The demand for maps and related cartographic products has increased greatly over the past years. This increase in the demand for cartographic products has greatly increased the work load for the cartographer because current practice requires the cartographer to manually identify and delineate the significant cartographic features from an image. The availability of digital image data has made it possible to use the computer to assist in the extraction and delineation of cartographic features. This research presents one approach to automating the delineation of large area features using neural networks for texture pattern classification.
Identifer | oai:union.ndltd.org:arizona.edu/oai:arizona.openrepository.com:10150/277973 |
Date | January 1991 |
Creators | DeKruger, David, 1960- |
Contributors | Hunt, B. R. |
Publisher | The University of Arizona. |
Source Sets | University of Arizona |
Language | en_US |
Detected Language | English |
Type | text, Thesis-Reproduction (electronic) |
Rights | Copyright © is held by the author. Digital access to this material is made possible by the University Libraries, University of Arizona. Further transmission, reproduction or presentation (such as public display or performance) of protected items is prohibited except with permission of the author. |
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