| Agouris P., A. Stefanidis & J. Carswell "Intelligent Retrieval of Digital Images from Large Geospatial Databases", International Archives of Photogrammetry and Remote Sensing, Vol. XXXII, Part 3/1, pp. 515-522, 1998, Columbus, OH. |
.... often in the context of military applications) Chellapa et al. 1994; Mueller and Olson, 1995; Huertas et al. 1995) Use of image analysis for automatic interpretation and vectorisation of maps (Frischknecht et al. 1998) Use of image analysis in data mining, image retrieval and queries (Agouris et al. 1998; Datcu and Seidel, 1999) Matching of maps and vector datasets (often termed conflation ) e.g. for combination of one road vector dataset with good geometry with another one having poor geometry but rich and up to date attributes. Use of image analysis to extend existing spatial databases ....
Agouris, P., Stefanidis, A., Carswell, J., 1998. Intelligent retrieval of digital images from large geospatial database. IAPRS, Vol. 32, Part 3/1, Columbus, USA, pp. 515-522.
....rotations, and scalings) to match a library feature. A matching percentage expresses the quality of the match, corresponding to the percentage of perfect pixel correspondences between the input outline and the library entry. For a more detailed description of the matching tool, please refer to [1]. An off line matching process is performed to establish links between feature library entries and image locations. A detailed description of the off line and on line processes may be found in [2] 3. THE FEATURE LIBRARY STRUCTURE ORGANIZATION The feature library permits us to narrow the ....
Agouris P., A. Stefanidis & J. Carswell "Intelligent Retrieval of Digital Images from Large Geospatial Databases", International Archives of Photogrammetry and Remote Sensing, Vol. XXXII, Part 3/1, pp. 515-522, 1998, Columbus, OH.
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