J4 ›› 2011, Vol. 38 ›› Issue (2): 47-53.doi: 10.3969/j.issn.1001-2400.2011.02.009

• 研究论文 • 上一篇    下一篇



  1. (西安电子科技大学 智能控制与图像工程研究所,陕西 西安  710071)
  • 收稿日期:2010-12-28 出版日期:2011-04-20 发布日期:2011-05-26
  • 通讯作者: 孟繁杰
  • 作者简介:孟繁杰(1978-),女,讲师,西安电子科技大学博士研究生,E-mail: Chinesemeng@sina.com.
  • 基金资助:


Image retrieval by using local distribution features of interest points and multiple-instance learning

MENG Fanjie;GUO Baolong   

  1. (Inst. of Intelligent Control & Image Engineering, Xidian Univ., Xi'an  710071, China)
  • Received:2010-12-28 Online:2011-04-20 Published:2011-05-26
  • Contact: MENG Fanjie



关键词: 图像检索, 兴趣点, 特征提取, 局部分布特征, 多示例学习


A novel method for image retrieval based on interest points is presented. The interest points are detected in the scale space. Then the image is divided into fan-shaped sub-regions of equal area according to the distribution of the interest points. Local features representing the spatial distribution information on the interest points are extracted to describe the image, and they are also robust to the image's rotation, scale and translation. In the relevant feedback, images are regarded as multiple-instance bags consisting of the local domain of the interest points in every fan-shaped sub-region. Labeled images chosen by the user are generated corresponding positive and negative bags, and the multiple-instance learning algorithm is employed to obtain the target concept reflecting the query image semantics. The method can reduce the ambiguity of the user query. Experimental results based on the Core image database show that our method improves the average retrieval precision by 7 percent or more, compared with other interest points based retrieval methods.

Key words: image retrieval, interest points, feature extraction, local distribution features, multiple-instance learning


  • TP391.41