Publication: Sistema de reconocimiento de partituras musicales
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2009-06
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2009
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Abstract
El objetivo principal del sistema reconocedor de partituras musicales desarrollado en este proyecto, es la elaboración de un programa capaz de analizar partituras, ya sean manuscritas o no manuscritas, y digitalizar sus elementos, pudiendo tratar dichos datos y representarlos en distintos formatos. Para ello, se hará uso de un clasificador simple basado en el algoritmo k-NN (k-Nearest Neighbor) que, junto a una base de datos de símbolos, será capaz de asignar a cada elemento una clase concreta dentro de las mencionadas en dicha base de datos. Por lo tanto, la implementación de este sistema diseña y elabora un sistema tradicional de reconocimiento óptico de música que destaca por la rapidez de ejecución y los resultados obtenidos para ambas clases de partituras (manuscritas o no manuscritas), en contraposición a la gran mayoría de los sistemas OMR desarrollados que centran su atención en los símbolos no manuscritos.-----------------------------------------------------------------------------
The main goal of the musical scores recognition system developed in this project is to make a program capable of analizing scores, wheter or not handwritten musical scores, and digitalize their symbols, for be able to treat these data and represent them in various formats. To do this, it will use a simple classifier based on k-NN algorithm (k-Nearest Neighbor) which, with a symbols database, it will be able to assign to each element a class of this database. Therefore, the implementation of this system designed and developed a tradicional system of optical music recognition that highlights the speed of execution and the results for both kinds of scores (handwritten musical scores or not handwritten musical scores), in contrast to most developed OMR systems that focus their work in the recognition of not handwritten musical scores.
The main goal of the musical scores recognition system developed in this project is to make a program capable of analizing scores, wheter or not handwritten musical scores, and digitalize their symbols, for be able to treat these data and represent them in various formats. To do this, it will use a simple classifier based on k-NN algorithm (k-Nearest Neighbor) which, with a symbols database, it will be able to assign to each element a class of this database. Therefore, the implementation of this system designed and developed a tradicional system of optical music recognition that highlights the speed of execution and the results for both kinds of scores (handwritten musical scores or not handwritten musical scores), in contrast to most developed OMR systems that focus their work in the recognition of not handwritten musical scores.
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Partituras musicales, Digitalización, Reconocimiento óptico de música, OMR