Efficient multilevel image segmentation through fuzzy entropy maximization and graph cut optimization
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- 作者：Shibai Yina ; b ; shibai.yin@gmail.com" class="auth_mailAuthor Vitae ; Xiangmo ZhaoaAuthor Vitae ; Weixing WangaAuthor Vitae ; Minglun Gongb ; gong@cs.mun.ca" class="auth_mailAuthor Vitae
- 关键词：Image segmentation ; Multilevel thresholding ; Fuzzy c-partition entropy ; Artificial bee colony ; Iterative scheme ; Graph cut
- 刊名：Pattern Recognition
- 出版年：September 2014
- 年：2014
- 卷：47
- 期：9
- 页码：2894-2907
- 全文大小：6144 K
文摘
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Iterative scheme for accelerating fuzzy c-partition (c>2) entropy calculation.
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Evaluation of different optimization techniques for maximizing fuzzy entropy.
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Enforcing local spatial coherence in global threshold-based segmentation approaches.
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Outperform existing algorithms in terms of both result quality and processing speed.