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Wavelet transformation for content-based image retrieval combine G-Regions of interest

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Indexed by:期刊论文

Date of Publication:2011-01-01

Journal:Advances in Intelligent and Soft Computing

Included Journals:EI、CPCI-S、Scopus

Volume:129

Page Number:285-291

ISSN No.:9783642259852

Key Words:Image Retrieval; GROI; Wavelet Transform

Abstract:This paper in the research of Region-Based characteristic image retrieval method foundation, proposed a new kind of the color image retrieval method based on wavelet transformation G-Regions Of Interest (GROI). We first use HVS(Human Visual System) characteristic to choose the color space which fit for the visual characteristics, then use K-means clustering to extract the areas of interest in the wavelet transform domain, and using the local energy of the wavelet coefficients in the areas of interest as the texture feature, color's mean and variance as the color feature, the barycentric coordinates as the position feature. We calculated the similarity between the image content and retrieval. The simulation results show that this GROI method which combined color characteristic, texture characteristic and position characteristic can more accurately find the necessary content of the images to users, significantly improve the accuracy in color image retrieval. © 2011 Springer-Verlag Berlin Heidelberg.

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