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Proceedings Paper

Content-based vessel image retrieval
Author(s): Satabdi Mukherjee; Samuel Cohen; Izidor Gertner
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Paper 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.

Paper Details

Date Published: 12 May 2016
PDF: 20 pages
Proc. SPIE 9844, Automatic Target Recognition XXVI, 984412 (12 May 2016); doi: 10.1117/12.2234847
Show Author Affiliations
Satabdi Mukherjee, The City College of New York (United States)
Samuel Cohen, The City College of New York (United States)
Izidor Gertner, The City College of New York (United States)


Published in SPIE Proceedings Vol. 9844:
Automatic Target Recognition XXVI
Firooz A. Sadjadi; Abhijit Mahalanobis, Editor(s)

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