计算机工程与应用2017，Vol.53Issue(18)：163-169,242,8.DOI:10.3778/j.issn.1002-8331.1604-0146
视觉相似性计算的艺术图像自组织方法
Self-organization method for artistic images based on visual simi- larity computation
摘要
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 simi-larity computing, features of image such as color, texture, space layout and SIFT are extracted. According to the calcula-tion 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 lev-els on given image database, by which it constructs a hierarchical structure on the visual information for these images. Experi-mental results show that the proposed method can achieve better organizational efficiency for artistic images.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Key words
artistic image/feature extraction/similarity computation/hierarchical clustering/self-organization/image management分类
信息技术与安全科学引用本文复制引用
徐绕山,王爽,孙正兴..视觉相似性计算的艺术图像自组织方法[J].计算机工程与应用,2017,53(18):163-169,242,8.基金项目
国家重点实验室创新基金(No.ZZKT2013A12) （No.ZZKT2013A12）
江苏省科技支撑计划项目(No.BE2011058,No.BY2012190) （No.BE2011058,No.BY2012190）
江苏省高校哲学社会科学基金项目(No.2014SJB302). （No.2014SJB302）
