@article{Alphonce1988,
author = {Alphonce, B. and Pennycook, B. and Fujinaga, I. and Boisvert, N.},
title = {Optical music recognition: A progress report},
journal = {Proceedings of the Small Computers in the Arts},
year = {1988},
pages = {8--12}
}
@article{Aoyama1982,
author = {Aoyama, H. and Tojo, A.},
title = {Automatic recognition of music scores (in Japanese)},
journal = {Electronic Image Conference Journal},
year = {1982},
volume = {TG PREL82-5},
pages = {33--40}
}
@article{Aoyama1982a,
author = {Aoyama, H. and Tojo, A.},
title = {Automatic recognition of printed music (in Japanese)},
journal = {Institute of Electronics and Communications Engineers of Japan (IECE)},
year = {1982},
volume = {11},
number = {5},
pages = {427--35}
}
@techreport{Bainbridge1995,
author = {Bainbridge, D.},
title = {Optical music recognition: Progress report 2},
institution = {Department of Computer Science, University of Canterbury},
year = {1995}
}
@inproceedings{Bainbridge1996a,
author = {Bainbridge, D.},
title = {Optical music recognition: A generalised approach},
booktitle = {Second New Zealand Computer Science Graduate Conference},
year = {1996}
}
@phdthesis{Beran1997,
author = {Beran, T.},
title = {Rozpoznavani notoveho zapisu (In Czech)},
school = {Czech Technical University},
year = {1997},
address = {Prague, Czech Republic}
}
@inproceedings{Capitaine1995,
author = {Capitaine, T. and Mouaddib, E. and Trannois, H. and Lebrun, A.},
title = {Automatic recognition of musical scores},
booktitle = {Second Asian Conference on Computer Vision},
year = {1995},
volume = {1},
pages = {422--424},
abstract = {Optical music recognition is a complex problem because of the stave lines which link up the musical symbols. Thus, the standard approach of segmentation attempts to remove them, without cutting the symbols, by developing a complex algorithm or using them to operate on the zones they delimit. For the segmentation phase, some workers have tried considering a musical score as a set of line segments, but this approach is not appropriate to easy recognition. Our original approach to the segmentation problem is based on an exploitation of these lines and on the creation of virtual interlines according to the musical significance that they have. To limit the influence of the skew, line detection only appears at bar level. The same is true of the final recognition phase which can also deal with a local musical context local for each bar to render the identification. More accurate these lines and virtual interlines define the limits of 2*13 vertical projections (F and G clef) to detect the presence of musical information (patterns). These patterns are coded with 3 characters according to their forms and their relative height and width. A pattern position analysis combined with the score writing rules allow strings of chars matching 2 classes of musical symbols to be created (horizontal analysis to create slurs and vertical analysis for the others). These strings feed a syntactic analyzer for the final recognition according to their musical significance. The checking of the number of beats played in association with the tone of the bar and the identified alterations enables us to guarantee an optimal musical symbols recognition (5 Refs.) segmentation; pattern recognition},
keywords = {automatic recognition of musical scores; optical music recognition; stave lines; segmentation; virtual interlines; skew; line detection; pattern position analysis; optimal musical symbols recognition processing); C1250 (Pattern recognition); C5260B (Computer vision and image processing techniques); C6170 (Expert systems)}
}
@phdthesis{Carter1989,
author = {Carter, N. P.},
title = {Automatic recognition of printed music in the context of electronic publishing},
school = {University of Surrey},
year = {1989},
address = {Surrey, UK}
}
@inproceedings{Carter1990,
author = {Carter, N. P. and Bacon, R. A.},
title = {Automatic recognition of music notation},
year = {1990},
volume = {482},
journal = {International Association for Pattern Recognition Workshop on Syntactic and Structural Pattern Recognition}
}
@article{Carter1991,
author = {Carter, N.},
title = {Automatic Recognition and Related Topics: Guildford, University of Surrey},
journal = {Computing in Musicology},
year = {1991},
volume = {7},
pages = {109--111}
}
@article{Carter1993,
author = {Carter, N. P.},
title = {A generalized approach to automatic recognition of music scores},
journal = {Department of Music},
year = {1993},
volume = {STAN-M-87}
}
@article{Carter1994a,
author = {Carter, N. P.},
title = {Music score recognition: Problems and prospects},
journal = {Computing in Musicology},
year = {1994},
volume = {9},
pages = {152--158}
}
@article{Cho1996,
author = {Cho, K. J. and Cho, K. E.},
title = {Recognition of piano score using skeletal lines and run-length information},
journal = {Journal of KISS(C) (Computing Practices)},
year = {1996},
volume = {2},
number = {4},
pages = {461--473},
abstract = {The automatic recognition system for printed music would make practical the conversion of large quantities of printed music into computer-readable form. Works on automatic recognition of printed music have been started in the late 1960s and early 1970s. And some recognition systems for music notation have been developed in Japan and Europe. This work presents an overview of works undertaken in the field of manipulating printed music by computer, and proposes a new method to recognize each music symbol using skeletal lines and run-length information. And the system for automatic recognition of printed piano music using the new method has been developed and tested. The result reveals 98.5\% accuracy for music symbols. The system shows size-independent, noise immune, and rotation-independent properties (28 Refs.) recognition},
