We explore the use of image analysis techniques for the classification of archaeological ceramic materials according to one aspect of their petrographic characterization. Specifically, we study the use of Gabor filter-based texture features, Laws' texture measures, and Haralick's texture measures for automated classification of a set of archaeological ceramic samples from two different Egyptian source materials: Marl clay and Nile clay. The motivation behind this work is the desire to pioneer the introduction of fully automated methods for pattern classification into the domain of archaeological science, where these can be extremely useful. The texture features are all extracted in a completely automated fashion and the classification is performed via a simple classification algorithm, the k-NN classifier. An accuracy of nearly 74% was obtained with base on the Laws' texture features.