Abstract
The digital music stand is proposed as a minimal-processing optical music recognition implementation, where music score (MS) presentation is realized without prior alignment, noise, or staff line removal. After each MS page is segmented into systems, staves, measures, and candidate music symbols, music symbol recognition is accomplished via probabilistic neural networks: Only the key music symbols (namely clefs, global accidentals, time signatures) of the MS are identified, while the remaining music symbols are generally classified. Subsequently, satisfactory quality of on-screen MS viewing is accomplished via the concatenation and/or substitution of appropriately selected parts and isolated music symbols of the original MS. In this piece of research, the processing stages leading to on-screen MS presentation are detailed.
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