A bag of notes approach to writer identification in old handwritten musical scores
DAS '10 Proceedings of the 9th IAPR International Workshop on Document Analysis Systems
Music score binarization based on domain knowledge
IbPRIA'11 Proceedings of the 5th Iberian conference on Pattern recognition and image analysis
onNote: playing printed music scores as a musical instrument
Proceedings of the 24th annual ACM symposium on User interface software and technology
Writer identification in handwritten musical scores with bags of notes
Pattern Recognition
Offline text-independent writer identification using codebook and efficient code extraction methods
Image and Vision Computing
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Writer identification consists in determining the writer of a piece of handwriting from a set of writers. In this paper we present a system for writer identification in old handwritten music scores which uses only music notation to determine the author. The steps of the proposed system are the following. First of all, the music sheet is preprocessed for obtaining a music score without the staff lines. Afterwards, four different methods for generating texture images from music symbols are applied. Every approach uses a different spatial variation when combining the music symbols to generate the textures. Finally, Gabor filters and Grey-scale Co-ocurrence matrices are used to obtain the features. The classification is performed using a k-NN classifier based on Euclidean distance. The proposed method has been tested on a database of old music scores from the 17th to 19th centuries, achieving encouraging identification rates.