Shape Description and Recognition Based on Directed Complex Network

For shape boundary becomes instable in some non-rigid transformation and other issues on traditional undirected complex network models, a new directed complex network model based on inner distances has been proposed to characteristic shape boundaries.Firstly, boundary points and inner distances between these points are represented as nodes and weights of edges of the initial network, respectively.Then, this initial network evolved based on the k-nearest neighbor method and its subnetworks were generated at each evolution stage.Finally, features of these directed sub-networks are computed and concatenated to describe the shape boundary.Experimental results on both shape recognition and retrieval show that the proposed method can perform more robust than traditional undirected complex network models.