keywords = {piano score recognition; skeletal lines; run-length information; printed music; music notation; rotation-independent properties techniques); C7820 (Humanities computing)}
}
@phdthesis{Choi1991,
author = {Choi, J.},
title = {Optical recognition of the printed musical score},
school = {University of Illinois at Chicago},
year = {1991}
}
@article{Choudhury2006,
author = {Choudhury, G. and DiLauro, T. and Ferguson, R. and Droettboom, M. and Fujinaga, I.},
title = {Document Recognition for a Million Books},
journal = {D-Lib Magazine},
year = {2006},
volume = {12},
number = {3}
}
@article{Clarke1988,
author = {Clarke, A. T. and Brown, B. M. and Thorne, M. P.},
title = {Inexpensive optical character recognition of music notation: A new alternative for publishers},
journal = {Proceedings of the Computers in Music Research Conference},
year = {1988},
pages = {84--87},
doi = {10.1045/march2006-choudhury}
}
@article{Clarke1990,
author = {Clarke, A. and Brown, M. and Thorne, M.},
title = {Problems to be faced by developers of computer based automatic music recognisers},
journal = {Proceedings of the International Computer Music Conference},
year = {1990},
pages = {345--347},
abstract = {Several attempts have been made to implement a computer based automatic music recogniser over the last twenty years. However, for tasks such as music printing or compiling a musical database, no such system has yet become commercially available that would help enter the music into the computer. This paper describes problems that have been ignored by the existing research and which the authors have encountered during the development of a music recognition system. It is argued why solutions to these problems will have to be found before an optical character recognition scheme for music can become reliable enough to be regularly used (7 Refs.) management systems; music; optical character recognition; printing},
keywords = {data entry systems; reliability; development problems; computer based automatic music recognisers; music printing; musical database; optical character recognition equipment); C7820 (Humanities)}
}
@article{Coueasnon1991,
author = {Co{\"{u}}asnon, B.},
title = {R{\'{e}}seaux de neurones appliqu{\'{e}}s {\`{a}} la reconnaissance de partitions musicales},
journal = {Rapport de DEA},
year = {1991}
}
@article{Coueasnon1995c,
author = {Co{\"{u}}asnon, B. and R{\'{e}}tif, B.},
title = {Utilisation d'une grammaire dans la reconnaissance de partitions d'orchestre},
journal = {Deuxi{\'{e}}mes Journ{\'{e}}es d'Informatique Musicale},
year = {1995},
pages = {143--152}
}
@article{Coueasnon1996,
author = {Co{\"{u}}asnon, B.},
title = {Formalisation grammaticale de la connaissance a priori pour l'analyse de documents : Application aux partitions d'orchestre},
journal = {Reconnaissance des formes et intelligence artificielle},
year = {1996},
pages = {465--474}
}
@phdthesis{Coueasnon1996a,
author = {Co{\"{u}}asnon, B.},
title = {Segmentation et reconnaissance de documents guides par la connaissance a priori : application aux partitions musicales},
school = {Universit de Rennes},
year = {1996},
address = {Rennes, France},
abstract = {This thesis deals with Optical Document Recognition. In this domain, reliability is an important point: the user should not have to proofread the whole document.
Reliability can be obtained by first improving the quality of the recognition - mostly by solving segmentation problems - and, second, by having the system itself
detect badly recognized zones. To fullfill these objectives, one must use a priori knowledge to solve segmentations problems and to represent redundancy, thus
allowing error detection. We chose in this thesis to work on Optical Music Recognition for its structured knowledge and because it has many unsolved segmentation
problems (mainly linked to information density). For this kind of document strongly syntaxed, we suggest a new method called DMOS (Description and
MOdification of Segmentation). It consists of a grammatical formalism of position (to define knowledge) and a parser allowing a dynamic modification of the parsed
structure. This modification allows us to introduce context (symbolic level) in segmentation (numeric level) in order to improve recognition. With knowledge
represented by a grammar, the DMOS method offers a separation between knowledge and program, and an automatic parser generation (through a compilation
phase). These two points greatly ease the management of complex knowledge. Using the formalism of position we have been able to define a grammar of the music
notation. The present system is already able to recognize some full scores with polyphonic staves by correcting some type of segmentation errors (like symbols
touching notes) and by pointing out badly recognized zones.},
keywords = {Structured Document Analysis, A Priori Knowledge Introduction, Segmentation, Grammar, DCG, Optical Music Recognition}
}
@phdthesis{DiRiso1992,
author = {Di Riso, D.},
title = {Lettura automatica di partiture musicali},
school = {Universit di Salerno},
year = {1992},
address = {Salerno, Italy}
}
@proceedings{Distasi1993,
title = {An automatic system for reading musical scores},
year = {1993},
volume = {2},
