Artificial Intelligence in 3-D Feature Extraction

The paper presents a general paradigm of knowledge-based system for automatic road extraction from aerial photography and high-resolution remotely sensed images. The method is based on low-level image processing for edge detection and linking, mid-level processing for feature formation, and high-level processing for the recognition of features. A generalized antiparallel pair is proposed to describe road boundaries. The recognition of roads is based on a model which includes the geometric and radiometric properties of a road and contextual information. The knowledge is expressed as rules in Prolog. To automate the generation of rules, machine learning techniques are exploited and a simple case study using a relational learning system FOIL is presented.

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