Optical Music Recognition Bibliography

(Ichiro Fujinaga October 2000)

Anonymous. 1994. Musitek, Midiscan. Keyboard 20 (3): 136.

Akiyama, T., and N. Hagita. 1990. Automated entry system for printed documents. Pattern Recognition 23 (11): 1141-54.

Alphonce, B., B. Pennycook, I. Fujinaga, and N. Boisvert. 1988. Optical music recognition: A progress report. Proceedings of the Small Computers in the Arts: 8-12.

Andronico, A., and A. Ciampa. 1982. On automatic pattern recognition and acquisition of printed music. Proceedings of the International Computer Music Conference: 245-78.

Anstice, J., T. Bell, A. Cockburn, and M. Setchell. 1996. The design of a pen-based musical input system. Proceedings Sixth Australian Conference on Computer-Human Interaction: 260-7.

Aoyama, H., and A. Tojo. 1982. Automatic recognition of music score (in Japanese). Electronic Image Conference Journal 11 (5): 427-35.

Aoyama, H., and A. Tojo. 1982. Automatic recognition of printed music (in Japanese). Institute of Electronics and Communications Engineers of Japan (IECE) TG PREL82-5: 33-40.

Armand, J. P. 1993. Musical score recognition: A hierarchical and recursive approach. Proceedings of the Second International Conference on Document Analysis and Recognition (Cat. No.93TH0578-5): 906-9.

Bacon, R. A., and N. P. Carter. 1988. Recognising music automatically. Physics Bulletin 39: 265.

Bainbridge, D. 1991. Preliminary experiments in musical score recognition. B.Eng. Thesis, Department of Computer Science, University of Edinburgh, The Kings Buildings, Mayfield Road, Edinburgh, GB.

Bainbridge, D. 1994. Optical music recognition: Progress report 1: Department of Computer Science, University of Canterbury.

Bainbridge, D. 1994. A complete optical music recognition system: Looking to the future.

Bainbridge, D. 1995. Optical music recognition: Progress report 2: Department of Computer Science, University of Canterbury.

Bainbridge, D. 1996. Optical music recognition: A generalised approach. Paper read at Second New Zealand Computer Science Graduate Conference.

Bainbridge, D. 1997. Extensible optical music recognition. Ph.D. Thesis, University of Canterbury, Christchurch, NZ.

Bainbridge, D., and T. Bell. 1996. An extensible optical music recognition system. Aust. Comput. Sci. Commun. (Australia), Australian Computer Science Communications 18 (1): 308-17.

Bainbridge, D., and T. C. Bell. 1997. Dealing with superimposed objects in optical music recognition. Sixth International Conference on Image Processing and its Applications (Conf. Publ. No.443) 2: 756-60.

Bainbridge, D., and N. Carter. 1997. Automatic reading of music notation. In Handbook of Character Recognition and Document Image Analysis, ed. H. Bunke and P. Wang, 583-603.: World Scientific.

Bainbridge, D., and S. Inglis. 1998. Musical image compression. Proceedings DCC '98 Data Compression Conference (Cat. No.98TB100225): 209-18.

Bainbridge, D., C. G. Nevill-Manning, I. H. Witten, L. A. Smith, and R. J. McNab. 1999. Towards a digital library of popular music. ACM Conference on Digital Libraries: 161-9.

Bainbridge, D., and K. Wijaya. 1999. Bulk processing of optically scanned music. Seventh International Conference on Image Processing and Its Applications (Conf. Publ. No.465): 474-8.

Baumann, S. 1995. A simplified attributed graph grammar for high-level music recognition. Proceedings of the Third International Conference on Document Analysis and Recognition 2: 1080-3.

Baumann, S., and A. Dengel. 1992. Transforming printed piano music into MIDI. Proceedings of International Workshop on Structural and Syntactic Pattern Recognition: 363-72.

Beran, T. 1997. Rozpoznavani notoveho zapisu (In Czech). Prague, Czech Republic: Czech Technical University.

Beran, T. 1999. Rozpoznavani notoveho zapisu (In Czech). Prague, Czech Republic: Czech Technical University.

