A relatively new x-ray imaging technique, xerography, gives very detailed, high contrast images. It is particularly useful in detecting texture changes associated with early breast cancer. We describe a process of digitally scanning photographs of these xeromammograms. Normalization of the data representing the breast images is necessary to later classification; four methods were used for our study. The visual appearance of certain abnormal texture is described and used to motivate our statistical measures of texture. One group of measurements is derived from density value histograms; a second group depends on a density value co-occurrence matrix; a third group computes statistics from a gradient of the image; the last group analyzes the number of connected paths in the image. Nineteen features are collected from these measurements and are evaluated by using them to classify abnormal from normal tissue in a set of four test cases.