By Topic

On the use of conceptual information in a concept-based image indexing and retrieval framework

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$33 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

3 Author(s)
Radi Jarrar ; Faculty of Information Technology, Monash university ; Mohammed Belkhatir ; Chris H. Messom

Existing image retrieval frameworks use the low-level visual features extracted from images to learn a set of semantic categories and tend to discard the conceptual properties of these features. In this paper, we propose to use the conceptual information of the low-level image features to establish a correspondence between the image features and a set of high-level semantic categories. In doing so, image objects are indexed using concepts that describe the low-level color, texture, and shape features in a way that reflects the human understanding of their visual properties. Experimentally, we show that using the conceptual information outperforms using the low-level features for indexing and classifying image regions. In the retrieval process, we demonstrate the effectiveness of using the conceptual information in queries to enrich the search process of users by handling non-trivial queries incorporating both the semantic concepts and the conceptual information of the queried semantic concepts.

Published in:

2011 18th IEEE International Conference on Image Processing

Date of Conference:

11-14 Sept. 2011