1. A method, implemented by a music symbol recognition apparatus for recognising music symbols based on handwritten music notations, said method comprising: detecting handwritten music notations; pre-segmenting said handwritten music notations into a plurality of elementary ink segments; grouping the elementary ink segments into graphical objects based on spatial relationships between elementary ink segments, wherein each elementary ink segment belongs to one or more of said graphical objects; determining for each graphical object at least one music symbol candidate, in association with an assigned symbol cost, the symbol cost representing the probability of said graphical object belonging to a predetermined class of said music symbol candidate, said determining being based on graphical features extracted from said graphical object; and parsing the music symbol candidates, wherein said parsing comprises: forming one or more graphs by applying at least one of a predetermined set of grammar rules to said music symbol candidates, wherein each graph comprises at least one non-terminal node corresponding to a grammar rule applied to a set of at least one descendant node, and wherein each descendant node is either a terminal node corresponding to a music symbol candidate or a non-terminal-node corresponding to a grammar rule applied to at least one other descendant node; associating each grammar rule applied to at least two descendant nodes with a spatial cost representative of the pertinence of said applied grammar rule based on the spatial relationships between the graphical objects of said at least two descendant nodes; and selecting at least one said graph as the most representative graph of the handwritten music notations based on the symbol costs associated with each music symbol candidate and the spatial costs associated with each applied grammar rule.
1. A method, implemented by a music symbol recognition apparatus for recognising music symbols based on handwritten music notations, said method comprising: detecting handwritten music notations; pre-segmenting said handwritten music notations into a plurality of elementary ink segments; grouping the elementary ink segments into graphical objects based on spatial relationships between elementary ink segments, wherein each elementary ink segment belongs to one or more of said graphical objects; determining for each graphical object at least one music symbol candidate, in association with an assigned symbol cost, the symbol cost representing the probability of said graphical object belonging to a predetermined class of said music symbol candidate, said determining being based on graphical features extracted from said graphical object; and parsing the music symbol candidates, wherein said parsing comprises: forming one or more graphs by applying at least one of a predetermined set of grammar rules to said music symbol candidates, wherein each graph comprises at least one non-terminal node corresponding to a grammar rule applied to a set of at least one descendant node, and wherein each descendant node is either a terminal node corresponding to a music symbol candidate or a non-terminal-node corresponding to a grammar rule applied to at least one other descendant node; associating each grammar rule applied to at least two descendant nodes with a spatial cost representative of the pertinence of said applied grammar rule based on the spatial relationships between the graphical objects of said at least two descendant nodes; and selecting at least one said graph as the most representative graph of the handwritten music notations based on the symbol costs associated with each music symbol candidate and the spatial costs associated with each applied grammar rule. 2. The method according to claim 1 , wherein forming one or more graphs comprises: attempting recursively to apply each of the set of grammar rules to said music symbol candidates.