12 May 2016 Content-based vessel image retrieval
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Abstract
This paper describes an approach to vessel classification from satellite images using content based image retrieval methodology. Content-based image retrieval is an important problem in both medical imaging and surveillance applications. In many cases the archived reference database is not fully structured, thus making content-based image retrieval a challenging problem. In addition, in surveillance applications, the query image may be affected by weather or/and geometric distortions. Our approach of content-based vessel image retrieval consists of two phases. First, we create a structured reference database, then for each new query image of a vessel we find the closest cluster of images in the structured reference database, thus identifying and classifying the vessel. Then we update the closest cluster with new query image.
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Satabdi Mukherjee, Samuel Cohen, Izidor Gertner, "Content-based vessel image retrieval", Proc. SPIE 9844, Automatic Target Recognition XXVI, 984412 (12 May 2016); doi: 10.1117/12.2234847; https://doi.org/10.1117/12.2234847
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