In most of the automatic face classification applications, images should be captured in natural environments, where partial occlusions or high local changes in the illumination are frequent. For this reason, face classification tasks in uncontrolled environment are still nowadays unsolved problems, given that the loss of information caused by these artifacts can easily mislead any classifier. We present in this paper a system to extract robust face features that can be applied to encode information from any zone of the face and that can be used for different face classification problems. To test this method we include the results obtained in different gender classification experiments, considering controlled and uncontrolled environments and extracting face features from internal and external face zones. The obtained rates show, on the one hand, that we can obtain significant information applying the presented feature extraction scheme and, on the other hand, that the external face zone can contribute useful information for classification purposes.