计算机科学 ›› 2014, Vol. 41 ›› Issue (2): 312-316.

• 图形图像与模式识别 • 上一篇    下一篇

基于头饰特征的唐卡标注和检索

毕学慧,刘华明,王维兰   

  1. 阜阳师范学院计算机与信息学院 阜阳236000;阜阳师范学院计算机与信息学院 阜阳236000;西北民族大学计算机科学与信息工程学院 兰州730030
  • 出版日期:2018-11-14 发布日期:2018-11-14
  • 基金资助:
    本文受国家自然科学基金项目(60875006),安徽省教育厅自然科学基金项目(KJ2013B195,KJ2012B131),阜阳师范学院自然科学基金项目(2011FSKJ04)资助

Thangka Annotation and Retrieval Based on Headdress Features

BI Xue-hui,LIU Hua-ming and WANG Wei-lan   

  • Online:2018-11-14 Published:2018-11-14

摘要: 通过提取唐卡头饰特征实现自动分类的主要步骤有:通过人机交互选择头饰区域,采用迭代与基于RGB的算法分割,预处理分割结果,获取头饰的初始分割图;提取初始分割图的欧拉数特征以分出头冠;提取初始分割图外轮廓的傅里叶描述子特征,根据特征值到各自聚类中心的距离来分类发髻和僧帽。唐卡头饰自动分类的实现,提高了分类效率,满足了头饰自动语义标注和语义检索的需要。根据应用需求,设计的唐卡检索系统不仅可以实现基于文本、内容和语义的检索,还提高了检索的精确度。

关键词: 唐卡检索,头饰分类,语义标注,分级检索系统 中图法分类号TP391文献标识码A

Abstract: Automatic classification can be done by extracting Thangka headdress features,the main steps:1) select the headdress region through human-computer interaction and obtain initial segmentation image by preprocessing the segmentation result which is segmented through iterative segmentation or segmentation algorithm based on RGB;2) separate the crown by the Euler number which is extracted from the initial segmentation image;3) extract Fourier descriptors from out contour of the initial segmentation image,separate hairpin or monk hat through the distance between the feature and each cluster center.The realization of headdress automatic classification can improve the classification efficiency and meet the needs of automatic semantic annotation and semantic retrieval.According to the demand of application,we designed a retrieval system,which can realize retrieval based on text,content and semantics,and improve the accuracy of retrieval.

Key words: Thangka retrieval,Headdress classification,Semantic annotation,Hierarchical retrieval system

[1] 王维兰,唐世喜,钱建军,等.基于内容的唐卡图像数据库检索系统[J].湛江师范学院学报,2008,9(3):91-95
[2] Qian Jian-jun,Wang Wei-lan.Main feature extraction and ex-pression for religious portrait Thangka image[C]∥The 9th International Conference for Young Computer Scientists,2008.Los Vaqueros Circle:IEEE Computer Society Press,2008:803-807
[3] 钱建军.基于语义的唐卡图像标注于检索研究[D].兰州:西北民族大学,2010
[4] 王维兰,钱建军,杨旦春,等.基于频率谱变化量的唐卡图像特征提取与表示[J].计算机工程与应用,2011,7(22):183-187
[5] 李玲,尚文文.基于迭代算法对CT肝脏感兴趣区域的提取[J].医疗卫生装备,2010,1(7):29-32
[6] 孙君顶,赵珊.图像低层特征提取与检索技术[M].北京:电子工业出版社,2009:92-93
[7] Person E,Fu K S.Shape discrimination using Fourier descrip-tors[J].IEEE Transactions on Systems,Man and Cybernetics,1977,7(3):170-179
[8] 潘崇,朱红斌.改进k-means算法在图像标注和检索中的应用[J].计算机工程与应用,2010,6(4):183-185
[9] Kunttu I,Lepistoe L,Rauhamaa J,et al.Multiscale Fourier descriptors for defect image retrieval[J].Pattern Recognition Letters,2006,7(2):123-132
[10] Belongie S,Malik J,Puaicha J.Shape matching and object recognition using shape contexts [J].IEEE Transactions on Pattern Analysis and Machine Intelligence,2002,4(4):509-522

No related articles found!
Viewed
Full text


Abstract

Cited

  Shared   
  Discussed   
No Suggested Reading articles found!