Learning-free text-image alignment for medieval manuscripts
Résumé
—In this paper, we describe a new approach for
text-image alignment of middle-age documents. The method is
dedicated to word-to-word alignment in a segmentation-free and
learning-free way. The best word-to-word matching lies on an
adapted editing cost between signatures extracted on Unicode
characters and on the images. The results are evaluated on the
“Queste del saint Graal” (13th c.) by palaeographers through an
intuitive validation interface that also offers a very fast interactive
correction process. The gain of time resulting from the absence
of learning stage offers the opportunity to pay more attention to
the integration of different specificities and variations in middle-
age handwritten documents (presence of typical abbreviations,
allographs. . . )