Extending databases to support image editing

In order to understand similarity between images, recent research has focused on adaptable searches (Seidl and Kreigel, 1997) and fuzzy queries (Fagin, 1998). However, one of the best means for determining similarity between images is to know how the image was created (Brown et al., 1999). If the image is a combination of other images in the database, then there is a great deal of similarity between the base images and the created one. This requires extending the database to support image editing operations. We have built a preliminary system which does this by using a Web-based image editor and an image server. The editor and the server understand a logical model language that represents images. This paper then explores the issues of performance for deriving images from a sequence of operations