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Adaptable image retrieval with application to underwater target identification

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2 Author(s)
Salazar, J. ; Dept. of Electr. & Comput. Eng., Colorado State Univ., Fort Collins, CO, USA ; Azimi-Sadjadi, M.R.

This paper presents a study on an adaptable image retrieval system used for underwater target identification. Shape and textural features extracted from contrast and range electro-optical imagery data are used to represent each mine-like or non-mine-like sample image. The retrieval system is an adaptable two-layer network where the first layer is structurally adaptable in response to relevance feedback from expert users, while the second layer is adaptable only when a new class is introduced. Each node in the second layer represents one sample image in the training database. Test results on a large electro-optical imagery database are presented, which show the promise of the proposed system as an adaptable image retrieval system.

Published in:

Signals, Systems and Computers, 2004. Conference Record of the Thirty-Eighth Asilomar Conference on  (Volume:2 )

Date of Conference:

7-10 Nov. 2004