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TWO IMPROVED GRAPH-THEORETICAL CLUSTERING ALGORITHMS 被引量:2
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作者 王波 丁军娣 陈松灿 《Transactions of Nanjing University of Aeronautics and Astronautics》 EI 2012年第3期263-272,共10页
Graph-theoretical approaches have been widely used for data clustering and image segmentation recently. The goal of data clustering is to discover the underlying distribution and structural information of the given da... Graph-theoretical approaches have been widely used for data clustering and image segmentation recently. The goal of data clustering is to discover the underlying distribution and structural information of the given data, while image segmentation is to partition an image into several non-overlapping regions. Therefore, two popular graph-theoretical clustering methods are analyzed, including the directed tree based data clustering and the minimum spanning tree based image segmentation. There are two contributions: (1) To improve the directed tree based data clustering for image segmentation, (2) To improve the minimum spanning tree based image segmentation for data clustering. The extensive experiments using artificial and real-world data indicate that the improved directed tree based image segmentation can partition images well by preserving enough details, and the improved minimum spanning tree based data clustering can well cluster data in manifold structure. 展开更多
关键词 image segmentation data clustering graph-theoretical approach directed tree method minimum spanning tree method
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