中南大学学报（自然科学版）2016，Vol.47Issue(7)：2326-2333,8.DOI:10.11817/j.issn.1672-7207.2016.07.021
结合领域知识和多特征表示的唐卡破损区域分割算法
Damaged region segmentation of Thangka based on domain knowledge and multi-feature
摘要
Abstract
A method was proposed to segment the consistent broken area of Buddha Thangka. Firstly, the head light area was projected and the symmetry axis was obtained by one-dimensional function symmetry detection method, and then the initial segmentation result was received based on the symmetric axis block segmentation. Secondly, the texture feature was extracted by Gabor transform, and the multi-scale features set was constructed combined with the Lab color space feature. The consistent broken area template was ultimately achieved by K−Nearest Neighbor (KNN) classification. The results show that this algorithm has an effective segmentation on the consistent broken area of the Buddha Thangka.关键词
唐卡/一致性破损区域/图像分割/镜像对称/多特征表示Key words
Thangka/consistent broken area/image segmentation/reflectional symmetries/multi-feature representation分类
信息技术与安全科学引用本文复制引用
胡文瑾,王维兰,刘仲民..结合领域知识和多特征表示的唐卡破损区域分割算法[J].中南大学学报（自然科学版）,2016,47(7):2326-2333,8.基金项目
国家自然科学基金资助项目(61561042)；中央高校基本科研业务费专项资金项目(31920150082)(Project(61561042) supported by the National Natural Science Foundation of China （61561042）
Project(31920150082) supported by the Fundamental Research Funds for the Central Universities) （31920150082）
