DocumentCode :
592884
Title :
Content based image retrieval based on Database revision
Author :
Sreedevi, S. ; Sebastian, Silpa
Author_Institution :
Dept. of Electron. & Commun., Amal Jyothi Coll. of Eng., Kanjirappally, India
fYear :
2012
fDate :
14-15 Dec. 2012
Firstpage :
29
Lastpage :
32
Abstract :
Images are the simplest and best way of representation of ideas. The significance of images has been considerably increased by the web pages. Thus efficient image retrieval systems are essential. Content-based image retrieval (CBIR) systems are the latest area of research. In this paper, an intelligent image retrieval system based on a novel method called database revision (DR) is proposed. Image feature extraction in terms of color, texture and shape is employed to retrieve images from the database. The result of feature similarity comparison of the query image with database images rewrites the database. The system is made interactive for the users to identify the images that are most satisfied to the need. The user-satisfied images are analyzed and the database is revised to make the system intelligent. Experiment results and comparisons are presented to demonstrate the feasibility of the proposed method.
Keywords :
Internet; content-based retrieval; feature extraction; image colour analysis; image retrieval; image texture; visual databases; CBIR systems; DR method; Web pages; content based image retrieval; database revision method; feature similarity comparison; image color feature; image database rewriting; image feature extraction; image identification; image shape; image texture; intelligent image retrieval system; query image; user-satisfied images; Feature extraction; Genetic algorithms; Image color analysis; Image retrieval; Shape; Visualization; Content-based image retrieval (CBIR); feature extraction; relevance feedback;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Machine Vision and Image Processing (MVIP), 2012 International Conference on
Conference_Location :
Taipei
Print_ISBN :
978-1-4673-2319-2
Type :
conf
DOI :
10.1109/MVIP.2012.6428753
Filename :
6428753
Link To Document :
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