半监督学习,图像检索,不变特征," /> 半监督学习,图像检索,不变特征,"/> Semi-supervised image retrieval based on diversity and invariant features

JOURNAL OF SHANDONG UNIVERSITY (ENGINEERING SCIENCE) ›› 2010, Vol. 40 ›› Issue (5): 150-153.

• Articles • Previous Articles     Next Articles

Semi-supervised image retrieval based on diversity and invariant features

SU Hong-lu, LI Fan-zhang*   

  1. College of Computer Science and Technology, Soochow University, Suzhou 215006, China
  • Received:2010-04-23 Online:2010-10-16 Published:2010-04-23

PDF (PC)

1066

Abstract:

Based on the idea of isomorphism, the image translation and rotation invariant feature could be formalized through the bispectrum. In order to expand the semantic scope of the results, a method called image retrieval based on diversity and invariant features (IRDIF) which can expand the diversity in search result has been applied in the semisupervised image retrieval. The item which has been visited will be set to be absorbing state, then the other items which are similar to the item of absorbing state will have smaller visiting probability. With this method, an experiment upon Corel database is conducted, and the final effect turns out to be quite satisfactory.

Key words:  semi-supervised learning, image retrieval, invariant features

[1] KONG Chao1,2, ZHANG Huaxiang1,2*, LIU Li1,2. A semi-supervised image retrieval algorithm based onfeature fusion of the region of interest [J]. JOURNAL OF SHANDONG UNIVERSITY (ENGINEERING SCIENCE), 2014, 44(3): 22-28.
[2] XIE Huo-sheng, LIU Min. An ensemble co-training algorithm based on active learning [J]. JOURNAL OF SHANDONG UNIVERSITY (ENGINEERING SCIENCE), 2012, 42(3): 1-5.
[3] CAI Nian, ZHANG Guo-hong, LOU Peng-xu, DAI Qing-yun. Image retrieval for a design patent based on shape
features and texture features [J]. JOURNAL OF SHANDONG UNIVERSITY (ENGINEERING SCIENCE), 2011, 41(2): 1-4.
[4] ZHENG Junjun1, XIA Shengping1, LI Xinguang1, ZHU Yiwei1, LIU Jianjun1, TAN Liqiu1,2. K nearest neighbors detecting algorithm based on a RSOM tree [J]. JOURNAL OF SHANDONG UNIVERSITY (ENGINEERING SCIENCE), 2011, 41(2): 80-84.
[5] HE Guang-nan, YANG Yu-bin*. Image retrieval algorithms based on manifold learning [J]. JOURNAL OF SHANDONG UNIVERSITY (ENGINEERING SCIENCE), 2010, 40(5): 129-136.
[6] CHEN Hu, LI Ming*, JIANG Yuan, ZHOU Zhi-hua. iCome: image retrieval system based on ambiguity [J]. JOURNAL OF SHANDONG UNIVERSITY (ENGINEERING SCIENCE), 2010, 40(5): 112-116.
[7] ZHOU Xin-hong,PENG Yu-hua,LIU Yong,QU Huai-jing . Image retrieval based on multi-scale analysis and SVM relevance feedback [J]. JOURNAL OF SHANDONG UNIVERSITY (ENGINEERING SCIENCE), 2008, 38(2): 45-50 .
[8] , . Research on Face Image Retrieval Based on Principal Independent [J]. JOURNAL OF SHANDONG UNIVERSITY (ENGINEERING SCIENCE), 2007, 37(4): 0-0 .
[9] SUN Guo-xia,SUN Xing-hua,BAI Shu-zhong,LIU Ju,SUN Jian-de . Research on face image retrieval based on principal independent content features [J]. JOURNAL OF SHANDONG UNIVERSITY (ENGINEERING SCIENCE), 2007, 37(4): 81-84 .
[10] XIE Hong-sheng,ZHANG Hong . [J]. JOURNAL OF SHANDONG UNIVERSITY (ENGINEERING SCIENCE), 2006, 36(6): 95-99 .
Viewed
Full text


Abstract

Cited
  Shared   
  Discussed   
No Suggested Reading articles found!
Copyright 2018 © Editorial office of Journal of Shandong University (Engineering Science)
Supported by Beijing Magtech Co.Ltd