abstract = {In this paper we will show our system for the automated reading of musical scores. The system, as of now, is made up of two modules. The first module takes as input a scanner image. From the image, an intermediate alphanumeric output is obtained. The format we have chosen for this intermediate data is the MUSICA language [De Biasi et al., 1982]. The second module of the system translates the MUSICA code into a standard MIDI file, suitable for immediate playing as well as for further processing (5 Refs.) scanners; optical character recognition},
author = {Distasi, R. and Nappi, M. and Vitulano, S.},
keywords = {automated reading; musical scores; scanner image; intermediate alphanumeric output; MUSICA language; standard MIDI file; optical character recognition processing); C1250B (Character recognition); C5260B (Computer vision and image processing techniques); C5530 (Pattern recognition and computer vision equipment)},
pages = {1307--1310}
}
@article{Donnelly2011,
author = {Donnelly, D. and Hankinson, A.},
title = {An Annotated Dataset for Optical Music Recognition Systems Development},
journal = {Conference of the Renaissance Society of America},
year = {2011},
location = {Montréal, QC}
}
@inproceedings{Fahmy1991,
author = {Fahmy, H. and Blostein, D.},
title = {A graph grammar for high-level recognition of music notation},
booktitle = {First International Conference on Document Analysis and Recognition},
year = {1991},
volume = {1},
pages = {70--78},
location = {St. Malo, France}
}
@mastersthesis{Fahmy1991a,
author = {Fahmy, H.},
title = {A graph-grammar approach to high-level music recognition},
school = {Queen’s University},
year = {1991},
address = {Kingston, Ontario, Canada}
}
@phdthesis{Fischer1978,
author = {Fischer, K. N.},
title = {Computer recognition of engraved music},
school = {University of Tennessee},
year = {1978}
}
@proceedings{Fluhr1988,
title = {Music pattern recognition},
year = {1988},
editor = {Truquet, M.},
address = {Toulouse, France},
author = {Fluhr, C. and Abouassly, J.},
booktitle = {Music pattern recognition}
}
@article{Fujinaga1989,
author = {Fujinaga, I. and Alphonce, B. and Pennycook, B. and Boisvert, N.},
title = {Optical recognition of music notation by computer},
journal = {Computers in Music Research},
year = {1989},
volume = {1},
pages = {161--164}
}
@proceedings{Fujinaga1989a,
title = {Computer recognition of musical notation},
year = {1989},
address = {Kyoto, Japan},
author = {Fujinaga, I. and Pennycook, B. and Alphonce, B.},
booktitle = {Computer recognition of musical notation},
pages = {87--90}
}
@proceedings{Fujinaga1989b,
title = {Issues in the design of an optical music recognition system},
year = {1989},
address = {Columbus, OH},
author = {Fujinaga, I. and Alphonce, B. and Pennycook, B.},
booktitle = {Issues in the design of an optical music recognition system},
pages = {113--116}
}
@article{Fujinaga1991,
author = {Fujinaga, I. and Pennycook, B. and Alphonce, B.},
title = {The optical music recognition project},
journal = {Computers in Music Research},
year = {1991},
volume = {3},
pages = {139--142}
}
@proceedings{Fujinaga1991a,
title = {Optical music recognition: Progress report},
year = {1991},
address = {Montreal, QC},
author = {Fujinaga, I. and Alphonce, B. and Pennycook, B. and Hogan, K.},
booktitle = {Optical music recognition: Progress report},
pages = {66--73}
}
@article{Fujinaga1992,
author = {Fujinaga, I},
title = {An optical music recognition system that learns},
journal = {Enabling Technologies for High-Bandwidth Applications},
year = {1992},
volume = {SPIE 1785},
pages = {210--217}
}
@article{Fujinaga1992a,
author = {Fujinaga, I. and Alphonce, B. and Pennycook, B.},
title = {Interactive optical music recognition},
journal = {Proceedings of the International Computer Music Conference},
year = {1992},
pages = {117--120}
}
@proceedings{Fujinaga1992b,
title = {Optical music recognition on NeXT workstation},
year = {1992},
address = {Los Angeles, CA},
author = {Fujinaga, I. and Alphonce, B. and Diener, G. and Pennycook, B.},
booktitle = {Optical music recognition on NeXT workstation}
}
@article{Fujinaga1996,
author = {Fujinaga, I.},
title = {Adaptive optical music recognition},
journal = {IEEE Transactions on Systems, Man, and Cybernetics},
year = {1996}
}
@article{Geggus1993,
author = {Geggus, K. M. and Botha, E. C.},
title = {A model-based approach to sheet music recognition},
journal = {Elektron},
year = {1993},
volume = {10},
number = {1},
pages = {25--29},
abstract = {The recognition of sheet music by computer has been tackled with varying degrees of success for 25 years. An effective solution to this problem is to use the model-based approach, where the syntax and structure of sheet music aid the recognition of the music symbols. The complete system, which translates a graphical sheet of music to a text file, involves data acquisition (a flat bed scanner with a resolution of 300 dots per inch is used), bar identification, stave line extraction, symbol segmentation and recognition, and generation of the output file (8 Refs.) model-based reasoning; optical character recognition},
keywords = {sheet music recognition; model-based approach; syntax; structure; data acquisition; flat bed scanner; bar identification; stave line extraction; symbol segmentation computer vision equipment); C1250B (Character recognition); C5520 (Data acquisition equipment and techniques)}
}
@phdthesis{Glass1989,
author = {Glass, S.},
title = {Optical music recognition},
school = {University of Canterbury},
year = {1989},
address = {Canterbury, UK}
}
@article{Hachimura1987,
author = {Hachimura, K. and Ohno, Y.},
title = {A system for the representation of human body movements from dance scores},
journal = {Pattern Recognition Letters},
year = {1987},
