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Proceedings Paper

Hierarchical approaches to analysis of natural textures
Author(s): Vadim R. Lutsiv; Igor A. Malyshev; Tatiana A. Novikova
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Paper Abstract

The surface textures of natural objects often have the visible fractal-like properties. A similar pattern of texture could be found looking at the forests in the aerial photographs or at the trees in the outdoor scenes when the image spatial resolution was changed. Or the texture patterns are different at different spatial resolution levels in the aerial photographs of villages. It creates the difficulties in image segmentation and object recognition because the levels of spatial resolution necessary to get the homogeneously and correctly labeled texture regions differ for different types of landscape. E.g. if the spatial resolution was sufficient for distinguishing between the textures of agricultural fields, water, and asphalt, the texture labeled areas of forest or suburbs are hardly fragmented, because the texture peculiarities corresponding to two stable levels of texture spatial resolution will be visible in this case. A hierarchical texture analysis could solve this problem, and we did it in two different ways: we performed the texture segmentation simultaneously for several levels of image spatial resolution, or we subjected the texture labeled image of highest spatial resolution to a recurring texture segmentation using the texture cells of larger sizes. The both approaches turned out to be rather fruitful for the aerial photographs as well as for the outdoor images. They generalize and support the hierarchical image analysis technique presented in another our paper. Some of the methods applied were borrowed from the living vision systems.

Paper Details

Date Published: 21 September 2004
PDF: 11 pages
Proc. SPIE 5426, Automatic Target Recognition XIV, (21 September 2004); doi: 10.1117/12.543378
Show Author Affiliations
Vadim R. Lutsiv, Vavilov State Optical Institute (Russia)
Igor A. Malyshev, Vavilov State Optical Institute (Russia)
Tatiana A. Novikova, Vavilov State Optical Institute (Russia)

Published in SPIE Proceedings Vol. 5426:
Automatic Target Recognition XIV
Firooz A. Sadjadi, Editor(s)

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