关键词: 艺术图像, 特征提取, 相似性计算, 层次聚类, 自组织, 图像管理

Abstract: In order to solve the complicated and inefficient problem for organizing massive digital artistic images with general methods, this paper proposes a self-organization method based on visual similarity computation. For visual similarity computing, features of image such as color, texture, space layout and SIFT are extracted. According to the calculation model designed from the spatial layout of artistic images, the method calculates the clustering effect of images under different features, and adopts Multi-Layered version of Affinity Propagation （MLAP） clustering algorithm for various levels on given image database, by which it constructs a hierarchical structure on the visual information for these images. Experimental results show that the proposed method can achieve better organizational efficiency for artistic images.

Key words: artistic image, feature extraction, similarity computation, hierarchical clustering, self-organization, image management