Statistical structuring of pictorial databases for content-based image retrieval systems

Bibtex entry :

@article { VG:PuS1996,
    author = { Thierry Pun and David McG. Squire },
    title = { Statistical structuring of pictorial databases for content-based image retrieval systems },
    journal = { Pattern Recognition Letters },
    year = { 1996 },
    volume = { 17 },
    pages = { 1299--1310 },
    keywords = { image databases, content-based image retrieval systems, exploratory statistics, correspondence analysis, ascendant hierarchical classification },
    url = { http://vision.unige.ch/publications/postscript/96/PuS96_prl_corran.ps.gz },
    abstract = { This letter presents a two-stage statistical approach for ``exploring and explaining'' a pictorial database, for content-based image retrieval systems. First, we describe how correspondence analysis provides images classes, as well as facilitates the understanding of the role of image primatives and attributes used to index pictures. Such understanding allows an intelligent choice of features, and thus computational savings, to be made. Second, ascendant heirarchical classification permits the structuring of the database, in order to ease picture indexing and retrieval. },
    url1 = { http://vision.unige.ch/publications/postscript/96/PuS96_prl_corran.pdf },
    vgclass = { refpap },
    vgproject = { {viper },
}