Title :
Image domain ontology fusion approach using multi-level inference mechanism
Author :
Wang Yuan ; Yang Xing
Author_Institution :
Dept. of Comput. & Inf. Eng., Huainan Normal Univ., Huainan, China
Abstract :
One of the main challenges in content-based or semantic image retrieval is still to bridge the gap between low-level features and semantic information. In this paper, An approach is presented using integrated multi-level image features in ontology fusion construction by a fusion framework, which based on the latent semantic analysis. The proposed method promotes images ontology fusion efficiently and broadens the application fields of image ontology retrieval system. The relevant experiment shows that this method ameliorates the problem, such as too many redundant data and relations, in the traditional ontology system construction, as well as improves the performance of semantic images retrieval.
Keywords :
image fusion; image retrieval; ontologies (artificial intelligence); fusion framework; image domain ontology fusion; image ontology retrieval system; low-level features; multilevel inference mechanism; ontology fusion construction; semantic information; Animals; Buildings; Delay; LCA; OWL Lite; domain ontology construction; image ontology fusion; multi-level features;
Conference_Titel :
Computer Science and Network Technology (ICCSNT), 2011 International Conference on
Conference_Location :
Harbin
Print_ISBN :
978-1-4577-1586-0
DOI :
10.1109/ICCSNT.2011.6182514