Music Score Reader Based on Image Processing and Neural Network

dc.contributor.authorNilangani, K.K.N.
dc.date.accessioned2019-04-11T07:50:09Z
dc.date.available2019-04-11T07:50:09Z
dc.date.issued2013
dc.description.abstractThere is a large population of music lovers who have strong interest in singing and playing. In general, music notation required performers to have a great deal of contextual knowledge about performing styles. Music notation is the written expression of music notes and rhythms on paper using symbols. Hence normal people cannot read music score which is the most common way of recording music. This project has targeted to help those people who do not know how to read music score to learn music easily with the system. Also music editor could make corrections of old editions. Because of that music score reader is the best solution for all those problems. After uploading the music score notation image in to system it reads the image and give the output of the image that represented letters. For develop this system, Microsoft visual studio 2010 is used. C# was the developing language. By go through in the several processors of the image finally get the music notation represented letters. First converted the image form the uploaded type to bitmap. By using EmguCV and Afoge.NET framework project was developed up to get the output. For recognizing the head of music note it identified the staff lines and then image divided in to several regions in horizontally and vertically. Then the location of head is identified for the represent of the character. This research showed that the Digital Image Processing techniques, able to identify the music notation that given in an image.en_US
dc.identifier.otherUWU/CST/09/0026
dc.identifier.urihttp://www.erepo.lib.uwu.ac.lk/bitstream/handle/123456789/274/UWULD%20CST%2009%200026-27032019154204.pdf?sequence=1&isAllowed=y
dc.language.isoenen_US
dc.publisherUva Wellassa University of Sri Lankaen_US
dc.subjectComputer Science and Technologyen_US
dc.titleMusic Score Reader Based on Image Processing and Neural Networken_US
dc.typeThesisen_US
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