Beran, T., and T. Macek. 1999. Recognition of printed music score. Machine Learning and Data Mining in Pattern Recognition. First International Workshop, MLDM'99. Proceedings. (Lecture Notes in Artificial Intelligence Vol.1715): 174-9.

Blostein, D., and H. S. Baird. 1992. A critical survey of music image analysis. In Structured Document Image Analysis, ed. H. S. Baird, H. Bunke and K. Yamamoto, 405-34. Berlin: Springer-Verlag.

Blostein, D., and N. P. Carter. 1992. Recognition of Music Notation: SSPR '90 Working Group Report. In Structured Document Image Analysis, ed. H. S. Baird, H. Bunke and K. Yamamoto, 573-4. Berlin: Springer Verlag.

Blostein, D., and L. Haken. 1990. Template matching for rhythmic analysis of music keyboard input. Proceedings of 10th International Conference on Pattern Recognition: 767-70.

Blostein, D., and L. Haken. 1991. Justification of printed music. Communications of the ACM: 88-91.

Blostein, D., and L. Haken. 1999. Using diagram generation software to improve diagram recognition: A case study of music notation. IEEE Transactions on Pattern Analysis and Machine Intelligence 21 (11): 1121-36.

Bulis, A., R. Almog, M. Gerner, and U. Shimony. 1992. Computerized recognition of hand-written musical notes. Proceedings of the International Computer Music Conference: 110-2.

Capitaine, T., E. M. Mouaddib, H. Trannois, and A. Lebrun. 1995. Automatic recognition of musical scores. ACCV '95. Second Asian Conference on Computer Vision. Proceedings 1: 422-4.

Carter, N. P. 1989. Automatic recognition of printed music in the context of electronic publishing. Ph.D., University of Surrey.

Carter, N. P. 1992. A new edition of Walton's Façade using automatic score recognition. Proceedings of International Workshop on Structural and Syntactic Pattern Recognition: 352-62.

Carter, N. P. 1992. Segmentation and preliminary recognition of madrigals notated in white mensural notation. Machine Vision and Applications 5 (3): 223-30.

Carter, N. P. 1993. A generalized approach to automatic recognition of music scores: Department of Music, Stanford University.

Carter, N. P. 1994. Conversion of the Haydn symphonies into electronic form using automatic score recognition: a pilot study. Proceedings of SPIE 2181: 279-90.

Carter, N. P. 1994. Music score recognition: Problems and prospects. Computing in Musicology 9: 152-8.

Carter, N. P., and R. A. Bacon. 1990. Automatic recognition of music notation. Proceedings of the International Association for Pattern Recognition Workshop on Syntactic and Structural Pattern Recognition: 482.

Carter, N. P., and R. A. Bacon. 1992. Automatic recognition of printed music. In Structured Document Image Analysis, ed. H. S. Baird, H. Bunke and K. Yamamoto, 456-65. Berlin: Springer-Verlag.

Carter, N. P., R. A. Bacon, and T. Messenger. 1988. The acquisition, representation and reconstruction of printed music by computer: A review. Computers and the Humanities 22 (2): 117-36.

Cho, K. J., and K. E. Cho. 1996. Recognition of piano score using skeletal lines and run-length information. Journal of KISS(C) (Computing Practices) 2 (4): 461-73.

Choi, J. 1991. Optical recognition of the printed musical score. M.S. Thesis, Electrical Engineering and Computer Science, University of Illinois at Chicago.

Choudhury, G. S., C. Requardt, I. Fujinaga, T. DiLauro, E. W. Brown, J. W. Warner, and B. Harrington. 2000. Digital workflow management: the Lester S. Levy digitized collection of sheet music.

Clarke, A., M. Brown, and M. Thorne. 1990. Problems to be faced by developers of computer based automatic music recognisers. Proceedings of the International Computer Music Conference: 345-7.

Clarke, A. T., B. M. Brown, and M. P. Thorne. 1988. Inexpensive optical character recognition of music notation: A new alternative for publishers. Proceedings of the Computers in Music Research Conference: 84-7.

