust in computing the size of the fuzzy object than the hard approaches that yield a distinct segmentation result. (C) 2017 The Authors. Published by Elsevier B.V.

语种英语
WOS类目Computer Science, Artificial Intelligence ; Computer Science, Interdisciplinary Applications
关键词[WOS]Em Algorithm ; Incomplete Data ; Systems ; Likelihood ; Navigation
WOS研究方向Computer Science
引用统计
文献类型期刊论文
条目标识符http://ir.sia.cn/handle/173321/20494
专题机器人学研究室
通讯作者Wang ZZ(王振洲)
作者单位State Key Lab of Robotics, Shenyang Institute of Automation, Chinese Academy of Science (CAS), Shenyang, China
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GB/T 7714
Wang ZZ,Yang YM. A non-iterative clustering based soft segmentation approach for a class of fuzzy images[J]. APPLIED SOFT COMPUTING,2018,70:988-999.
APA Wang ZZ,&Yang YM.(2018).A non-iterative clustering based soft segmentation approach for a class of fuzzy images.APPLIED SOFT COMPUTING,70,988-999.
MLA Wang ZZ,et al."A non-iterative clustering based soft segmentation approach for a class of fuzzy images".APPLIED SOFT COMPUTING 70(2018):988-999.
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