Scale invariant texture classification with mathematical morphology

One of the most interesting fields of research in Digital Image Processing tr the segmentation of an image into different objects. The detection of re gions with different textures Is one of the techniques used to achieve this objective. These techniques differ among each other In the texture paramet ers used and the way to obtain them. In this work the characteristics assoc iated to each region will be obtained from the application of the Size Crit eria of Successive Openings. This technique of the Mathematical Morphology shows how the image interacts with different structuring elements. Taking p arameters from the images, we obtain sire distribution functions associated to each region. We demonstrate that We can obtain invariant characteristic s under change of scale using the statistical moments of the associated nor malised density functions. These characteristics can be used as patterns fo r a further classification.