We describe the design of document analysis procedures to separate mathematics from ordinary text on a scanned page of mixed material. It is easy to observe that the accuracy of commercial OCR programs is helped by separating mixed material into two (or more) streams, with conventional non-math text handled by the usual OCR text-based-heuristics analysis. The second stream, consisting of material judged to be mathematics, can be fed to a specialized recognizer. If that fails to decode it, it can be passed on to yet a third stream including diagrams, logos, or other miscellaneous material, perhaps including halftones. We explore the extent to which this separation can be automated in the context of scanning archival material for a digital library project including mathematical and scientific journal pages.