Proceedings chapter
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Correspondence Analysis and Hierarchical Indexing For Content-Based Image Retrieval

Presented atLausanne (Switzerland)
Published inP. Delogne (Ed.), IEEE International Conference on Image Processing, p. 859-862
Publication date1996
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 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. P. Delogne (Ed.). Lausanne (Switzerland). [s.l.] : [s.n.], 1996. p. 859–862.
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