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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Fornes, A. Llados, J. Sanchez, G. Bunke, H. |
| Copyright Year | 2009 |
| Abstract | 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. |
| Starting Page | 996 |
| Ending Page | 1000 |
| File Size | 1627714 |
| Page Count | 5 |
| File Format | |
| ISBN | 9781424445004 |
| ISSN | 15205363 |
| DOI | 10.1109/ICDAR.2009.100 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2009-07-26 |
| Publisher Place | Spain |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Feature extraction Text analysis Image generation Handwriting recognition Computer science Data mining Image recognition Computer vision Mathematics Gabor filters historical documents writer identification graphics recognition optical music recognition |
| Content Type | Text |
| Resource Type | Article |
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