Using domain knowledge in low-level visual processing to interpret handwritten music: An experiment

摘要

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.