Optical Music Recognitoin of Early Typographic Prints using Hidden Markov Models
نویسنده
چکیده
Music printed with movable type (typographic music) from the 16th and 17th centuries contains specific graphic features. In this paper, we present a technique and associated experiments for performing optical music recognition on such music prints using Hidden Markov Models (HMM). Our original approach avoids the difficult and unreliable removal of staff lines usually required before processing. The modeling of symbols on the staff is based on low-level simple features. We show that, using our technique, these features are robust enough to obtain good recognition rates even with poor quality images scanned from microfilm of originals. The music content retrieved by the optical recognition process can be put to significant use in, for example, the creation of searchable digital music libraries.
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تاریخ انتشار 2006