This paper uses complex network theory to analyze the shape characteristics.Based on inner distance of shape

a shape is modeled into a small-world complex network

through analyze degree and cluster coefficient characteristics of nodes in the dynamic evolution of complex network

multi-scale histograms on nodes distribution is proposed for shape descriptor;describe contour points of shape with multi-scale degree、cluster coefficient characteristics and shape context features based on inner distance

this paper combines the improved optimal subsequence bijection to achieve shape matching.Experiment analyzes the capacity of complex network characteristics for shape descriptor

experimental results show that the proposed algorithm can achieve shape matching with non-rigid transformations and the high precision in shape retrieval.