Abstract
This paper addresses the topic of semi-automatic object extraction for GIS data capture. It includes novel algorithms and conceptual strategies, together with performed experiments, encountered problems and adopted solutions. In particular, we present an algorithm and obtained results for semi-automatic extraction of road networks from SPOT imagery using wavelet-transformed images and cost functions expressing local gray value variations and global continuity constraints. For larger scale images and for various object types, we present our technique of least squares template matching for edge extraction, which uses local gray value variations to precisely identify edge locations. Finally, we propose a global approach for semi-automatic object outline detection, whereby least squares matching provides the mathematical foundation, while global continuity is enforced through the introduction of object-type-dependent shape constraints.
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© 1994 Springer-Verlag Berlin Heidelberg
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Gruen, A., Agouris, P., Stallmann, D., Li, H. (1994). Algorithms for automated extraction of man-made objects from raster image data in a GIS. In: Nievergelt, J., Roos, T., Schek, HJ., Widmayer, P. (eds) IGIS '94: Geographic Information Systems. IGIS 1994. Lecture Notes in Computer Science, vol 884. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-58795-0_41
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DOI: https://doi.org/10.1007/3-540-58795-0_41
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