Feature Distribution Based Quick Image Retrieval

摘要：

Query by image example is still a challenge in image retrieval. The goal of similarity retrieval in images is to get the similar images quickly and accurately in high-dimension space. The accuracy of similarity retrieval in high-dimension space is mainly decided by the features representing images and the method used for similar calculation. Our main goal in this paper is to improve the retrieval speed without great lost of accuracy. We propose a filtering method to greatly reduce the search range based on two assumptions: (1) the similar images will have similar amount of SIFT(scale invariant feature transform) features;(2) the similar images will all contain the important features. In contrast to prior work on similarity retrieval in high-dimension space, we use the distribution of features of images to filter the target images. Experimental results show that our approach can significantly reduce the time complexity.

关键词： Similar retrieval high dimension space feature based search

作者: Weifeng Zhang Shuaiqiu Men Lei Xu Baowen Xu

作者单位: College of Computer, Nanjing University of Posts and Telecommunications, Nanjing, China College of Computer, Southeast University, Nanjing, China College of Computer, Nanjing University, Nanjing, China

会议类型: 国际会议

会议名称: 2010 Seventh Web Information System and Applications Conference(第七届全国web信息系统及其应用学术会议)

会议地点: 呼和浩特

会议语种:英文

页码: 23-28

在线出版日期: 2010-08-20（万方平台首次上网日期，不代表论文的发表时间）