Optical music recognition: Architecture and algorithms

Interactive Multimedia Music Technologies

Volumn , Issue , 2007, Pages 80-110

  Bellini, Pierfrancesco ^a   Bruno, Ivan ^a   Nesi, Paolo ^a  

^a UNIVERSITY OF FLORENCE   (Italy)

Author keywords

[No Author keywords available]

Indexed keywords

EID: 84884483940     PISSN: None     EISSN: None     Source Type: Book    
DOI: 10.4018/978-1-59904-150-6.ch005     Document Type: Chapter

References (36)

1. Bainbridge, D., & Bell, T.(1996). An extensible optical music recognition system. Australian Computer Science Communications, 18(1), 308-317.
2. Bainbridge, D., & Bell, T. (2003). A music notation construction engine for optical music recognition. Software-Practice & Experience, 33(2), 173-200.
3. Bellini, P., Bruno, I., & Nesi, P. (2001b). Optical music sheet segmentation. In Proc. of the 1st International Conference of Web Delivering of Music WEDELMUSIC2001, (pp.183-190), Florence: IEEE Press.
4. Bellini, P., Bruno, I., & Nesi, P. (2004). An off-line optical music sheet recognition. In S. E. George (Ed.), Visual perception of music notation: Online and off-line recognition. Hershey, PA: Idea Group Inc.
5. Bellini, P., Bruno, I., & Nesi, P. Assessing optical music recognition tools. Computer Music Journal, 31(1), 68-93.
6. Bellini, P., & Nesi, P. (2001a). WEDELMUSIC format: An XML music notation format for emerging applications. In Proc. of the First International Conference on WEB Delivering of Music (pp. 79-86). Retrieved from http://www.wedelmusic.org
7. Blostein, D., & Baird, H. S. (1992). A critical survey of music image analysis. In H. S. Baird, H. Bunke, & K. Yamamoto (Eds.), Structured document image analysis (pp. 405-434). Berlin: Springer-Verlag.
8. Bruno, I. (2003). Music score image analysis: Methods and tools for automatic recognition and indexing. PhD Thesis, Department of Systems and Informatics, University of Florence, Italy.
9. Byrd, D. (2001). Music-notation searching and digital libraries. InProceedings of 2001 Joint Conference on Digital Libraries (JCDL 2001) (pp. 239-246).
10. Byrd, D. (2006). OMR (Optical Music Recognition) Systems. School of Informatics and School of Music, Indiana University. Retrieved from http://mypage.iu.edu/~donbyrd/OMRSystemsTable.html
11. Carter, N. P. (1989). Automatic recognition of printed music in the context of electronic publishing. Doctoral dissertation, University of Surrey, UK.
12. Carter, N. P. (1994). Music score recognition: Problems and prospects. Computing in Musicology, 9, 152-158.
13. Cooper, D., Ng, K. C., & Boyle, R. D. (1997). MIDI extensions for musical notation: Expressive MIDI. In E. Selfridge-Field (Ed.), Beyond MIDI - The handbook of musical codes (pp. 402-447). London: The MIT Press.
14. Coüasnon, B., & Camillerapp, J.(1995). A way to separate knowledge from program in structured document analysis: Application to optical music recognition. InInternational Conference on Document Analysis and Recognition (pp. 1092-1097).
15. Fujinaga, I. (1988). Optical music recognition using projections. M.A: Thesis.
16. Fujinaga, I. (1996). Adaptive optical music recognition. Ph.D. Dissertation, Music, McGIll University.
17. Good, M. (2001). MusicXML for notation and analysis. In W. B. Hewlett and E. Selfridge-Field, The virtual score (pp. 113-124). Cambridge, MA: MIT Press.
18. Heussenstamm, G. (1987). The Norton manual of music notation. W.W. Norton & Company, Inc.
19. IMUTUS. (2004). Interactive Music Tuition System. Retrieved from http://www.exodus.gr/imutus
20. Kanai, J., Rice, S. V., Nartker, T. A., & Nagy, G. (1995). Automated evaluation of OCR zoning. IEEE Transactions on Pattern Analysis and Machine Intelligence, 17(1), 86-90.
21. Kato, H., & S. Inokuchi. (1990). The recognition system for printed piano music using musical knowledge and constraints.In Proceedings of the International Association for Pattern Recognition Workshop on Syntactic and Structural Pattern Recognition (pp. 231-48).
22. Kobayakawa, T. (1993). Auto music score recognition system.In Proceedings SPIE: Character Recognition Technologies 1906 (pp. 112-23).
23. McPherson, J. R. (2002). Introducing feedback into an optical music recognition system. Third International Conference on Music Information Retrieval, Paris.
24. Miyao, H., & Haralick, R. M. (2000). Format of ground truth data used in the evaluation of the results of an optical music recognition system. InIAPR Workshop on Document Analysis Systems (pp. 497-506).
25. Modayur, B. R. (1996). Music score recognition - a selective attention approach using mathematical morphology. Seattle, University of Washington, Electrical Engineering Department.
26. Musitek (2002). SmartScore. Retrieved from http://www.musitek.com/
27. Ng, K. C., & Boyle, R. D. (1994). Reconstruction of music scores from primitive Sub-segmentation. School of Computer Studies, University of Leeds.
28. Ng, K. C., & Boyle, R. D. (1996). Recognition and reconstruction of primitives in music scores. Image and Vision Computing, 14(1), 39-46.
29. Prerau, D. S. (1970). Computer pattern recognition of standard engraved music notation. Ph.D. Dissertation, Massachusetts Institute of Technology.
30. Ross, T. (1970). The art of music engraving and processing. Miami: Hansen Books.
31. Roth, M. (1994). An approach to recognition of printed music. Diploma thesis, Department of Computer Science, Swiss Federal Institute of Technology, Zurich, Switzerland.
32. Rumelhart, D. E., Hinton, G. E., & McClelland, J. L. (1986). A general framework for parallel distributed processing. In D. E. Rumelhart, J. L. McClelland, and the PDP Research Group (Eds.), Parallel distributed processing: Explorations in the microstructure of cognition, vol. 1: Foundations. Cambridge, MA: MIT Press
33. Selfridge-Field E., (1997). Beyond MIDI - The handbook of musical codes. London: The MIT Press.
34. Selfridge-Field, E. (1993). Optical recognition of musical notation: A survey of current work. Computing in Musicology, 9, 109-145.
35. Tojo, A., & Aoyama, H. (1982). Automatic recognition of music score. InProceedings of 6th International Conference on Pattern Recognition, 1223.
36. Visiv. (2005). Sharpeye. Retrieved from http://www.visiv.co.uk/