PT Unknown AU Albert Gordo Marçal Rusiñol Dimosthenis Karatzas Andrew Bagdanov TI Document Classification and Page Stream Segmentation for Digital Mailroom Applications BT 12th International Conference on Document Analysis and Recognition PY 2013 BP 621 EP 625 DI 10.1109/ICDAR.2013.128 AB In this paper we present a method for the segmentation of continuous page streams into multipage documents and the simultaneous classification of the resulting documents. We first present an approach to combine the multiple pages of a document into a single feature vector that represents the whole document. Despite its simplicity and low computational cost, the proposed representation yields results comparable to more complex methods in multipage document classification tasks. We then exploit this representation in the context of page stream segmentation. The most plausible segmentation of a page stream into a sequence of multipage documents is obtained by optimizing a statistical model that represents the probability of each segmented multipage document belonging to a particular class. Experimental results are reported on a large sample of real administrative multipage documents. ER