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Author  |
Alicia Fornes; Josep Llados; Gemma Sanchez |
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Title |
Primitive Segmentation in Old Handwritten Music Scores |
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Miscellaneous |
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2005 |
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6th IAPR International Workshop on Graphics Recognition (GREC 2005) |
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Hong Kong, Hong Kong SAR (China) |
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DAG @ dag @ FLS2005a |
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584 |
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Author |
Alicia Fornes; Josep Llados; Gemma Sanchez |
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Title |
Staff and graphical primitive segmentation in old handwritten music scores |
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2005 |
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DAG @ dag @ FLS2005b |
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585 |
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Alicia Fornes; Josep Llados; Gemma Sanchez |
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Title |
Primitive Segmentation in Old Handwritten Music Scores |
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Book Chapter |
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2006 |
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Graphics Recognition: Ten Years Review and Future Perspectives, W. Liu, J. Llados (Eds.), LNCS 3926: 288–299 |
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DAG @ dag @ FLS2006 |
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697 |
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Alicia Fornes; Josep Llados; Gemma Sanchez |
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Title |
Old Handwritten Musical Symbol Classification by a Dynamic Time Warping Based Method |
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2007 |
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Seventh IAPR International Workshop on Graphics Recognition |
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26–27 |
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Curitiba (Brazil) |
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GREC |
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DAG @ dag @ FLS2007 |
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887 |
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Author |
Alicia Fornes; Josep Llados; Gemma Sanchez |
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Title |
Old Handwritten Musical Symbol Classification by a Dynamic TimeWrapping Based Method |
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2008 |
Publication |
Graphics Recognition: Recent Advances and New Opportunities |
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5046 |
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52–60 |
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W. Liu, J. Llados, J.M. Ogier |
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DAG |
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DAG @ dag @ FLS2008a |
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990 |
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Author |
Alicia Fornes; Josep Llados; Gemma Sanchez; Dimosthenis Karatzas |
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Title |
Rotation Invariant Hand-Drawn Symbol Recognition based on a Dynamic Time Warping Model |
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Journal Article |
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2010 |
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International Journal on Document Analysis and Recognition |
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IJDAR |
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13 |
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3 |
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229–241 |
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One of the major difficulties of handwriting symbol recognition is the high variability among symbols because of the different writer styles. In this paper, we introduce a robust approach for describing and recognizing hand-drawn symbols tolerant to these writer style differences. This method, which is invariant to scale and rotation, is based on the dynamic time warping (DTW) algorithm. The symbols are described by vector sequences, a variation of the DTW distance is used for computing the matching distance, and K-Nearest Neighbor is used to classify them. Our approach has been evaluated in two benchmarking scenarios consisting of hand-drawn symbols. Compared with state-of-the-art methods for symbol recognition, our method shows higher tolerance to the irregular deformations induced by hand-drawn strokes. |
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Springer-Verlag |
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1433-2833 |
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DAG; IF 2009: 1,213 |
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DAG @ dag @ FLS2010a |
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1288 |
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Author |
Alicia Fornes; Josep Llados; Gemma Sanchez; Horst Bunke |
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Title |
Writer Identification in Old Handwritten Music Scores |
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Conference Article |
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2008 |
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Proceedings of the 8th International Workshop on Document Analysis Systems, |
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347–353 |
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Nara (Japan) |
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DAS |
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DAG |
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DAG @ dag @ FLS2008b |
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1078 |
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Author |
Alicia Fornes; Josep Llados; Gemma Sanchez; Horst Bunke |
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Title |
Symbol-independent writer identification in old handwritten music scores |
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Conference Article |
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2009 |
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In proceedings of 8th IAPR International Workshop on Graphics Recognition |
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186–197 |
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La Rochelle, France |
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Springer Berlin Heidelberg |
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0302-9743 |
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978-3-642-13727-3 |
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GREC |
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DAG @ dag @ FLS2009a |
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1222 |
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Alicia Fornes; Josep Llados; Gemma Sanchez; Horst Bunke |
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Title |
On the use of textural features for writer identification in old handwritten music scores |
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Conference Article |
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2009 |
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10th International Conference on Document Analysis and Recognition |
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996 - 1000 |
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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. |
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Barcelona |
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1520-5363 |
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978-1-4244-4500-4 |
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ICDAR |
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DAG @ dag @ FLS2009b |
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1223 |
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Alicia Fornes; Josep Llados; Gemma Sanchez; Horst Bunke |
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Title |
Writer Identification in Old Handwritten Music Scores |
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2012 |
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Pattern Recognition and Signal Processing in Archaeometry: Mathematical and Computational Solutions for Archaeology |
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27-63 |
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The aim of writer identification is 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. Even though an important amount of compositions contains handwritten text in the music scores, the aim of our work is to use only music notation to determine the author. The steps of the system proposed are the following. First of all, the music sheet is preprocessed and normalized for obtaining a single binarized music line, without the staff lines. Afterwards, 100 features are extracted for every music line, which are subsequently used in a k-NN classifier that compares every feature vector with prototypes stored in a database. By applying feature selection and extraction methods on the original feature set, the performance is increased. The proposed method has been tested on a database of old music scores from the 17th to 19th centuries, achieving a recognition rate of about 95%. |
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IGI-Global |
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Copnstantin Papaodysseus |
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Admin @ si @ FLS2012 |
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1828 |
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