Efficient image recognition using local feature and fuzzy triangular number based similarity measures

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DOIResolve DOI: http://doi.org/10.4156/IJEI.vol3.issue1.5
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TypeArticle
Journal titleInternational Journal of Engineering and Industries
Volume3
Issue1
Pages4554; # of pages: 10
AbstractImage local scale invariant features are of great importance for object recognition. Among various local scale invariant feature descriptors, Scale Invariant Feature Transform (SIFT) descriptor has been shown to be the most descriptive one and thus widely applied to image retrieval, object recognition and computer vision. By SIFT descriptor, an image may be described by hundreds of key points with each point depicted by a 128-element feature vector; this representation makes the subsequent feature matching very computationally demanding. In this paper, we propose to incorporate the fuzzy set concepts into SIFT features and define fuzzy similarity between images. The proposed approach is applied to image recognition. Experimental results with the coil-100 image database are provided to show the superiority of the proposed approach.
Publication date
PublisherAdvanced Institute of Convergence IT
LanguageEnglish
AffiliationNRC Institute for Information Technology; National Research Council Canada
Peer reviewedYes
NPARC number20861006
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Record identifier6d74bcd1-600b-4472-8c5c-1d7bf8ea5784
Record created2012-10-25
Record modified2016-05-09
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