volume = {5},
pages = {1--9}
}
@article{Hankinson2010,
author = {Hankinson, A.},
title = {Distributed Optical Music Recognition},
journal = {Digital Humanities Summer Institute},
year = {2010},
location = {Victoria, BC}
}
@article{Hankinson2011,
author = {Hankinson, A. and Vigliensoni, G. and Burgoyne, J. A. and Fujinaga, I.},
title = {New tools for Optical Chant Recognition},
journal = {Conference of the International Association of Music Libraries},
year = {2011},
location = {Dublin, Ireland}
}
@article{Hankinson2012,
author = {Hankinson, A. and Vigliensoni, G. and Burgoyne, J. A. and Fujinaga, I.},
title = {New tools for Optical Chant Recognition},
journal = {Conference of the Music Libraries Association},
year = {2012},
location = {Dallas, TX}
}
@article{Hankinson2013a,
author = {Hankinson, A. and Fujinaga, I.},
title = {Searching and Navigating Digitized Music Books using Optical Music Recognition},
journal = {Canadian Association of Music Libraries Conference},
year = {2013},
location = {Victoria, BC}
}
@proceedings{Hankinson2013b,
title = {SIMSSA: Towards full-music search over a large collection of musical scores},
year = {2013},
address = {Lincoln, NE},
author = {Hankinson, A. and Fujinaga, I.},
booktitle = {SIMSSA: Towards full-music search over a large collection of musical scores}
}
@article{Hankinson2014,
author = {Hankinson, A. and Fujinaga, I.},
title = {Optical music recognition for navigating and retrieving music manuscript images},
journal = {Medieval and Renaissance Conference},
year = {2014},
location = {Birmingham, UK}
}
@proceedings{Homenda2004,
title = {Automatic Recognition of Music Notation Using Methods of Centroids and Classification Trees},
year = {2004},
address = {Haikou, China},
author = {Homenda, W. and Luckner, M},
booktitle = {Automatic Recognition of Music Notation Using Methods of Centroids and Classification Trees}
}
@article{Inokuchi1981,
author = {Inokuchi, S.},
title = {Musical database},
journal = {Journal of the Institute of Electronics and Communication Engineers of Japan},
year = {1981},
volume = {64},
number = {5},
pages = {466--468},
abstract = {Musical data entry methods by typewriter, piano, tablet touch pad, OCR and automatic digital musical analysis are outlined. As examples of musical databases the Institut de Recherche et Coordination Acoustique/musique and the National Ethnographic Museum (of Japan) methods are discussed (9 Refs.) optical character recognition; typewriters},
keywords = {data entry methods; typewriter; piano; tablet touch pad; OCR; automatic digital musical analysis; musical databases computing)}
}
@article{Inokuchi1990,
author = {Inokuchi, S. and Katayose, H.},
title = {Computer and music},
journal = {Journal of the Institute of Electronics, Information and Communication Engineers},
year = {1990},
volume = {73},
number = {9},
pages = {965--967},
abstract = {Computer applications for music production have been developed in the 1970s. Computers have been used in various fields of music, including applications for a music database, music CAI and visual input of musical information as well as music production tools. Music as the objective of cognitive science or artificial intelligence has been attracting great interest and international conferences have been held recently. The paper describes the technology and development trends in this field, referring to the basic technology of computer music, notation system, man-machine interaction system, music composition/arrangement systems and music recognition (16 Refs.) instruction; electronic music; music},
keywords = {computer applications; music production; music database; music CAI; visual input; musical information; cognitive science; artificial intelligence; computer music; notation system; man-machine interaction system; music composition/arrangement systems; music recognition C7810C (Computer-aided instruction); C6170 (Expert systems)}
}
@inproceedings{Itagaki1990,
author = {Itagaki, T. S. and Hashimoto, S. and Isogai, M. and Ohteru, S.},
title = {Automatic recognition on some different types of musical notation.},
booktitle = {Proceedings of the International Association for Pattern Recognition Workshop on Syntactic and Structural Pattern Recognition},
year = {1990},
pages = {488 ff.}
}
@incollection{Kassler1970,
author = {Kassler, M.},
title = {An essay toward specification of a music-reading machine},
booktitle = {Musicology and the computer},
publisher = {City University of New York Press},
year = {1970},
editor = {Brook, B.},
pages = {151--175},
address = {New York}
}
@article{Kato1988,
author = {Kato, H. and Inokuchi, S.},
title = {Automatic recognition of printed piano music based on bar unit processing (in Japanese)},
journal = {Transactions of I. E. C. E.},
year = {1988},
volume = {J71-D},
number = {5},
pages = {894--901}
}
@article{Kato1990,
author = {Kato, H. and Inokuchi, S.},
title = {The recognition system for printed piano music using musical knowledge and constraints},
journal = {Proceedings of the International Association for Pattern Recognition Workshop on Syntactic and Structural Pattern Recognition},
year = {1990},
pages = {231--248}
}
@article{Kinoshita1998,
author = {Kinoshita, T. and Muraoka, H. and Tanaka, H.},
title = {Note recognition using statistical information of musical note transitions},
journal = {Journal of the Acoustical Society of Japan},
year = {1998},
volume = {54},
number = {3},
pages = {190--198},
