  This paper aims to compare between four different types of feature extraction
approaches in terms of texture segmentation. The feature extraction methods
that were used for segmentation are Gabor filters (GF), Gaussian Markov random
fields (GMRF), run-length matrix (RLM) and co-occurrence matrix (GLCM). It was
shown that the GF performed best in terms of quality of segmentation while the
GLCM localises the texture boundaries better as compared to the other methods.
