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首页> 外文会议>International Conference on Fuzzy Systems and Knowledge Discovery(FSKD 2005) pt.1; 20050827-29; Changsha(CN) >Fuzzy Sets Theory Based Region Merging for Robust Image Segmentation
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Fuzzy Sets Theory Based Region Merging for Robust Image Segmentation

机译：基于模糊集理论的区域合并鲁棒图像分割

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摘要

A fuzzy set theory based region merging approach is presented to tackle the issue of oversegmentation from the watershed algorithm, for achieving robust image segmentation. A novel hybrid similarity measure is proposed as the merging criterion, based on the region-based similarity and the edge-based similarity. Both similarities are obtained using the fuzzy set theory. To adaptively adjust the influential degree of each similarity to region merging, a simple but effective weighting scheme is employed with the weight varying as region merging proceeds. The proposed approach has been applied to various images, including gray-scale images and color images. Experimental results have demonstrated that the proposed approach produces quite robust segmentations.
机译：提出了一种基于模糊集理论的区域合并方法，以解决分水岭算法的分割过度问题，实现鲁棒的图像分割。提出了一种基于区域相似度和边缘相似度的混合相似度度量作为融合准则。两种相似性都是使用模糊集理论获得的。为了自适应地调整每个相似度对区域合并的影响程度，采用了一种简单但有效的加权方案，其权重随区域合并的进行而变化。所提出的方法已经被应用于各种图像，包括灰度图像和彩色图像。实验结果表明，所提出的方法产生了非常鲁棒的分割。

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