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Turning handwritten scores into engraved scores consumes a significant portion of music publishing companies' budgets. Pattern recognition is the major bottleneck holding up automation of this process. Human beings who know music can easily read a handwritten score, but without musical knowledge, even people cannot correctly perceive the markings in a handwritten score. This paper reports an experiment in which knowledge of music, a highly structured domain is applied to extract primitive musical features. This experiment shows that if the domain of image processing is well defined, significant improvements in low-level segmentations can be achieved (17 Refs.) recognition; computerised picture processing; expert systems; music
Keywords: handwritten music recognition; character recognition; knowledge based feature extraction; expert systems; primitive musical feature extraction; computerised pattern recognition; domain knowledge; low-level visual processing; image processing; low-level segmentations equipment); C6170 (Expert systems); C7820 (Humanities)
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