This paper describes progress towards engineering a combined GIS and image understanding system, designed to analyse remotely-sensed imagery in a task-oriented manner, with the task and contextual parameters being supplied by the GIS. The overall aim is to evaluate some of the more recent developments in the field of computer vision and to show how they may be integrated (along with more traditional methods of image interpretation) to improve system performance in terms of object recognition and extraction. Three aspects are reported: (1) Development of a formal notation as the basis of describing the process of transforming data from low level image representations to high level object representations; (2) Design of collaborating low and high level image processes used in this abstraction process and their control via Process Networks encapsulated into frames; and (3) Use of Dempster-Shafer Decision Theory as the basis for combining different types of evidence to improve the recognition of objects in the scene. Some sample results are presented to illustrate the issues raised and mechanisms for the co-operative processing of data are suggested.
['Mark Gahegan', 'Julien Flack']
The integration of scene understanding within a Geographic Information System: A prototype approach for agricultural applications