There is a large number of scanned historical documents
that need to be indexed for archival and retrieval purposes.
A visual word spotting scheme that would serve these purposes
is a challenging task even when the transcription of
the document image is available. We propose a framework
for mapping each word in the transcript to the associated
word image in the document. Coarse word mapping
based on document constraints is used for lexicon reduction.
Then, word mappings are refined using word recognition
results by a dynamic programming algorithm that finds
the best match while satisfying the constraints.