Home

About

Advanced Search

Browse by Discipline

Scientific Societies

E-print Alerts

Add E-prints

E-print Network
FAQHELPSITE MAPCONTACT US


  Advanced Search  

 
Y. Zhuang et al. (Eds.): PCM 2006, LNCS 4261, pp. 167 174, 2006. Springer-Verlag Berlin Heidelberg 2006
 

Summary: Y. Zhuang et al. (Eds.): PCM 2006, LNCS 4261, pp. 167 ­ 174, 2006.
© Springer-Verlag Berlin Heidelberg 2006
Fast Content-Based Image Retrieval Based
on Equal-Average K-Nearest-Neighbor Search Schemes
Zhe-Ming Lu1,2
, Hans Burkhardt2
, and Sebastian Boehmer2
1
Visual Information Analysis and Processing Research Center, Harbin Institute of Technology
Shenzhen Graduate School, Room 417, Building No.4, HIT Campus Shenzhen University
Town, Xili, Shenzhen 518055 P.R. China
zhemingl@yahoo.com
2
Institute for Computer Science, University of Freiburg, Georges-Koehler-Allee 052,
room 01-030, 79110 Freiburg i.Br., Germany
Hans.burkhardt@informatik.uni-freiburg.de
Abstract. The four most important issues in content-based image retrieval
(CBIR) are how to extract features from an image, how to represent these fea-
tures, how to search the images similar to the query image based on these fea-
tures as fast as we can and how to perform relevance feedback. This paper

  

Source: Albert-Ludwigs-Universität Freiburg, Institut für Informatik,, Lehrstuhls für Mustererkennung und Bildverarbeitung

 

Collections: Computer Technologies and Information Sciences