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- W2367563258 abstract "Feature extraction and similarity measurement for graphs are important issues in computer vision and pattern recognition.However,traditional methods could not describe the graphs under some non-rigid transformation adequately,so a new graph feature descriptor and its similarity measurement method were proposed based on Graph Context(GC) descriptor.Firstly,a sample point set was obtained by discretely sampling.Secondly,graph context descriptor was presented based on the sample point set.At last,improved Earth Mover's Distance(EMD) was used to measure the similarity for graph context descriptor.Different from the graph edit distance methods,the proposed method did not need to define cost function which was difficult to set in those methods.The experimental results demonstrate that the proposed method performs better for the graphs under some non-rigid transformation." @default.
- W2367563258 created "2016-06-24" @default.
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- W2367563258 date "2013-01-01" @default.
- W2367563258 modified "2023-09-25" @default.
- W2367563258 title "Graph context and its application in graph similarity measurement" @default.
- W2367563258 hasPublicationYear "2013" @default.
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