Querying Images in the DISIMA DBMS

Because digital images are not meaningful by themselves, images are often coupled with some descriptive or qualitative data in an image database. Moreover the division of these data into syntactic (color, shape, texture) and semantic (meaningful real word object or concept) features necessitates novel querying techniques. Most image systems and prototypes have focussed on similarity searches based only on the syntactic features. In the DISIMA system we also propose a solution for similarity searches that combines color histograms, spatial relationships of image blocks and a hash structure to better discriminate among images. Additionally we query images on the basis of salient objects (regions of interest in images) and their properties. This paper presents the querying facilities implemented for the DISIMA system. Both the textual query language (MOQL) and its visual counterpart (VisualMOQL) allow the combination of semantic queries with different types of image queries for better results.