Image Domain Ontology Inference Mechanism with Heterogeneous Features

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, A two-phase hybrid knowledge base inference mechanism based on DL and FOL is presented using integrated heterogeneous image features in ontology reasoning. The proposed method, having been proved by FO theory, promotes images ontology inference efficiently, and broadens the application fields of image ontology retrieval system. The relevant experiment shows that this method ameliorates the problems such as too many redundant data and relations in the traditional ontology system construction. The method also improves the performance of semantic images retrieval.