abstract = {This paper proposes a new method that improves the note recognition accuracy of a music recognition system. The system recognizes the pitch and the name of the instrument for each note in monaural music signals. The basic idea of the method is utilizing transition pattern of notes in music. Firstly, the results of statistical analyses of printed music are described. These have been conducted in order to obtain the note transition probabilities. Then the method for integrating such probabilistic information into recognition processes is introduced. The method has been implemented using the OPTIMA architecture and tested from several aspects. The results of the tests show that the proposed method improves the note recognition accuracy (6 Refs.)},
keywords = {note recognition; statistical information; musical}
}
@article{Kobayakawa1993,
author = {Kobayakawa, T.},
title = {Auto music score recognition system},
journal = {Proceedings of the SPIE: Character Recognition Technologies},
year = {1993},
volume = {1906},
pages = {112--123}
}
@article{Lee1985,
author = {Lee, M. Woo and Choi, J. Soo},
title = {The recognition of printed music score and performance using computer vision system (in Korean and English translation)},
journal = {Journal of the Korean Institute of Electronic Engineers},
year = {1985},
volume = {22},
number = {5},
pages = {429--435}
}
@article{Lee1994,
author = {Lee, S. and Shin, J.},
title = {Recognition of music scores using neural networks},
journal = {Journal of the Korea Information Science Society},
year = {1994},
volume = {21},
number = {7},
pages = {1358--1366}
}
@misc{Lee1995,
author = {Lee, S. D.},
title = {Automatic Optical Music Recognition},
year = {1995},
comment = {Uncertain type},
school = {Department of Computer Science, Hong Kong University}
}
@phdthesis{Leite1994,
author = {Leite, J. A. and Ferrand, M.},
title = {RIEM: Reconhecimento e Interpretao de Escrita Musical (in Portuguese)},
school = {Universidade de Coimbra},
year = {1994},
type = {B.Sc. Dissertation}
}
@article{Leite1998,
author = {Leite, J. and Ferrand, M. and Cardoso, A.},
title = {RIEM: A system for recognition and interpretation of music writing (in Portuguese)},
year = {1998},
volume = {Internal Report RI-DEI-001-98}
}
@article{Leplumey1991,
author = {Leplumey, I. and Camillerapp, J.},
title = {Comparison of region labelling for musical scores},
journal = {International Conference on Document Analysis and Recognition},
year = {1991},
volume = {2},
pages = {674--682},
location = {St. Malo, France}
}
@article{Leplumey1991a,
author = {Leplumey, I. and Camillerapp, J.},
title = {Coopration entre la segmentation des rgions blanches et des rgions noires pour l'analyse de partitions musicales},
journal = {8e Congress Reconnaissance des Formes et Intelligence Artificielle},
year = {1991},
volume = {3},
pages = {1045--1052}
}
@proceedings{Lobb2005,
title = {Fast capture of sheet music for an agile digital music library},
year = {2005},
address = {London, UK},
author = {Lobb, R. and Bell, T. and Bainbridge, D.},
booktitle = {Fast capture of sheet music for an agile digital music library},
pages = {145--152}
}
@phdthesis{Luckner2003,
author = {Luckner, M.},
title = {Automatic Identification of Selected Symbols of Music Notation},
school = {Warsaw University of Technology},
year = {2003},
address = {Warsaw, Poland}
}
@article{Maenaka1983,
author = {Maenaka, K. and Tadokoro, Y.},
title = {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)},
journal = {Prl83-60},
year = {1983},
pages = {37--45}
}
@phdthesis{Mahoney1982,
author = {Mahoney, J. V.},
title = {Automatic analysis of musical score images},
school = {Massachusetts Institute of Technology},
year = {1982}
}
@phdthesis{Martin1987,
author = {Martin, N. G.},
title = {Towards computer recognition of the printed musical score},
school = {Thames Polytechnic},
year = {1987}
}
@article{Martin1989,
author = {Martin, P.},
title = {Reconnaissance de partitions musicales et rseaux de neurones: une tude},
journal = {Actes 7 ime Congrs AFCET de Reconnaissance des Formes et Intelligence Artificielle},
year = {1989},
pages = {217--226}
}
@inproceedings{Martin1991,
author = {Martin, P. and Bellissant, C.},
title = {Low-level analysis of music drawing images},
booktitle = {International Conference on Document Analysis and Recognition},
year = {1991},
pages = {417--425}
}
@article{Martin1991a,
author = {Martin, P. and Bellissant, C.},
title = {Neural networks at different levels of musical score image analysis system},
journal = {Seventh Scandinavian Conference on Image Analysis},
year = {1991},
pages = {1102--1109},
location = {Alborg, DK}
}
@article{Matsushima1985a,
author = {Matsushima, T. and Harada, T. and Sonomoto, I. and Kanamori, K. and Uesugi, A. and Nimura, Y. and Hashimoto, S. and Ohteru, S.},
title = {Automated recognition system for musical score: The vision system of WABOT-2},
year = {1985},
number = {112: 25-52}
}
@article{Matsushima1985b,
author = {Matsushima, T. and Ohteru, S. and Kanamori, K.},
title = {Automatic recognition of printed music (in Japanese)},
journal = {Japan Acoustics Society Journal},
year = {1985},
volume = {41},
number = {6},
pages = {412--415}
}
@article{Matsushima1988,
author = {Matsushima, T.},
title = {Automatic printed-music-to-braille translation system},
journal = {Journal of Information Processing},
year = {1988},
volume = {11},
number = {4},
pages = {249--257}
}
@proceedings{Matsushima1989,
title = {An integrated music information processing system},
year = {1989},
author = {Matsushima, T. and Ohteru, S. and Hashimoto, S.},
booktitle = {An integrated music information processing system},
pages = {191--198}
}
@proceedings{Matsushima1992,
title = {Computerized Japanese traditional music processing system},
