Proceedings chapter
Open access

Correspondence Analysis and Hierarchical Indexing For Content-Based Image Retrieval

Published inIEEE International Conference on Image Processing, Editors P. Delogne, p. 859-862
Presented at Lausanne (Switzerland)
Publication date1996

This paper describes a two-stage statistical approach supporting content-based search in image databases. The first stage performs correspondence analysis, a factor analysis method transforming image attributes into a reduced-size, uncorrelated factor space. The second stage performs ascendant heirarchical classification, an iterative clustering method which constructs a heirarchical index structure for the images of the database. Experimental results supporting the applicability of both techniques to data sets of heterogeneous images are reported.

Citation (ISO format)
MILANESE, Ruggero, SQUIRE, David, PUN, Thierry. Correspondence Analysis and Hierarchical Indexing For Content-Based Image Retrieval. In: IEEE International Conference on Image Processing. Lausanne (Switzerland). [s.l.] : [s.n.], 1996. p. 859–862.
Main files (1)
Proceedings chapter (Published version)
  • PID : unige:47838

Technical informations

Creation03/06/2015 5:12:17 PM
First validation03/06/2015 5:12:17 PM
Update time03/14/2023 10:59:25 PM
Status update03/14/2023 10:59:25 PM
Last indexation08/29/2023 3:12:40 PM
All rights reserved by Archive ouverte UNIGE and the University of GenevaunigeBlack