1. A method for classifying forms, said method comprising: receiving by at least one processor an image representing a form of an unknown document type, the image including line-art; receiving by the at least one processor a plurality of template models corresponding to a plurality of different document types; selecting by the at least one processor a subset of the plurality of template models as candidate template models, the candidate template models including line-art junctions best matching line-art junctions of the received image; and, selecting by the at least one processor one of the candidate template models as a best candidate template model, the best candidate template model including horizontal and vertical lines best matching horizontal and vertical lines of the received image, respectively, aligned to the best candidate template model.
1. A method for classifying forms, said method comprising: receiving by at least one processor an image representing a form of an unknown document type, the image including line-art; receiving by the at least one processor a plurality of template models corresponding to a plurality of different document types; selecting by the at least one processor a subset of the plurality of template models as candidate template models, the candidate template models including line-art junctions best matching line-art junctions of the received image; and, selecting by the at least one processor one of the candidate template models as a best candidate template model, the best candidate template model including horizontal and vertical lines best matching horizontal and vertical lines of the received image, respectively, aligned to the best candidate template model. 8. The method according to claim 1 , further including: removing background form information of the received image using the best candidate template model to create a background-subtracted image; and, extracting data from the background-subtracted image using zonal optical character recognition.