Selective attention filtering for land-use digitized map image classification

Rafael Santos; Takeshi Ohashi; Takaichi Yoshida; Toshiaki Ejima

doi:10.1117/12.304643

1 April 1998 Selective attention filtering for land-use digitized map image classification

Rafael Santos, Takeshi Ohashi, Takaichi Yoshida, Toshiaki Ejima

Proceedings Volume 3305, Document Recognition V; (1998) https://doi.org/10.1117/12.304643
Event: Photonics West '98 Electronic Imaging, 1998, San Jose, CA, United States

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.

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Rafael Santos, Takeshi Ohashi, Takaichi Yoshida, and Toshiaki Ejima "Selective attention filtering for land-use digitized map image classification", Proc. SPIE 3305, Document Recognition V, (1 April 1998); https://doi.org/10.1117/12.304643

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KEYWORDS

Image filtering

Image classification

Digital filtering

Optical filters

RGB color model

Vegetation

Feature extraction

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