Proceedings of 3rd ICDAR, pp.1074-1079 (1995)
Abstract
In an automatic music score recognition system, it is very important to
extract heads and stems of notes, since these symbols are most ubiquitous in a
score and musically important. The purpose of our system is to present an
accurate and speedy extraction of note heads (except the whole notes and stems
according to the following procedures.
(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 as faster as the manual work.
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First Written Before June 17, 1998
Transplanted to KSU Before May 17, 2003
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Last Update April 11, 2007
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