Mammogram analysis is needed to identify specific descriptions of regions of interest (ROI). One way to achieve
this is to develop features of the image which can be used to classify the image data. The greatest difficulty lies in finding
some property of the image from which such features may be extracted. Texture is a commonly used feature in the analysis and interpretation of images. Texture is characterized by a set of statistical properties of pixel intensities. Texture features are calculated using a variety of statistical, structural and spectral techniques including co-occurrence matrices, fractal dimensions and multiresolution techniques such as wavelet and curvelet. Multiresolution allows a preservation of an image according to a certain levels of resolution. It allows as well a zooming in and out on the underlying texture structure. Therefore, the texture extraction is not affected by the size of the pixel neighborhood.