Texture image segmentation based on the elements of Gray Level Aura Matrices

We present a method for texture image segmentation based on Gray Level Aura Matrices (GLAMs). The GLAMs allow describing the relationship between the target pixel and its neighboring pixels located in neighborhood structure defined by a structuring element. Their elements are directly used in this paper instead of Haralick features in order to characterize each pixel of the image. The pixels having the same features are then gathered into classes using the Fuzzy C-means algorithm. Experiments results on synthetic and real images show the relevance of the elements of GLAMs in the segmentation of images with different textures.