Shape Recognition Using Unordered Point-Set Description and Matching of Object Contour
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National Natural Science Foundation of China (61372158); the Natural Science Foundation of Jiangsu Province (BK20141487), the “333” Foundation for high level talents of Jiangsu Province (BRA2015351); The industrialization of scientific research achievements in Universities of Jiangsu Province (JHB2012-18); the Project Funded by the Priority Academic Program Development of Jiangsu Higher Education Institutions (PAPD); and the Policy guidance program (Cooperation of Industry, Education and Academy) of Jiangsu Province (BY2016009-03)

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    Abstract:

    Treating the shape contour as an unordered point set and extracting shape features from it for fast and effective shape recognition is a challenge task of shape analysis. To address this issue, a complex-network based shape description and recognition method is proposed in this paper. In this method, a self-organized dynamic network-evolution model is built for providing a hierarchical description framework. In each moment of the dynamic evolution of the complex network, local and global measurements are performed against the network shut that both weighted and un-weighted features are extracted from the network. At the shape matching stage, the local matching (based on Hausdorff distance) and global matching (based on L1 distance) are conducted using the obtained local descriptor and global descriptor respectively. The dissimilar value between two shapes is determined by combining the two distance measures. Several standard test sets are used to evaluate the performance of the proposed method, and the experimental results show that the proposed method can provide robust and fast shape recognition in high accuracy.

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王斌.用于形状识别的目标轮廓无序点集描述与匹配.软件学报,2016,27(12):3131-3142

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History
  • Received:November 16,2015
  • Revised:March 22,2016
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  • Online: August 06,2016
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