Clarke, A. T., B. M. Brown, and M. P. Thorne. 1988. Using a micro to automate data acquisition in music publishing. Microprocessing and Microprogramming 24: 549-54.

Clarke, A. T., B. M. Brown, and M. P. Thorne. 1989. Coping with some really rotten problems in automatic music recognition. Microprocess. Microprogr. (Netherlands), Microprocessing & Microprogramming 27 (1-5): 547-50.

Clarke, A. T., B. M. Brown, and M. P. Thorne. 1993. Recognising musical text. Proceedings of the SPIE 2064: 222-33.

Coüasnon, B. 1996. Formalisation grammaticale de la connaissance a priori pour l'analyse de documents : Application aux partitions d'orchestre. Reconnaissance des formes et intelligence artificielle: 465-74.

Coüasnon, B. 1996. Segmentation et reconnaissance de documents guidées par la connaissance a priori : application aux partitions musicales. Thèse de doctorat, Université de Rennes.

Coüasnon, B., and J. Camillerapp. 1994. Using grammars to segment and recognize music scores. International Association for Pattern Recognition Workshop on Document Analysis Systems: 15-27.

Coüasnon, B., and J. Camillerapp. 1995. A way to separate knowledge from program in structured document analysis: Application to optical music recognition. International Conference on Document Analysis and Recognition: 1092-7.

Coüasnon, B., P. Brisset, and I. Stephan. 1995. Using logic programming languages for optical music recognition. International Conference on the Practical Application of Prolog: 115-34.

Coüasnon, B., and B. Rétif. 1995. Using a grammar for a reliable full score recognition system. International Computer Music Conference: 187-94.

d'Andecy, V. P., J. Camillerapp, and I. Leplumey. 1994. Kalman filtering for segment detection: application to music scores analysis. Proceedings of the 12th IAPR International Conference on Pattern Recognition (Cat. No.94CH3440-5) 1: 301-5.

d'Andecy, V. P., J. Camillerapp, and I. Leplumey. 1994. Détecteur robuste de segments-Application à l'analyse de partitions musicales. Actes 9 ème Congrés AFCET Reconnaissance des Formes et Intelligence Artificielle.

Di Riso, D. 1992. Lettura automatica di partiture musicali. Masters thesis, Università di Salerno, Italy.

Diener, G. R. 1990. Modeling music notation: A three-dimensional approach. Ph.D: Thesis, Stanford University.

Distasi, R., and e. al. 1993. Automatic system for reading scores. Proceedings of the 8th Scandinavian Conference on Image Analysis: 1307-10.

Distasi, R., M. Nappi, and S. Vitulano. 1993. An automatic system for reading musical scores. Proceedings of the 8th Scandinavian Conference on Image Analysis: 1307-10 vol.2.

Fahmy, H. 1991. A graph-grammar approach to high-level music recognition. M. Sc. Thesis, Department of Computing and Information Science, Queen's University, Kingston, ON, Canada.

Fahmy, H., and D. Blostein. 1991. A graph grammar for high-level recognition of music notation. Proceedings of First International Conference on Document Analysis 1: 70-8.

Fahmy, H., and D. Blostein. 1992. Graph grammar processing of uncertain data. Proceedings of International Workshop on Structural and Syntactic Pattern Recognition: 373-82.

Fahmy, H., and D. Blostein. 1992. Graph grammar processing of uncertain data. In Advances in Structural and Syntactic Pattern Recognition, ed. H. Bunke, 373-84.: World Scientific.

Fahmy, H., and D. Blostein. 1993. A graph grammar programming style for recognition of music notation. Machine Vision and Applications 6: 83-99.

Fahmy, H., and D. Blostein. 1994. A graph-rewriting approach to discrete relaxation: Application to music recognition. Proceedings of the SPIE 2181: 291-302.

Fahmy, H., and D. Blostein. 1998. A graph-rewriting paradigm for discrete relaxation: Application to sheet-music recognition. International Journal of Pattern Recognition and Artificial Intelligence 12 (6): 763-99.

