Correspondence analysis and hierarchical indexing for content-based image retrieval

Ruggero Milanese, David Squire, Thierry Pun

Research output: Contribution to conferencePaper

15 Citations (Scopus)

Abstract

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 perform ascendant hierarchical classification, an iterative clustering method which constructs a hierarchical index structure for the images of the database. Experimental results supporting the applicability of both techniques to data sets of heterogeneous images are reported.

Original languageEnglish
Pages859-862
Number of pages4
Publication statusPublished - 1 Dec 1996
Externally publishedYes
EventIEEE International Conference on Image Processing 1996 - Lausanne, Switzerland
Duration: 16 Sep 199619 Sep 1996
Conference number: 1996
https://ieeexplore.ieee.org/xpl/conhome/4140/proceeding?isnumber=12183 (Proceedings)

Conference

ConferenceIEEE International Conference on Image Processing 1996
Abbreviated titleICIP 1996
CountrySwitzerland
CityLausanne
Period16/09/9619/09/96
Internet address

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