ISSN:
1573-7675
Keywords:
content-based access of images
;
image representation
;
intelligent information retrieval
;
knowledge representation
;
image databases
;
query containment
;
description logics
;
intentional reasoning
Source:
Springer Online Journal Archives 1860-2000
Topics:
Computer Science
Notes:
Abstract The problem of content management of multimedia data types (e.g., image, video, graphics) is becoming increasingly important with the development of advanced multimedia applications. Traditional database management systems are inadequate for the handling of such data types. They require new techniques for query formulation, retrieval, evaluation, and navigation. In this paper we develop a knowledge-based framework for modeling and retrieving image data by content. To represent the various aspects of an image object's characteristics, we propose a model which consists of three layers: (1) Feature & Content Layer, intended to contain image visual features such as contours, shapes, etc.; (2) Object Layer, which provides the (conceptual) content dimension of images; and (3) Schema Layer, which contains the structured abstractions of images, i.e., a general schema about the classes of objects represented in the object layer. We propose two abstract languages on the basis of description logics: one for describing knowledge of the object and schema layers, and the other, more expressive, for making queries. Queries can refer to the form dimension (i.e., information of the Feature & Content Layer) or to the content dimension (i.e., information of the Object Layer). These languages employ a variable free notation. As the amount of information contained in the previous layers may be huge and operations performed at the Feature & Content Layer are time-consuming, resorting to the use of materialized views to process and optimize queries may be extremely useful. For that, we propose a formal framework for testing containment of a query in a view expressed in our query language.
Type of Medium:
Electronic Resource
URL:
http://dx.doi.org/10.1023/A:1008731702009
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