Ferrand, M., and A. Cardoso. 1998. Scheduling to reduce uncertainty in syntactical music structures. Advances in Artificial Intelligence. 14th Brazilian Symposium on Artificial Intelligence, SBIA'98. Proceedings: 249-58.

Ferrand, M., J. A. Leite, and A. Cardoso. 1999. Improving optical music recognition by means of abductive constraint logic programming. Progress in Artificial Intelligence. 9th Portuguese Conference on Artificial Intelligence, EPIA'99. Proceedings (Lecture Notes in Artificial Intelligence Vol.1695): 342-56.

Ferrand, M., J. A. Leite, and A. Cardoso. 1999. Hypothetical reasoning: An application to optical music recognition. Proceedings. of the APPIA-GULP-PRODE'99 Joint Conference on Declarative Programming: 367-81.

Fischer, K. N. 1978. Computer recognition of engraved music. M.S. Thesis, University of Tennessee.

Fletcher, L. A., and R. Kasturi. 1988. A robust algorithm for text string separation from mixed text/graphics images. IEEE Transactions on Pattern Analysis and Machine Intelligence 10 (6): 910-8.

Fluhr, C., and J. Abouassly. 1989. Music pattern recognition. Paper read at Proceedings of a workshop held in Toulouse, September 1988, EEC Concerted Action on "Technology and Blindness", at Toulouse.

Fotinea, S.-E., G. Giakoupis, A. Liveris, S. Bakamidis, and G. Carayannis. 2000. An optical notation recognition system for printed music based on template matching and high level reasoning. Paper read at The 6th Recherche d'Informations Assistée par Ordinateur, at Paris.

Fujimoto, Y. a. o. 1985. The keyboard playing robot WABOT-2. In Bulletin of Science and Engineering Research Laboratory.

Fujinaga, I. 1988. Optical music recognition using projections. M.A: Thesis.

Fujinaga, I. 1992. An optical music recognition system that learns. Enabling Technologies for High-Bandwidth Applications SPIE 1785: 210-17.

Fujinaga, I. 1993. Optical music recognition system which learns. Proc. SPIE - Int. Soc. Opt. Eng. (USA), Proceedings of the SPIE - The International Society for Optical Engineering 1785: 210-17.

Fujinaga, I. 1997. Adaptive optical music recognition. Abstract of the International Musicological Society Meeting. London, UK. 77.

Fujinaga, I. 1996. Exemplar-based learning in adaptive optical music recognition system. Proceedings of the International Computer Music Conference: 55-6.

Fujinaga, I., B. Alphonce, G. Diener, and B. Pennycook. 1992. Optical music recognition on NeXT workstation. Paper presented at the Second International Conference on Music Perception and Cognition.

Fujinaga, I., B. Alphonce, and B. Pennycook. 1989. Issues in the design of an optical music recognition system. Proceedings of the International Computer Music Conference: 113-6.

Fujinaga, I., B. Alphonce, and B. Pennycook. 1992. Interactive optical music recognition. Proceedings of the International Computer Music Conference: 117-20.

Fujinaga, I., B. Alphonce, B. Pennycook, and N. Boisvert. 1989. Optical recognition of music notation by computer. Computers in Music Research 1: 161-4.

Fujinaga, I., B. Alphonce, B. Pennycook, and K. Hogan. 1991. Optical music recognition: Progress report. Proceedings of the International Computer Music Conference: 66-73.

Fujinaga, I., B. Pennycook, and B. Alphonce. 1989. Computer recognition of musical notation. Proceedings of the First International Conference on Music Perception and Cognition: 87-90.

Fujinaga, I., B. Pennycook, and B. Alphonce. 1991. The optical music recognition project. Computers in Music Research 3: 139-42.

Geggus, K. M., and E. C. Botha. 1993. A model-based approach to sheet music recognition. Elektron 10 (1): 25-9.

Glass, S. 1989. Optical music recognition. Undergraduate project report, University of Canterbury, Canterbury, New Zealand.

Goolsby, T. W. 1994. Eye movement in music reading: Effects of reading ability, notational complexity, and encounters. Music Perception 12 (1): 77-96.

Goolsby, T. W. 1994. Profiles of processing: Eye movements during sightreading. Music Perception 12 (1): 97-123.

