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
Each directed graph with the asymmetric costs defined over its arcs,can be represented by a table,which we call an expansion table.The basic properties of cycles and spanning tables of the expansion table correspondin...Each directed graph with the asymmetric costs defined over its arcs,can be represented by a table,which we call an expansion table.The basic properties of cycles and spanning tables of the expansion table corresponding to the cycles and spanning trees of the directed graph is first explored.An algorithm is then derived to find a minimum spanning table corresponding to a minimum spanning tree in the directed graph.Finally,how to use the algorithm to find the optimal expansion of competence set and related problems are discussed.展开更多
基金Supported by the Key National Natural Science Foundation of China(61035003)~~
文摘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.
基金Supported by National Natural Science Foundation of China(No.79870 0 30 )
文摘Each directed graph with the asymmetric costs defined over its arcs,can be represented by a table,which we call an expansion table.The basic properties of cycles and spanning tables of the expansion table corresponding to the cycles and spanning trees of the directed graph is first explored.An algorithm is then derived to find a minimum spanning table corresponding to a minimum spanning tree in the directed graph.Finally,how to use the algorithm to find the optimal expansion of competence set and related problems are discussed.
