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First International Workshop on Document Image Analysis for Libraries (DIAL'04)
Text Alignment with Handwritten Documents
Palo Alto, California
January 23-January 24
ISBN: 0-7695-2088-X
E. Micah Kornfield, University of Massachusetts at Amherst
R. Manmatha, University of Massachusetts at Amherst
James Allan, University of Massachusetts at Amherst
Today?s digital libraries increasingly include not only printed text but also scanned handwritten pages and other multimedia material. There are, however, few tools available for manipulating handwritten pages. Here, we propose an algorithm based on dynamic time warping (DTW) for a word by word alignment of handwritten documents with their (ASCII) transcripts. We see at least three uses for such alignment algorithms. First, alignment algorithms allow us to produce displays (for example on the web) that allow a person to easily find their place in the manuscript when reading a transcript. Second, such alignment algorithms will allow us to produce large quantities of ground truth data for evaluating handwriting recognition algorithms. Third, such algorithms allow us to produce indices in a straightforward manner for handwriting material. We provide experimental results of our algorithm on a set of 70 pages of historical handwritten material - specifically the writings of George Washington. Our method achieves 74.5% accuracy on line by line alignment and 60.5% accuracy when aligning whole pages at time.
Citation:
E. Micah Kornfield, R. Manmatha, James Allan, "Text Alignment with Handwritten Documents," dial, pp.195, First International Workshop on Document Image Analysis for Libraries (DIAL'04), 2004
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