Generalized Fractional Brownian Texture Dataset

Published: 23 November 2020| Version 1 | DOI: 10.17632/7rjyfn5bgg.1
Contributor:
Abdourrahmane Mahamane Atto

Description

A texture associated with a Generalized Fractional Brownian Field (GFBF) is generated from convolution operations over modulated fractional Brownian fields. Related challenges are: 1) counting the number of interacting modulated fractional Brownian fields and 2) locating the corresponding modulation frequencies, see references given below. Dataset structure: one root folder including 4 subfolders, any folder being associated with the number of modulated fractional Brownian interactions. Any TIF file (2 channels: modulus and phase of complex data) included in the subfolders has 2 channels: one for the modulus and the other for the phase of the complex GFBF texture.

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Categories

Artificial Intelligence, Computer Vision, Machine Learning, Information Classification, Fractal Dimension Model, Numerical Method in Complex Analysis, Texture Analysis, Complex Mixture

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