Hachimura, K., and Y. Ohno. 1987. A system for the representation of human body movements from dance scores. Pattern Recognition Letters 5: 1-9.

Hewlett, W. B., and E. Selfridge-Field. 1990. Optical recognition of musical data. Computing in Musicology: A Directory of Research: 36-45.

Homenda, W. 1995. Optical pattern recognition for printed music notation. Proc. SPIE - Int. Soc. Opt. Eng. (USA), Proceedings of the SPIE - The International Society for Optical Engineering 2490: 230-9.

Homenda, W. 1996. Automatic recognition of printed music and its conversion into playable music data. Control and Cybernetics 25 (2): 353-67.

Hori, T., S. Wada, T. Howzan, S. Y. D. E. Kung, and W. Bastiaan Kleijn. 1999. Automatic music score recognition/play system based on decision based neural network. 1999 IEEE Third Workshop on Multimedia Signal Processing (Cat. No.99TH8451): 183-4.

Inokuchi, S. 1981. Musical database. Journal of the Institute of Electronics and Communication Engineers of Japan 64 (5): 466-8.

Inokuchi, S., and H. Katayose. 1990. Computer and music. Journal of the Institute of Electronics, Information and Communication Engineers 73 (9): 965-7.

Itagaki, T. S., S. Hashimoto, M. Isogai, and S. Ohteru. 1990. Automatic recognition on some different types of musical notation. Proceedings of the International Association for Pattern Recognition Workshop on Syntactic and Structural Pattern Recognition: 488 ff.

Itagaki, T. S., S. Hashimoto, M. Isogai, and S. Ohteru. 1992. Automatic recognition of several types of musical notation. In Structured Document Image Analysis, ed. H. S. Baird, H. Bunke and K. Yamamoto, 466-76. Berlin: Springer-Verlag.

Kassler, M. 1970. An essay toward specification of a music-reading machine. In Musicology and the computer, ed. B. S. Brook, B.: City University of New York Press.

Kassler, M. 1972. Optical character recognition of printed music: A review of two dissertations. Perspectives of New Music 11: 250-4.

Katayose, H., T. Fukuoka, K. Takami, and S. Inokuchi. 1990. Expression extraction in virtuoso music performances. Proceedings of the Tenth International Conference on Pattern Recognition: 780-4.

Katayose, H., and S. Inokuchi. 1989. The kansei music system. Computer Music Journal 13 (4): 72-7.

Katayose, H., H. Kato, M. Imai, and S. Inokuchi. 1989. An approach to an artificial music expert. Proceedings of the International Computer Music Conference: 139-46.

Kato, H., and S. Inokuchi. 1988. Automatic recognition of printed piano music based on bar unit processing (in Japanese). Transactions of I. E. C. E. J71-D (5): 894-901.

Kato, H., and S. Inokuchi. 1990. The recognition system for printed piano music using musical knowledge and constraints. Proceedings of the International Association for Pattern Recognition Workshop on Syntactic and Structural Pattern Recognition: 231-48.

Kato, H., and S. Inokuchi. 1992. A recognition system for printed piano music using musical knowledge and constraints. In Structured Document Image Analysis, ed. H. S. Baird, H. Bunke and K. Yamamoto, 435-55. Berlin: Springer-Verlag.

Kim, W. J., M. J. Chung, and Z. Bien. 1987. Recognition system for a printed music score. Proceedings of TENCON 87: 1987 IEEE Region 10 Conference 'Computers and Communications Technology Toward 2000 2: 573-7.

Kinoshita, T., H. Muraoka, and H. Tanaka. 1998. Note recognition using statistical information of musical note transitions. Journal of the Acoustical Society of Japan 54 (3): 190-8.

Kobayakawa, T. 1993. Auto music score recognition system. Proceedings SPIE: Character Recognition Technologies 1906: 112-23.

Kopec, G. E., P. A. Chou, and D. A. Maltz. 1995. Markov source model for printed music decoding. Proc. SPIE - Int. Soc. Opt. Eng. (USA), Proceedings of the SPIE - The International Society for Optical Engineering 2422: 115-25.

