Production environment implementation of the stereo extraction of cartographic features using computer vision and knowledge base systems in DMA's digital production system

摘要

The prototypic nature of knowledge base systems has made it difficult to realize a 'production environment knowledge base system', until now. We will describe the use of computer vision and knowledge base system (KBS) techniques to delineate, identify, and attribute cartographic features from digital stereo imagery, with the distinction that these functions are implemented in a large production environment. Along with a discussion of the technology that supports this application, we broach the realities of using KBS technology in large production environments. The KBS chiefly assists in the cartographic feature identification and attribution. Our paper will cover the knowledge acquisition activities and the selection knowledge representations that supported the construction of the knowledge base as well as the inference engine that supports the operation of the KBS. We will describe in detail the computer vision tools and the level of image understanding that is achieved by their application. This includes a discussion of the 'computer vision tool box' used for the delineation of cartographic features. Of particular interest are the variety of technologies that support the tool box, such as the use of artificial neural networks. Because of their significance to the real world success of KBS technology, we include the subjects of risk mitigation in the design phase in addition to the ongoing KBS support in the maintenance phase.