Abstract: The identification and quantification of microtextured regions in orientation datasets is provided through the use of microstructure informatics based on n-point correlation functions, dimensionality reduction techniques, and a computer algebra system. Orientation information is extracted for materials and processing is performed on the orientation information along with other ancillary data that accompanies each piece of orientation information and a hybrid descriptor of orientation is formed. Representative descriptors are identified such that regions of microtexture are classified. This classification is mapped back onto the real space of the sample and a local clustering is done to identify continuous regions of microtexture. These labeled continuous regions of microtexture then provide a method for segmentation of the orientation data into their respective macrozones.