An Automatic Method to Determine the Degree of Flocculence of a Galaxy

Computer Science – Learning

Scientific paper

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Scientific paper

We propose a new method to determine the flocculence of a galaxy image. Flocculence is characterized by a texture feature computed using a bank of Gabor filters. These filters, inspired by the human visual system, uniformly cover the spatial-frequency domain. Texture features are obtained by extracting statistics from sub-windows in the filtered images. Flocculent regions are then detected using a machine learning approach. First results are presented on the EFIGI dataset.

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