Search results for key=MSP1996 :
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Refereed full papers (journals, book chapters, international conferences)
1996
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Ruggero Milanese, David McG. Squire and Thierry Pun,
Correspondence Analysis and Hierarchical Indexing For
Content-Based Image Retrieval,
In P. Delogne ed., IEEE International Conference on Image Processing,
Lausanne, Switzerland, Vol. 3, pp. 859-862, September 1996.
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 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.
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