Fractal descriptors based on the probability dimension: A texture analysis and classification approach

• A texture descriptor is proposed based on the fractal descriptors concept.
• Fractal dimension estimation is performed by the probability (Voss) method.
• The descriptor are obtained applying a multi-scale transform into the fractal curve.
• The method is compared and outperforms fractal and non-fractal texture stat-of-art methods.

In this work, we propose a novel technique for obtaining descriptors of gray-level texture images. The descriptors are provided by applying a multiscale transform to the fractal dimension of the image estimated through the probability (Voss) method. The effectiveness of the descriptors is verified in a classification task using benchmark over texture datasets. The results obtained demonstrate the efficiency of the proposed method as a tool for the description and discrimination of texture images.