关键词: 特征提取, 复杂网络, 内部距离, 动态演化

Abstract: Shape feature extraction is important in content based image recognition. Considering the variance of shape, this paper presents a new shape feature extraction method based on multi-model complex network. Firstly, an initial complex network is constructed with nodes corresponding to the boundary points and edges allocated with Euclidean and inner distances as weights existing between each node pairs. Then, this initial network is evolved based on Euclidean and inner distances, respectively. At last, some features are extracted from these sub-networks and further provided for the shape. Experimental results on both object classification and retrieval show that the proposed method is more robust compared with the single-model complex network model.

Key words: feature extraction, complex network, inner distance, dynamic evolution