Image segmentation algorithm based on feature fusion and cluster

机译：基于特征融合和聚类的图像分割算法

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摘要

In order to make balance between the effect and time consumption of image segmentation, an image segmentation algorithm based on feature fusion and cluster is proposed in this paper. Firstly, the segmentation granularity is obtained adaptively according to the coarseness of image; secondly, different features are extracted, multi features are fused and classified by K-means clustering, and the image can be segmented quickly. Experiments show that the proposed algorithm can segment image quickly, and the segmentation effect is good, which has verified the validity.

机译：为了在图像分割的效果和时间消耗之间进行平衡，本文提出了一种基于特征融合和集群的图像分割算法。首先，根据图像的粗糙度自适应地获得分段粒度;其次，提取不同的特征，通过k-means聚类融合和分类多个特征，并且可以快速分割图像。实验表明，所提出的算法可以快速分割图像，分割效果好，这已经验证了有效性。

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来源
《2011 International Conference on Mechatronic Science, Electric Engineering and Computer》|2011年|p.1086-1089|共4页
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作者
Gao Zhanguo; Yao Li; Duan Fengyu;
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正文语种
中图分类机电一体化;
关键词
Clustering; Feature Fusion; Image Segmentation;

机译：聚类;特征融合;图像分割;

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机译：基于纹理特征融合的彩色图像分割优化聚类算法

Image segmentation algorithm based on feature fusion and cluster

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