Automated Feature Extraction from Scanned Nautical Charts and High-Resolution Images for GIS Applications Using Expert Systems Programmable with Pseudo-English

Converted from advanced automatic target recognition (ATR) processors, this new feature extraction/GIS system (a) uses raster data as input, and thus eliminates manual digitization; (b) uses expert systems to extract features automatically, and thus eliminates time-consuming and error-prone manual object tracing; and (c) vectorizes the extracted objects and converts them into GIS layers automatically, and thus eliminates the intermediate, man-in-the-loop steps of conventional GIS procedures. We achieve such data processing efficiency by first combining Image processing, Multi-sources analysis and GIS into one single system, second by using psuedo English as a programming language to perform pattern recognition, third by using a target identification system to perform numberic character recognition, and fourth by combining a rule-based object recognizer and an image-library-based object matcher into one integrated system. In this environment, each processor is an English key word, and a set of key words becomes an expert system that controls the entire feature extraction and GIS processes. We will demonstrate these claimed system capabilities and GIS benefits from testing with scanned NOAA nautical charts and government-supplied high-resolution image data, if appropriate.