By Topic

Image Semantic Information Retrieval Based on Parallel Computing

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

2 Author(s)
Yun Ling ; Coll. of Comput. & Inf. Eng., Zhejiang Gongshang Univ., Hangzhou ; Yi Ouyang

Most of the algorithms proposed in the literature deal with the problem of digital image retrieval. To interpret semantic of image, many researcher use keywords as textual annotation. Concept recognition is a key problem in semantic information searching. In order to be effective and efficient, we proposed a parallel algorithm for semantic concept mapping, which adopts two-stages concept searching method. The first stage is to implement image low-level feature extraction schema; the second step is to implement latent semantic concept model searching, and bridging relationship between image low- level feature and global sharable ontology. Through combining ontology and image SIFT feature, the images on web pages and semantic concept can be mapping together for semantic searching. Experiments on several web pages sets show that it can outperform other methods in terms of precision and recall.

Published in:

2008 ISECS International Colloquium on Computing, Communication, Control, and Management  (Volume:1 )

Date of Conference:

3-4 Aug. 2008