year = {1992},
author = {Matsushima, T.},
booktitle = {Computerized Japanese traditional music processing system},
pages = {121--124}
}
@article{McGee1989,
author = {McGee, W. F. and Merkley, P.},
title = {Optical recognition of music using page straightening},
year = {1989}
}
@article{McGee1994,
author = {McGee, W. F.},
title = {MusicReader: An interactive optical music recognition system},
journal = {Computing in Musicology},
year = {1994},
volume = {9},
pages = {146--151}
}
@phdthesis{McLean1991,
author = {McLean, G.},
title = {Music recognition},
school = {Heriot-Watt University},
year = {1991}
}
@proceedings{McPherson2001,
title = {Coordinating knowledge within an optical music recognition system},
year = {2001},
address = {Christchurch, New Zealand},
author = {McPherson, J. and Bainbridge, D.},
booktitle = {Coordinating knowledge within an optical music recognition system},
pages = {50--58}
}
@proceedings{McPherson2002,
title = {Introducing feedback into an optical music recognition system},
year = {2002},
address = {Bloomington, IN},
abstract = {Page 1. Introducing Feedback into an Optical Music Recognition System},
author = {McPherson, J.},
booktitle = {Introducing feedback into an optical music recognition system},
pages = {259--260}
}
@article{Miyao1990,
author = {Miyao, H. T. and Ejima, T. and Miyahara, M. and Kotani, K.},
title = {Recognition for printed piano scores (in Japanese)},
journal = {Nlc90-34, Pru90-74},
year = {1990},
pages = {39--46}
}
@article{Miyao1992,
author = {Miyao, H. T. and Ejima, T. and Miyahara, M. and Kotani, K.},
title = {Symbol recognition for printed piano scores based on the musical knowledge (in Japanese)},
journal = {Transactions of the Institute of Electronics, Information and Communication Engineers D-II},
year = {1992},
volume = {J75D-II},
number = {11},
pages = {1848--1855}
}
@article{Miyao2007,
author = {Miyao, H. and Okamoto, M.},
title = {Stave extraction for printed music scores using DP matching},
journal = {Journal of Advanced Computational Intelligence and Intelligent Informatics},
year = {2007},
volume = {8},
number = {2},
pages = {208--215}
}
@inproceedings{Modayur1991,
author = {Modayur, B. R.},
title = {Restriced domain music score recognition using mathematical morphology},
booktitle = {Fifth International Conference on Symbolic and Logical Computing},
year = {1991}
}
@proceedings{Modayur1992a,
title = {On printed music score symbol recognition},
year = {1992},
author = {Modayur, B. R. and Haralick, R. M. and Shapiro, L. G.},
booktitle = {On printed music score symbol recognition},
pages = {16--18},
url = {http://haralick.org/conferences/Printed_Music_Score.pdf}
}
@article{Musitek1994,
author = {Musitek},
title = {Musitek Midiscan Sheet music recognition software for IBM},
journal = {Keyboard},
year = {1994},
volume = {20},
number = {3},
pages = {136},
url = {https://openmusiclibrary.org/article/972021/}
}
@article{Nagy1989,
author = {Nagy, G.},
title = {Document analysis and optical character recognition},
journal = {Fifth International Conference on Image Analysis and Processing},
year = {1989},
pages = {511--529}
}
@article{Nakamura1978,
author = {Nakamura, Y. and Shindo, M. and Inokuchi, S.},
title = {Input method of [musical] note and realization of folk music data-base (in Japanese)},
journal = {Institute of Electronics and Communications Engineers of Japan (IECE)},
year = {1978},
volume = {TG PRL78-73},
pages = {41--50}
}
@article{Nelson1973,
author = {Nelson, G. and Penney, T. R.},
title = {Pattern recognition in musical score - Project no. M88.},
journal = {Computers and the Humanities},
year = {1973},
volume = {8},
pages = {50--51}
}
@article{Newell1993,
author = {Newell, C. and and, Homenda, W.},
title = {MIDISCAN for windows},
year = {1993}
}
@article{Ng1994,
author = {Ng, K. and Boyle, R. D.},
title = {Reconstruction of music scores from primitive Sub-segmentation},
year = {1994},
url = {http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.35.648&rep=rep1&type=pdf}
}
@phdthesis{Ng1995a,
author = {Ng, K.},
title = {Automated computer recognition of music score},
school = {University of Leeds},
year = {1995},
address = {Leeds, UK}
}
@misc{Ng1995b,
author = {Ng, K. and Boyle, R. and Cooper, D.},
title = {Automated optical musical score recognition and its enhancement using high-level musical knowledge},
year = {1995},
address = {Bologna, Italy},
booktitle = {XI Colloquium on Musical Informatics},
pages = {167--170}
}
@inproceedings{Ng1996a,
author = {Ng, K. and Boyle, R. and Cooper, D.},
title = {Hand written music manuscript recognition},
booktitle = {Proceedings of the International Computer Music Conference},
year = {1996},
pages = {500--503},
address = {Hong Kong, China}
}
@misc{Ng2000,
author = {Ng, K. C. and Cooper, D},
title = {Enhancement of optical music recognition using metric analysis},
year = {2000},
booktitle = {XIII Colloquium on Musical Informatics}
}
@proceedings{Ng2001,
title = {Towards an integrated Handwritten Music Manuscript Analysis and Recognition System},
year = {2001},
address = {Glasgow},
author = {Ng, K and Cooper, D. and Ong, B},
booktitle = {Towards an integrated Handwritten Music Manuscript Analysis and Recognition System}
}
@proceedings{Ng2002a,
title = {Document Imaging for Music Manuscript},
year = {2002},
address = {Florida, USA},
author = {Ng, K},
booktitle = {Document Imaging for Music Manuscript}
}
@inproceedings{Ng2002b,
author = {Ng, K and Cooper, D. and Ong, B},
title = {Optical music analysis: A reverse engineering approach},
booktitle = {EVA},
year = {2002},
address = {Florence, Italy}
}
@article{Ohteru1984,
