alexa A Robust Image Retrieval System Using Weighted Composit
ISSN: 2320-2459

Research & Reviews: Journal of Pure and Applied Physics
Open Access

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Research Article

A Robust Image Retrieval System Using Weighted Composition of Features

Tohid Sedghi*

Department of Electrical Engineering, Urmia branch, Islamic Azad University, Urmia, Iran

*Corresponding Author:
Tohid Sedghi
Department of Electrical Engineering
Urmia branch, Islamic Azad University
Urmia, Iran.
Email:
[email protected]

Received date: 05/10/2012 Revised date: 17/11/2012 Accepted date: 16/12/2012

 

 

Abstract

A robust, flexible and effective image retrieval system using weighted combination of image retrieval features, is proposed. The proposed method properties such as, shape and spatial features are quite simple to derive and effective, and can be extracted in real time. The system is comprehensive because it incorporates Gabor filters of different grid sizes and flexible because the feature weights can be adjusted to achieve retrieval refinement according to user‟s need and robust because the system‟s algorithm is applicable to retrieval in all kinds of image database. In CBIR systems the common method of improving retrieval performance is by weighting the feature vectors. In this paper a new and reliable method of improving retrieval performance, and which complement feature weighting is proposed. Based on results obtained from this paper, we hereby state that the key to a breakthrough in current research in semantic image retrieval lies in the use of Gabor texture feature. Its benefits of Fourier as well as local analysis of images enable analysis of gradual changes of texture and texture variations which are essential properties of real-world scenes.

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