Texture classification using ART-based neural networks and fractals

Dimitrios Charalampidis; Takis Kasparis; Michael Georgiopoulos

doi:10.1117/12.327099

17 July 1998 Texture classification using ART-based neural networks and fractals

Dimitrios Charalampidis, Takis Kasparis, Michael Georgiopoulos

Proceedings Volume 3374, Signal Processing, Sensor Fusion, and Target Recognition VII; (1998) https://doi.org/10.1117/12.327099
Event: Aerospace/Defense Sensing and Controls, 1998, Orlando, FL, United States

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.

Citation Download Citation

Dimitrios Charalampidis, Takis Kasparis, and Michael Georgiopoulos "Texture classification using ART-based neural networks and fractals", Proc. SPIE 3374, Signal Processing, Sensor Fusion, and Target Recognition VII, (17 July 1998); https://doi.org/10.1117/12.327099

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