A system for selecting sentences from an imaged document for presentation as part of a document summary is presented. The extracts are identified without the use of optical character recognition. The sentences are selected based on a set of discrete features characterizing the words within a sentence and the location of the sentence within the imaged document. Each sentence is scored based on the values of the discrete features using a statistically based classifier. The imaged document is processed to identify the word locations, the reading order of words, and the location of sentence and paragraph boundaries in the text. The words are grouped into equivalence classes to mimic the terms in a text document. A sample extract for a technical document is shown, and evaluation against a set of abstracts created by a professional abstracting company is given. These results are compared with text-based abstracts.