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Proceedings Paper

Texture classification using ART-based neural networks and fractals
Author(s): Dimitrios Charalampidis; Takis Kasparis; Michael Georgiopoulos
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Paper Abstract

In this paper texture classification is studied based on the fractal dimension (FD) of filtered versions of the image and the Fuzzy ART Map neural network (FAMNN). FD is used because it has shown good tolerance to some image transformations. We implemented a variation of the testing phase of Fuzzy ARTMAP that exhibited superior performance than the standard Fuzzy ARTMAP and the 1-nearest neighbor (1-NN) in the presence of noise. The performance of the above techniques is tested with respect to segmentation of images that include more than one texture.

Paper Details

Date Published: 17 July 1998
PDF: 11 pages
Proc. SPIE 3374, Signal Processing, Sensor Fusion, and Target Recognition VII, (17 July 1998); doi: 10.1117/12.327099
Show Author Affiliations
Dimitrios Charalampidis, Univ. of Central Florida (United States)
Takis Kasparis, Univ. of Central Florida (United States)
Michael Georgiopoulos, Univ. of Central Florida (United States)


Published in SPIE Proceedings Vol. 3374:
Signal Processing, Sensor Fusion, and Target Recognition VII
Ivan Kadar, Editor(s)

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