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Proceedings Paper

Selective attention filtering for land-use digitized map image classification
Author(s): Rafael Santos; Takeshi Ohashi; Takaichi Yoshida; Toshiaki Ejima
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Paper Abstract

Map images are complex documents generated from several layers of information overlapped and printed on paper, and usually the only available information is the digitized image of the map. The recovery of the original layers of the map for analysis of its components independently would be useful but would require several steps to be completed. One first step could separate the image in conceptual layers by using basic spectral and spatial properties, giving layers corresponding to basic features in the amp image, which would serve as input for more sophisticated algorithms which could give as results more detailed information and so on, until a complete high-level description of the map information is obtainable. Extraction of the conceptual map layers is often a complex task since the pixels that correspond to the categories in a map image are spectrally and spatially mixed with the pixels of other classes. This paper presents the selective attention filter (SAF) which is able to filter out pixels that are not relevant to the information being extracted or enhance pixels of categories of interest. The SAF filter is robust in presence of noise and result of classification with images filtered with it are quantitatively better than results obtained with other commonly used filters.

Paper Details

Date Published: 1 April 1998
PDF: 11 pages
Proc. SPIE 3305, Document Recognition V, (1 April 1998); doi: 10.1117/12.304643
Show Author Affiliations
Rafael Santos, Univ. do Vale do Paraiba (Brazil) and Kyushu Institute of Technology (Japan) (Brazil)
Takeshi Ohashi, Kyushu Institute of Technology (Japan)
Takaichi Yoshida, Kyushu Institute of Technology (Japan)
Toshiaki Ejima, Kyushu Institute of Technology (Japan)

Published in SPIE Proceedings Vol. 3305:
Document Recognition V
Daniel P. Lopresti; Jiangying Zhou, Editor(s)

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