Application research of semantic ontology technology in content-based image retrieval

In the recent years, image retrieval is of high importance in the web community since there are so many useful images on web pages. Hence, it is a large challenge to make full use of so considerable data by conventional retrieval approach. The lack of semantic based retrieval capability has impeded application of remote sensing data. To address the issue, we propose a framework based on domain-dependent ontology to perform semantic retrieval in image archives. Firstly, primitive features expressed by color and texture are extracted to gain homogeneous region by means of kmeans unsupervised algorithm. The homogeneous regions are described by high-level concepts depicted and organized by domain specific ontology. Additionally, a reasoning mechanism over ontology integrating an inference engine is discussed. It enables the capability of semantic query in archives by mining the interrelationships among domain concepts and their properties to satisfy users' requirements. Finally, the paper does some testing experiment, whose result shows the feasibility of the framework.