Efficient Content-based Image Retrieval Using Weighted Feature Aggregation Scheme
Date Issued
2010
Author(s)
Jankulovski, Blagojce
Loshkovska, Suzana
Abstract
This paper presents a content-based image retrieval system for
aggregation and combination of different image features. Feature aggregation is
important technique in general content-based image retrieval systems that
employ multiple visual features to characterize image content. We introduced
and evaluated linear combination to fuse different features. The most important
step in the feature aggregation is to find suitable weights for the individual
features. We have used relevance feedback techniques to determine the salient
features and to learn weights for each feature. The weights are used in linear
combination scheme that we call weighted feature aggregation. The
implemented system has several advantages over the existing content-based
image retrieval systems. Several implemented features included in our system
allow the user to adapt the system to the query image. The weighted
combination of features allows flexible query formulations and helps
processing specific queries for which users have no knowledge about any
suitable descriptors.
aggregation and combination of different image features. Feature aggregation is
important technique in general content-based image retrieval systems that
employ multiple visual features to characterize image content. We introduced
and evaluated linear combination to fuse different features. The most important
step in the feature aggregation is to find suitable weights for the individual
features. We have used relevance feedback techniques to determine the salient
features and to learn weights for each feature. The weights are used in linear
combination scheme that we call weighted feature aggregation. The
implemented system has several advantages over the existing content-based
image retrieval systems. Several implemented features included in our system
allow the user to adapt the system to the query image. The weighted
combination of features allows flexible query formulations and helps
processing specific queries for which users have no knowledge about any
suitable descriptors.
Subjects
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