On the use of textural features for writer identification in old handwritten music scores

Fornés, Alicia; Lladós, Josep; Sánchez, Gemma; Bunke, Horst (2009). On the use of textural features for writer identification in old handwritten music scores. In: 10th International Conference on Document Analysis and Recognition ICDAR 2009 (pp. 996-1000). Washington, DC: IEEE Computer Society 10.1109/ICDAR.2009.100

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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.

Item Type: Conference or Workshop Item (Paper)
Division/Institute: 08 Faculty of Science > Institute of Computer Science (INF)
UniBE Contributor: Fornés-Bisquerra, Alicia and Bunke, Horst
Subjects: 000 Computer science, knowledge & systems
500 Science > 510 Mathematics
ISSN: 1520-5363
ISBN: 978-0-7695-3725-2
Publisher: IEEE Computer Society
Language: English
Submitter: Factscience Import
Date Deposited: 04 Oct 2013 15:22
Last Modified: 08 Dec 2014 21:44
Publisher DOI: 10.1109/ICDAR.2009.100
BORIS DOI: 10.7892/boris.37089
URI: http://boris.unibe.ch/id/eprint/37089 (FactScience: 206724)

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