Lee, M. W., and J. S. Choi. 1985. The recognition of printed music score and performance using computer vision system (in Korean and English translation). Journal of the Korean Institute of Electronic Engineers 22 (5): 429-35.

Lee, S., and J. Shin. 1994. Recognition of music scores using neural networks. Journal of the Korea Information Science Society 21 (7): 1358-66.

Leite, J. A., and M. Ferrand. 1994. RIEM: Reconhecimento e Interpretação de Escrita Musical (in Portuguese). B.Sc. Dissertation, Dept. de Engenharia Electrotécnica, Faculdade de Ciências e Tecnologia, Universidade de Coimbra.

Leite, J. A., M. Ferrand, and A. Cardoso. 1998. RIEM: A system for recognition and interpretation of music writing (in Portuguese): Dept. Engenharia Informatica, Faculdade de Ciências e Tecnologia, Universidade de Coimbra.

Leplumey, I., and J. Camillerapp. 1991. Comparison of region labelling for musical scores. Proceedings of First International Conference on Document Analysis 2: 674-82.

Leplumey, I., and J. Camillerapp. 1991. Coopération entre la segmentation des régions blanches et des régions noires pour l'analyse de partitions musicales. AFCET, 8e Congress Reconnaissance des Formes et Intelligence Artificielle 3: 1045-52.

Leplumey, I., J. Camillerapp, and G. Lorette. 1993. A robust detector for music staves. Proceedings o the International Conference on Document Analysis and Recognition: 902-5.

Maenaka, K., and Y. Tadokoro. 1983. Recognition of music using the special image-input-device enabling to scan the staff of music as the supporting system for the blind (in Japanese). Prl83-60: 37-45.

Mahoney, J. V. 1982. Automatic analysis of musical score images. B.S. Thesis, Massachusetts Institute of Technology.

Martin, N. G. 1987. Towards computer recognition of the printed musical score. B.Sc. Project report, Thames Polytechnic.

Martin, P. 1989. Reconnaissance de partitions musicales et réseaux de neurones: une étude. Actes 7 iéme Congrés AFCET de Reconnaissance des Formes et Intelligence Artificielle: 217-26.

Martin, P. 1992. Réseaux de neurones artificiels : Application à la reconnaissance optique de partitions musicales. Ph.D. Thesis, IMAG, Grenoble, France.

Martin, P., and C. Bellissant. 1991. Neural networks at different levels of musical score image analysis system. Proceedings of 7th Scandinavian Conference on Image Analysis: 1102-9.

Martin, P., and C. Bellissant. 1991. Low-level analysis of music drawing images. Proceedings of the International Conference on Document Analysis and Recognition: 417-25.

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Matsushima, T. 1992. Computerized Japanese traditional music processing system. Proceedings of the International Computer Music Conference: 121-4.

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Matsushima, T., I. Sonomoto, T. Harada, K. Kanamori, and S. Ohteru. 1985. Automated high speed recognition of printed music (WABOT-2 vision system). Proceedings of the 1985 International Conference on Advanced Robotics: 477-82.

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McGee, W. F. 1994. MusicReader: An interactive optical music recognition system. Computing in Musicology 9: 146-51.

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Miyao, H., and Y. Nakano. 1995. Head and stem extraction from printed music scores using a neural network approach. Proceedings of the Third International Conference on Document Analysis and Recognition 2: 1074-9.

Miyao, H., and Y. Nakano. 1996. Note symbol extraction for printed piano scores using neural networks. IEICE Transactions on Information and Systems E79-D (5): 548-54.

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Miyao, H. T., T. Ejima, M. Miyahara, and K. Kotani. 1992. Symbol recognition for printed piano scores based on the musical knowledge (in Japanese). Transactions of the Institute of Electronics, Information and Communication Engineers D-II J75D-II (11): 1848-55.

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Modayur, B. R., V. Ramesh, R. M. Haralick, and L. G. Shapiro. 1993. MUSER: a prototype musical recognition system using mathematical morphology. Machine Vision and Applications 6 (2-3): 140-50.

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