alceufc/sfta

Implementation of the SFTA algorithm for texture feature extraction.

Extract texture features from an image using the SFTA (Segmentation-based Fractal Texture Analysis) algorithm. To extract features, use the sfta(I, nt) function, where I corresponds to the input grayscale image and nt is a parameter that defines the size of the feature vector.
The features are returned as a 1 by (6*nt -3) vector.
Example:

I = imread('coins.png');
D = sfta(I, 4)

Brief description of the SFTA algorithm:

The extraction algorithm consists in decomposing the input image into a set of binary images from which the fractal dimensions of the resulting regions are computed in order to describe segmented texture patterns.

Publication where the SFTA algorithm is described:

Costa, A. F., G. E. Humpire-Mamani, A. J. M. Traina. 2012. "An Efficient Algorithm for Fractal Analysis of Textures." In SIBGRAPI 2012 (XXV Conference on Graphics, Patterns and Images), 39-46, Ouro Preto, Brazil.

Here I show how SFTA can be used to classify textures:

http://www.alceufc.com/classification,/computer/vision,/descriptor,/feature/extraction,/image/processing,/matlab,/texture/descriptor/2013/09/02/texture-classification.html