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Alicia Fornes, & Josep Llados. (2010). A Symbol-dependent Writer Identifcation Approach in Old Handwritten Music Scores. In 12th International Conference on Frontiers in Handwriting Recognition (pp. 634–639).
Abstract: Writer identification consists in determining the writer of a piece of handwriting from a set of writers. In this paper we introduce a symbol-dependent approach for identifying the writer of old music scores, which is based on two symbol recognition methods. The main idea is to use the Blurred Shape Model descriptor and a DTW-based method for detecting, recognizing and describing the music clefs and notes. The proposed approach has been evaluated in a database of old music scores, achieving very high writer identification rates.
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Alicia Fornes, Josep Llados, Gemma Sanchez, & Dimosthenis Karatzas. (2010). Rotation Invariant Hand-Drawn Symbol Recognition based on a Dynamic Time Warping Model. IJDAR - International Journal on Document Analysis and Recognition, 13(3), 229–241.
Abstract: 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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Alicia Fornes, Josep Llados, Gemma Sanchez, & Horst Bunke. (2009). On the use of textural features for writer identification in old handwritten music scores. In 10th International Conference on Document Analysis and Recognition (pp. 996–1000).
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.
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Alicia Fornes, Josep Llados, Gemma Sanchez, & Horst Bunke. (2009). Symbol-independent writer identification in old handwritten music scores. In In proceedings of 8th IAPR International Workshop on Graphics Recognition (186–197). Springer Berlin Heidelberg.
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Alicia Fornes, Josep Llados, Gemma Sanchez, & Horst Bunke. (2008). Writer Identification in Old Handwritten Music Scores. In Proceedings of the 8th International Workshop on Document Analysis Systems, (347–353).
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Alicia Fornes, Josep Llados, & Gemma Sanchez. (2008). Old Handwritten Musical Symbol Classification by a Dynamic TimeWrapping Based Method. In J.M. Ogier J. L. W. Liu (Ed.), Graphics Recognition: Recent Advances and New Opportunities (Vol. 5046, 52–60). LNCS.
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Alicia Fornes, Josep Llados, & Gemma Sanchez. (2007). Old Handwritten Musical Symbol Classification by a Dynamic Time Warping Based Method. In Seventh IAPR International Workshop on Graphics Recognition (26–27).
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Alicia Fornes, Josep Llados, & Gemma Sanchez. (2006). Primitive Segmentation in Old Handwritten Music Scores. In Graphics Recognition: Ten Years Review and Future Perspectives, W. Liu, J. Llados (Eds.), LNCS 3926: 288–299.
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Alicia Fornes, Josep Llados, & Gemma Sanchez. (2005). Staff and graphical primitive segmentation in old handwritten music scores.
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Alicia Fornes, Josep Llados, & Gemma Sanchez. (2005). Primitive Segmentation in Old Handwritten Music Scores.
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Miquel Ferrer, Dimosthenis Karatzas, Ernest Valveny, & Horst Bunke. (2009). A Recursive Embedding Approach to Median Graph Computation. In 7th IAPR – TC–15 Workshop on Graph–Based Representations in Pattern Recognition (Vol. 5534, 113–123). LNCS. Springer Berlin Heidelberg.
Abstract: The median graph has been shown to be a good choice to infer a representative of a set of graphs. It has been successfully applied to graph-based classification and clustering. Nevertheless, its computation is extremely complex. Several approaches have been presented up to now based on different strategies. In this paper we present a new approximate recursive algorithm for median graph computation based on graph embedding into vector spaces. Preliminary experiments on three databases show that this new approach is able to obtain better medians than the previous existing approaches.
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Miquel Ferrer, & Ernest Valveny. (2007). Combination of OCR Engines for Page Segmentation based on Performance Evaluation. In 9th International Conference on Document Analysis and Recognition (Vol. 2, 784–788).
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Mathieu Nicolas Delalandre, Ernest Valveny, Tony Pridmore, & Dimosthenis Karatzas. (2010). Generation of Synthetic Documents for Performance Evaluation of Symbol Recognition & Spotting Systems. IJDAR - International Journal on Document Analysis and Recognition, 13(3), 187–207.
Abstract: This paper deals with the topic of performance evaluation of symbol recognition & spotting systems. We propose here a new approach to the generation of synthetic graphics documents containing non-isolated symbols in a real context. This approach is based on the definition of a set of constraints that permit us to place the symbols on a pre-defined background according to the properties of a particular domain (architecture, electronics, engineering, etc.). In this way, we can obtain a large amount of images resembling real documents by simply defining the set of constraints and providing a few pre-defined backgrounds. As documents are synthetically generated, the groundtruth (the location and the label of every symbol) becomes automatically available. We have applied this approach to the generation of a large database of architectural drawings and electronic diagrams, which shows the flexibility of the system. Performance evaluation experiments of a symbol localization system show that our approach permits to generate documents with different features that are reflected in variation of localization results.
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Mathieu Nicolas Delalandre, Ernest Valveny, & Josep Llados. (2008). Performance Evaluation of Symbol Recognition and Spotting Systems. In Proceedings of the 8th International Workshop on Document Analysis Systems, (497–505).
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Mathieu Nicolas Delalandre, Ernest Valveny, & Josep Llados. (2008). Performance Evaluation of Symbol Recognition and Spotting Systems: An Overview.
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