Optical Music Recognition as the Case of Imbalanced Pattern Recognition: A Study of Single Classifiers

OMR (Optical Music Recognition) is a technology for digital musical score image processing and recognition by computer, which has broad applications in the digital music library, contemporary music education, music theory, music automatic classification, music and audio sync dissemination and etc. This paper first has a brief description of OMR research and focuses on describing the research of Chinese OMR literature, it represents the research status and results in China, then the paper pointes out that the target of OMR research in China must tend to Chinese traditional musical score image processing and pattern recognition.

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Optical Music Recognition

Interactive Multimedia Music Technologies ◽

10.4018/978-1-59904-150-6.ch005 ◽

2011 ◽

pp. 80-110 ◽

Cited By ~ 6

Author(s):

Pierfrancesco Bellini ◽

Ivan Bruno ◽

Paolo Nesi

Keyword(s):

Image Processing ◽

Pattern Recognition ◽

Research And Development ◽

European Commission ◽

Image Understanding ◽

Development Project ◽

Music Notation ◽

Optical Music Recognition ◽

Digital World ◽

Music Recognition

Optical music recognition is a key problem for coding western music sheets in the digital world. This problem has been addressed in several manners obtaining suitable results only when simple music constructs are processed. To this end, several different strategies have been followed, to pass from the simple music sheet image to a complete and consistent representation of music notation symbols (symbolic music notation or representation). Typically, image processing, pattern recognition and symbolic reconstruction are the technologies that have to be considered and applied in several manners the architecture of the so called OMR (Optical Music Recognition) systems. In this chapter, the O3MR (Object Oriented Optical Music Recognition) system is presented. It allows producing from the image of a music sheet the symbolic representation and save it in XML format (WEDELMUSIC XML and MUSICXML). The algorithms used in this process are those of the image processing, image segmentation, neural network pattern recognition, and symbolic reconstruction and reasoning. Most of the solutions can be applied in other field of image understanding. The development of the O3MR solution with all its algorithms has been partially supported by the European Commission, in the IMUTUS Research and Development project, while the related music notation editor has been partially funded by the research and development WEDELMUSIC project of the European Commission. The paper also includes a methodology for the assessment of other OMR systems. The set of metrics proposed has been used to assess the quality of results produce by the O3MR with respect the best OMR on market.

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Optical Music Recognition: the Case Study of Pattern Recognition

Advances in Soft Computing - Computer Recognition Systems ◽

10.1007/3-540-32390-2_98 ◽

2008 ◽

pp. 835-842 ◽

Cited By ~ 16

Author(s):

Wladyslaw Homenda

Keyword(s):

Pattern Recognition ◽

Optical Music Recognition ◽

Music Recognition

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Optical Music Recognition as the Case of Imbalanced Pattern Recognition: A Study of Complex Classifiers

Advances in Intelligent Systems and Computing - Advances in Systems Science ◽

10.1007/978-3-319-01857-7_31 ◽

2014 ◽

pp. 325-335 ◽

Cited By ~ 1

Author(s):

Agnieszka Jastrzebska ◽

Wojciech Lesinski

Keyword(s):

Pattern Recognition ◽

Optical Music Recognition ◽

Music Recognition

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Pengantar dan Survey Tentang Optical Music Recognition

Jurnal ULTIMATICS ◽

10.31937/ti.v6i1.331 ◽

2014 ◽

Vol 6 (1) ◽

pp. 36-39

Author(s):

Kevin Purwito

Keyword(s):

Character Recognition ◽

Optical Character Recognition ◽

Optical Music Recognition ◽

Optical Character ◽

Digital Format ◽

Music Recognition ◽

Index Terms ◽

The Many ◽

Further Development ◽

Music Symbol

This paper describes about one of the many extension of Optical Character Recognition (OCR), that is Optical Music Recognition (OMR). OMR is used to recognize musical sheets into digital format, such as MIDI or MusicXML. There are many musical symbols that usually used in musical sheets and therefore needs to be recognized by OMR, such as staff; treble, bass, alto and tenor clef; sharp, flat and natural; beams, staccato, staccatissimo, dynamic, tenuto, marcato, stopped note, harmonic and fermata; notes; rests; ties and slurs; and also mordent and turn. OMR usually has four main processes, namely Preprocessing, Music Symbol Recognition, Musical Notation Reconstruction and Final Representation Construction. Each of those four main processes uses different methods and algorithms and each of those processes still needs further development and research. There are already many application that uses OMR to date, but none gives the perfect result. Therefore, besides the development and research for each OMR process, there is also a need to a development and research for combined recognizer, that combines the results from different OMR application to increase the final result’s accuracy. Index Terms—Music, optical character recognition, optical music recognition, musical symbol, image processing, combined recognizer

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