author = {Ohteru, S. and et, al.},
title = {A multi processor system for high speed recognition of printed music (in Japanese)},
journal = {National Convention Records of IECE},
year = {1984}
}
@misc{Ohteru1984a,
author = {Ohteru, S. and others},
title = {A multi processor system for high speed recognition of printed music (in Japanese)},
howpublished = {National Convention Records of I. E. C. E.},
year = {1984}
}
@article{Ohteru1987,
author = {Ohteru, S.},
title = {Automatic recognition of music score (in Japanese)},
journal = {Bit (special issue on Computer and Music)},
year = {1987},
pages = {92--100}
}
@article{Ohteru1988,
author = {Ohteru, S.},
title = {Data entry and automatic recognition of music score (in Japanese)},
journal = {Journal of the Information Processing Society of Japan},
year = {1988},
volume = {29},
number = {6},
pages = {586--592}
}
@proceedings{Onoe1979,
title = {Experiment on automatic music reading (in Japanese)},
year = {1979},
author = {Onoe, M. and Ishizuka, M. and Tsuboi, K.},
booktitle = {Experiment on automatic music reading (in Japanese)},
pages = {6F-65}
}
@article{Ostenstad1988,
author = {Ostenstad, B.},
title = {Oppdeling av abjektene i et digitalt notebilde i klassifiserbare enheter (in Norwegian)},
year = {1988},
location = {Oslo, Norway}
}
@article{Pennycook1990,
author = {Pennycook, B.},
title = {Towards advanced optical music recognition},
journal = {Advanced Imaging},
year = {1990},
pages = {54--57}
}
@proceedings{Perrotti1993,
title = {Pre-processamento, Exctracao de Atributos e Primeiro Nivel de Classiccao para un Sistema de Reconhecimento Otico de Simbolos Musicais},
year = {1993},
author = {Perrotti, F. A. and Lotufo, R. A.},
booktitle = {Pre-processamento, Exctracao de Atributos e Primeiro Nivel de Classiccao para un Sistema de Reconhecimento Otico de Simbolos Musicais}
}
@inproceedings{PoulaindAndecy1993,
author = {Poulain d'Andecy, Vincent},
title = {Segmentation et reconnaissance optique de partitions musicales},
year = {1993},
location = {Rennes, France}
}
@inproceedings{Prerau1975,
author = {Prerau, D. S.},
title = {Do-Re-Mi: A program that recognizes music notation},
booktitle = {Computers and the Humanities},
year = {1975},
volume = {9},
number = {1},
pages = {25--9}
}
@article{Pugin2008,
author = {Pugin, L.},
title = {Computer Tools for Early Music Sources Comparison: A Practical Study on Marenzio Editions and Re-editions},
year = {2008},
volume = {Luca Marenzio and the Late Renaissance Madrigal: Music, Poetry, Patronage, and Reception},
location = {Turnjout}
}
@article{Pugin2009,
author = {Pugin, L.},
title = {Editing Renaissance Music: The Aruspix Project},
year = {2009},
volume = {Beihefte zur Editio, Internationales Jahrbuch für Editionswissenschaften},
pages = {94--103},
location = {Tübingen}
}
@mastersthesis{Reed1995,
author = {Reed, K. T.},
title = {Optical Music Recognition},
school = {University of Calgary, Canada},
year = {1995}
}
@article{Richard1990,
author = {Richard, D. M.},
title = {Godel tune: formal models in music recognition systems},
journal = {ICMC Glasgow 1990. Proceedings},
year = {1990},
pages = {338--340},
abstract = {Formal models of music have been used as a design principle of automatic music recognition systems. These models range from statistical to generative/transformational models. However, the use of formal models in recognition problems implicitly impose data structures and algorithmic processes to the mechanism of perception and can result in inconsistent or extremely limited systems. By first modeling the perception mechanism as a statistical decision process merging sensory data and memory information, one can more readily identify the data elements and computational structures required for the recognition task and integrate formal representation(s) of music in a dynamically changing system (26 Refs.) music; statistics},
keywords = {Godel tune; formal models; music recognition systems; design principle; generative/transformational models; data structures; algorithmic processes; perception mechanism; statistical decision process; sensory data; memory information; data elements; computational structures; formal representation; dynamically changing system}
}
@phdthesis{Roth1992,
author = {Roth, M.},
title = {OMR-optical music recognition},
school = {Swiss Federal Institute of Technology},
year = {1992}
}
@article{Sawada1990,
author = {Sawada, H. and Matsushima, T. and Itakagi, T. and Ohteru, S.},
title = {A practical bilateral translation system between printed music and braille},
journal = {Proceedings of Sixth International Workshop on Computer Applications for the Visually Handicapped},
year = {1990}
}
@article{Sawaki1998,
author = {Sawaki, M. and Murasei, H. and Hagita, N. and Ishii, K.},
title = {A study on SYAKUHACHI score recognition with embedded symbols},
journal = {Transactions of the Institute of Electronics, Information and Communication Engineers D-II},
year = {1998},
volume = {J81D-II},
number = {10},
pages = {2480--2482},
abstract = {A method for recognizing SYAKUHACHI scores with embedded symbols is proposed. A SYAKUHACHI score mainly consists of characters indicating pitch and embedded symbols indicating the length of the sound. The complementary similarity measure enables the system to handle embedded symbols independently and that results in high performance of the recognition (6 Refs.)},
keywords = {SYAKUHACHI score recognition; embedded symbols; characters; pitch; complementary similarity measure vision and image processing techniques); C1250B (Character recognition)}
}
@article{Selfridge-Field1994,
