Document Type

Conference Paper

Rights

Available under a Creative Commons Attribution Non-Commercial Share Alike 4.0 International Licence

Disciplines

1.2 COMPUTER AND INFORMATION SCIENCE

Publication Details

6th European Conference on Case-Based Reasoning (ECCBR2002), Springer Verlag Lecture Notes in Artificial Intelligence; Aberdeen, Scotland, September, 2002.

Abstract

The amount and availability of high-quality geo-spatial image data, such as digital satellite and aerial photographs, is increasing dramatically. Task-based management of such visual information and associated knowledge is a central concern for organisations that rely on digital imagery. We are developing geo-spatial knowledge management techniques that employ case-based reasoning as the core methodology. In order to provide effective retrieval of task-based experiences that center around geo-spatial imagery, we need to forward novel similarity metrics for directly comparing the image components of experience cases. Based on work in geo-spatial image database retrieval, we are building an effective similarity metric for geo-spatial imagery that makes comparisons based on derived image features, their shapes, and the spatial relations between them. This paper gives an overview of the geo-spatial knowledge management context, describes our image similarity metric, and provides an initial evaluation of the work.

Download


Share

COinS