(1) We extract all regions which are considered as candidates of stems or heads.
(2) To identify heads from the candidates, we use a three-layer neural network.
(3) The weights for the network are learned by the back propagation method.
In the learning the network learns the spatial constraints between the heads and
surroundings rather than the shapes of heads.
(4) After the learning process us completed we use this network to
identify a number of test head candidates.
(5) The stem candidates touching the detected heads are extracted as true stems.
As an experimental result, we obtained high recognition rates of 99.0% and 99.2% for
stems and note heads, respectively. It took time from about 40 to 100 seconds to do for
a printed piano score on A4 sheet using a workstation. Therefore, our system can analyze
it 10 times or as faster as the manual work.
[Music Score Recognition] [Research Themes of Prof. Nakano.]
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First Written Before June 17, 1998
Transplanted to KSU Before June 18, 2003
Transplanted to So-net April 22, 2007
Last Update April 22, 2007
© Yasuaki Nakano 1998-2007