A Fuzzy Object Query Language (FOQL) for Image Databases

The image data as well as the nature of querying image data is fuzzy. Users like to retrieve images based on similarity rather than exact matching. Often, the users are able to provide only partial information while posing queries. As a consequence, the query languages of traditional databases which deal with precise data are inappropriate for querying image data. Content based retrieval systems have been developed for querying image data in which the users can pose queries based on visual properties such as color and texture. These systems which have advanced the state of the art in image database remarkably lack formal query languages. The traditional query languages are unable to capture the inherent fuzzy nature of the image data and content based querying. The fuzzy object query language (FOQL) presented in this paper addresses the need to support fuzzy values and fuzzy collections required for image databases. It can be used for deening schemas and high level concepts, and for querying image databases. FOQL provides the following advantages over other query languages. It allows users to deene high level concepts such as mountain and sunset in terms of low level features such as color and texture. It captures the inherent fuzzy nature of content based retrieval by keeping the query results fuzzy as against other query languages. The users can interactively reene their queries and high level concept deenitions using recursive and named query deenition constructs in FOQL. Being an extension of ODMG-OQL, FOQL can be easily mapped to ODMG-compliant visual query languages.