author = {Selfridge-Field, E.},
title = {How practical is Optical Music Recognition as an Input Method?},
journal = {Computing in Musicology},
year = {1994},
volume = {9},
number = {1993-94},
pages = {159--166}
}
@article{Selfridge-Field1994a,
author = {Selfridge-Field, E.},
title = {Optical recognition of musical notation: A survey of current work},
journal = {Computing in Musicology},
year = {1994},
volume = {9},
pages = {109--145}
}
@article{Sokei1997,
author = {Sokei, S. and Yamashiro, T. and Iha, Z. and Toguchi, M.},
title = {Study of recognition for okinawa syamisen score KUNKUNSI},
year = {1997},
abstract = {Handwritten character recognition has been increasing in importance and has been expanding its application areas. In this paper, the authors propose a recognition system of a musical score. The recognition system uses a simple, fast feature extraction method, and an efficient way of combining a fast recognition method (3-dimensional table method) and an exact recognition method (multiple simularity method). The authors demonstrated the performance of the completed system by experiments using real data (8 Refs.) transforms; optical character recognition},
keywords = {handwritten character recognition; musical score recognition; feature extraction method; fast recognition method; 3-D table method; exact recognition method; multiple simularity method; recognition performance processing); B0230 (Integral transforms); C1250B (Character recognition); C1130 (Integral transforms)}
}
@article{Sonomoto1985,
author = {Sonomoto, I. and Harada, T. and Matsushima, T. and Kanamori, K. and Konuma, M. and Uesugi, A. and Nimura, Y. and Hashimoto, S. and Ohteru, S.},
title = {Automated recognition system of printed music for playing keyboards (in Japanese)},
journal = {Acoustical Society of Japan},
year = {1985},
pages = {TG MA84--22 17}
}
@article{Stueckelberg1999,
author = {Vuilleumier St{\"{u}}ckelberg, Marc},
title = {Musical score recognition using probabilistic inference},
year = {1999}
}
@mastersthesis{Sumsion1992,
author = {Sumsion, H.},
title = {Optical Music Recognition},
school = {Leeds, University of Leeds},
year = {1992}
}
@article{Thorud1988,
author = {Thorud, E.},
title = {Analyse av notebilder (in Norwegian)},
year = {1988},
location = {Oslo, Norway}
}
@inproceedings{Tojo1982,
author = {Tojo, A. and Aoyama, H.},
title = {Automatic recognition of music score (in Japanese)},
booktitle = {Sixth International Conference on Pattern Recognition},
year = {1982},
volume = {11},
number = {5},
pages = {427--435},
journal = {Electronic Image Conference Journal}
}
@article{Tonnesland1986,
author = {Tonnesland, S.},
title = {SYMFONI: System for note coding (in Norwegian)},
year = {1986},
location = {Oslo, Norway}
}
@inproceedings{Vieira2000,
author = {Vieira, P. and Marcolino, A. and others},
title = {Ancient music optical recognition},
booktitle = {11th Portuguese Conference on Pattern Recognition RecPad2000},
year = {2000}
}
@inproceedings{Vieira2001,
author = {Vieira, P. and Pinto, J.},
title = {A classification method for ancient hand-written musical symbols},
booktitle = {Actas de 10{$^{\circ}$} Encontro Portugu{\^{e}}s de Computa{\c{c}}{\~{a}}o},
year = {2001},
address = {Gr{\'{a}}fica, Lisbon}
}
@phdthesis{Vrist2009,
author = {Vrist, S.},
title = {Optical Music Recognition for structural information from high-quality scanned music},
school = {University of Copenhagen},
year = {2009},
address = {Copenhagen, DK}
}
@article{Watkins1994,
author = {Watkins, G.},
title = {A fuzzy syntactic approach to recognising hand-written music},
journal = {Proceedings of the International Computer Music Conference},
year = {1994},
pages = {297--302}
}
@mastersthesis{Wilk1995,
author = {Wilk, R.},
title = {Converting graphic musical data to a machine playable form},
school = {McGill University},
year = {1995}
}
@mastersthesis{Wilkinson1995,
author = {Wilkinson, J.},
title = {Optical Music Recognition},
school = {School of Computer Science, University of Birmingham},
year = {1995},
address = {Birmingham}
}
@article{Wittlich1973,
author = {Wittlich, G.},
title = {Project SCORE},
journal = {Computational Musicology Newsletter},
year = {1973},
volume = {1},
number = {1},
pages = {6}
}
@article{Wittlich1974,
author = {Wittlich, G. E.},
title = {Non-physics measurements on the PEPR System: Seismograms and music scores},
year = {1974}
}
@inproceedings{Wolman1994,
author = {Wolman, A. and Yeager, T.},
title = {Optical music recognition: progress report},
booktitle = {International Computer Music Conference},
year = {1994}
}
@phdthesis{Wright1994,
author = {Wright, D. J.},
title = {Optical music recognition: A deterministic, object-oriented approach},
school = {University of Victoria},
year = {1994}
}
@article{Yadid-Pecht1992,
author = {Yadid-Pecht, O. and Brutman, E. and Dvir, L. and Gerner, M. and Shimony, U.},
title = {RAMIT: Neural network for recognition of musical notes},
journal = {Proceedings of the International Computer Music Conference},
year = {1992},
pages = {128--131}
}
@article{Yin1989,
author = {Yin, F. and Qingshi, G. and Xiang, Z.},
title = {Principle on designing the music reading system (in Chinese)},
journal = {Mini-Micro Systems},
year = {1989},
volume = {10},
number = {12},
pages = {1--10}
}
@techreport{Yoda1994,
author = {Yoda, Ikushi and Yamamoto, Kazuhiko and Yamada, Hiromitsu},
title = {Automatic Construction of Recognition Procedures for Musical Notes by GA},
year = {1994},
file = {:pdfs/1994 - Automatic Construction of Recognition Procedures for Musical Notes by GA.pdf:PDF}
}
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