Vision-Based Image Processing of Digitized Cadastral Maps

This paper presents an automatic method for processing digitized images of cadastral maps. The method includes two major algorithms: a segmentation and a Raster-to-Vector conversion. Those algorithms use a simple data-list structure for recording data created during single-pass, row-majority scanning and line tracing. The segmentation algorithm obtains the positions and sizes of symbols and characters, in addition to completing map segmentation and proving useful for pattern recognition. The Raster-to-Vector conversion alprithm obtains topological information necessary to relate cadastral map spatial data to line start points, midpoints, intersection points, and termination points. It consists of four integrated sub-algorithms that remove noise, unify run-length coordinates, and perform synchronous line approximations and logical linkage of line breaks. Straight, angled, and curved lines can then be completely reconstructed for display. Also presented are six indices that verify algorithm and experimental results.