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Attention Driven Model for Image Retrieval Applications

Published on None 2011 by Satrajit Acharya, M.R.Vimala Devi
journal_cover_thumbnail
International Conference on VLSI, Communication & Instrumentation
Foundation of Computer Science USA
ICVCI - Number 3
None 2011
Authors: Satrajit Acharya, M.R.Vimala Devi
05e88247-a3cc-4be3-a23f-52c8fb952956

Satrajit Acharya, M.R.Vimala Devi . Attention Driven Model for Image Retrieval Applications. International Conference on VLSI, Communication & Instrumentation. ICVCI, 3 (None 2011), 23-25.

@article{
author = { Satrajit Acharya, M.R.Vimala Devi },
title = { Attention Driven Model for Image Retrieval Applications },
journal = { International Conference on VLSI, Communication & Instrumentation },
issue_date = { None 2011 },
volume = { ICVCI },
number = { 3 },
month = { None },
year = { 2011 },
issn = 0975-8887,
pages = { 23-25 },
numpages = 3,
url = { /proceedings/icvci/number3/2644-1187/ },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Proceeding Article
%1 International Conference on VLSI, Communication & Instrumentation
%A Satrajit Acharya
%A M.R.Vimala Devi
%T Attention Driven Model for Image Retrieval Applications
%J International Conference on VLSI, Communication & Instrumentation
%@ 0975-8887
%V ICVCI
%N 3
%P 23-25
%D 2011
%I International Journal of Computer Applications
Abstract

Image Retrieval has always been an area of extensive research. Many efficient retrieval algorithms have already been proposed. Text based image retrieval system got replaced and Content Based Image Retrieval (CBIR) came into being. CBIR, more efficient than text based image retrieval, has already been implemented by several techniques and researches are going on to increase the efficiency. This paper proposes a new technique of incorporating visual attention model to segment and extract the ROI from an image and then use the result for image retrieval purposes. The main advantage of this concept lies in the improvement of the performance of this retrieval scheme in terms of two parameters: Precision and Recall. Keywords: image retrieval,precision,recall.

References
  1. Oge Marques, “An attention-driven model for grouping similar images with image retrieval applications”, Eurasip Journal on Advances in Signal Processing, Special Issue on Image Perception, Vol. 2007, Article ID 43450, 17 pages, 2007.
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Index Terms

Computer Science
Information Sciences

Keywords

Image Retrieval Attention Driven Model