Correspondence analysis and hierarchical indexing for content-based image retrieval

Ruggero Milanese, David Squire, Thierry Pun

Research output: Contribution to conferencePaperpeer-review

15 Citations (Scopus)


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
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 (Proceedings)


ConferenceIEEE International Conference on Image Processing 1996
Abbreviated titleICIP 1996
Internet address

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