Local grayvalue invariants for image retrieval

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Local grayvalue invariants for image retrieval (1997)

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by Cordelia Schmid , Roger Mohr

Venue:	IEEE Transactions on Pattern Analysis and Machine Intelligence
Citations:	544 - 27 self

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@ARTICLE{Schmid97localgrayvalue,
    author = {Cordelia Schmid and Roger Mohr},
    title = {Local grayvalue invariants for image retrieval},
    journal = {IEEE Transactions on Pattern Analysis and Machine Intelligence},
    year = {1997},
    volume = {19},
    pages = {530--535}
}

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Abstract

Abstract—This paper addresses the problem of retrieving images from large image databases. The method is based on local grayvalue invariants which are computed at automatically detected interest points. A voting algorithm and semilocal constraints make retrieval possible. Indexing allows for efficient retrieval from a database of more than 1,000 images. Experimental results show correct retrieval in the case of partial visibility, similarity transformations, extraneous features, and small perspective deformations. Index Terms—Image retrieval, image indexing, graylevel invariants, matching, interest points. 1

Keyphrases

local grayvalue invariant image retrieval interest point semilocal constraint similarity transformation large image database graylevel invariant image indexing correct retrieval extraneous feature voting algorithm efficient retrieval partial visibility small perspective deformation experimental result index term image retrieval

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