23.2.7.3 Analysis of Music, Musical Notation

Prerau, D.,
Computer Pattern Recognition of Standard Engraved Music Notation,
Ph.D.Thesis, EE, MIT, 1970. BibRef 7000

Bainbridge, D.,
Extensible Optical Music Recognition,
Ph.D.Thesis, CS, University of Cantebury, New Zealand, 1997. BibRef 9700

Roach, J.W., Tatem, J.E.,
Using Domain Knowledge in Low-Level Visual Processing to Interpret Handwritten Music: An Experiment,
PR(21), No. 1, 1988, pp. 33-44.
WWW Version. BibRef 8800

Blostein, D., Baird, H.S.,
A Critical Survey of Music Image Analysis,
SDIA92(405-434). BibRef 9200

Modayur, B.R., Ramesh, V., Haralick, R.M., Shapiro, L.G.,
MUSER: A prototype musical score recognition system using mathematical morphology,
MVA(6), No. 2-3, 1993, pp. 140-150. BibRef 9300

Fahmy, H., Blostein, D.,
A graph grammar programming style for recognition of music notation,
MVA(6), No. 2-3, 1993, pp. 83-99. BibRef 9300

Kopec, G.E., Chou, P.A., Maltz, D.A.,
Markov Source Model for Printed Music Decoding,
JEI(5), No. 1, January 1996, pp. 7-14. BibRef 9601

Yadid-Pecht, O., Gerner, M., Dvir, L., Brutman, E., Shimony, U.,
Recognition of Handwritten Musical Notes by a Modified Neocognitron,
MVA(9), No. 2, 1996, pp. 65-72.
HTML Version. 9609
Neural Nets. Overall rates of around 80%. BibRef

Ng, K.C., Boyle, R.D.,
Recognition and Reconstruction of Primitives in Music Scores,
IVC(14), No. 1, February 1996, pp. 39-46.
WWW Version. 9608
BibRef
Earlier:
Segmentation of Music Primitives,
BMVC92(xx-yy).
PDF Version. 9209
BibRef

Blostein, D.[Dorothea], Haken, L.[Lippold],
Using Diagram Generation Software to Improve Diagram Recognition: A Case Study of Music Notation,
PAMI(21), No. 11, November 1999, pp. 1121-1136.
IEEE Abstract. IEEE Top Reference.
WWW Version. 9912
BibRef

Gezerlis, V.G.[Velissarios G.], Theodoridis, S.[Sergios],
Optical character recognition of the Orthodox Hellenic Byzantine Music notation,
PR(35), No. 4, April 2002, pp. 895-914.
WWW Version. 0201
BibRef
Earlier:
An Optical Music Recognition System for the Notation of the Orthodox Hellenic Byzantine Music,
ICPR00(Vol IV: 837-840).
IEEE DOI Link
HTML Version. 0009
BibRef

Rossant, F.[Florence],
A global method for music symbol recognition in typeset music sheets,
PRL(23), No. 10, August 2002, pp. 1129-1141.
HTML Version. 0205
BibRef

Pinto, J.R.C.[João R. Caldas], Vieira, P.[Pedro], Sousa, J.M.[João M.],
A new graph-like classification method applied to ancient handwritten musical symbols,
IJDAR(6), No. 1, 2003, pp. 10-22.
HTML Version. 0308
BibRef

Vieira, P.[Pedro], Pinto, J.R.C.[João R. Caldas],
Recognition of Musical Symbols in Ancient Manuscripts,
ICIP01(III: 38-41).
IEEE Abstract. IEEE Top Reference. 0108
BibRef

Miyao, H.[Hidetoshi], Maruyama, M.[Minoru],
An online handwritten music symbol recognition system,
IJDAR(9), No. 1, March 2007, pp. 49-58.
Springer DOI Link 0703
BibRef
Earlier:
An online handwritten music score recognition system,
ICPR04(I: 461-464).
IEEE DOI Link 0409
BibRef

Dalitz, C.[Christoph], Droettboom, M.[Michael], Pranzas, B.[Bastian], Fujinaga, I.[Ichiro],
A Comparative Study of Staff Removal Algorithms,
PAMI(30), No. 5, May 2008, pp. 753-766.
IEEE DOI Link 0803
Staff lines in music. BibRef

Dalitz, C.[Christoph], Michalakis, G.K.[Georgios K.], Pranzas, C.[Christine],
Optical recognition of psaltic Byzantine chant notation,
IJDAR(11), No. 3, December 2008, pp. xx-yy.
Springer DOI Link 0804
BibRef

Dalitz, C.[Christoph], Karsten, T.[Thomas], Droettboom, M.[Michael], Fujinaga, I.[Ichiro], Pose, F.[Florian], Czerwinski, B.[Bastian],
Staff Line Removal Toolkit for Gamera,
Online2005-2007.
WWW Version. Code, Music Processing. BibRef 0500

dos Santos Cardoso, J.[Jaime], Capela, A.[Artur], Rebelo, A.[Ana], Guedes, C.[Carlos], da Costa, J.P.[Joaquim Pinto],
Staff Detection with Stable Paths,
PAMI(31), No. 6, June 2009, pp. 1134-1139.
IEEE DOI Link 0904
BibRef
Earlier: A1, A2, A3, A4, Only:
A connected path approach for staff detection on a music score,
ICIP08(1005-1008).
IEEE DOI Link 0810
BibRef
Earlier: A2, A3, A1, A4, Only:
Staff Line Detection and Removal with Stable Paths,
SPMM08(263-270). Staff lines for transcribing handwritten scores. Lines affected by curvature, discontinuities, and inclination are robustly detected. Find the shortest, mostly straight, path from one side to the other. BibRef

Mokbel, B.[Bassam], Hasenfuss, A.[Alexander], Hammer, B.[Barbara],
Graph-Based Representation of Symbolic Musical Data,
GbRPR09(42-51).
Springer DOI Link 0905
BibRef

Szwoch, M.[Mariusz],
Guido: A Musical Score Recognition System,
ICDAR07(809-813).
IEEE DOI Link 0709
BibRef
Earlier:
A Robust Detector for Distorted Music Staves,
CAIP05(701).
Springer DOI Link 0509
BibRef

Toyama, F.[Fubito], Shoji, K.[Kenji], Miyamichi, J.[Juichi],
Symbol Recognition of Printed Piano Scores with Touching Symbols,
ICPR06(II: 480-483).
WWW Version. 0609
BibRef

Stückelberg, M.V., Pellegrini, C., Hilario, M.,
An Architecture for Musical Score Recognition Using High-Level Domain Knowledge,
ICDAR97(Poste) 9708
BibRef

Kashino, K., Hagita, N.,
A Music Scene Analysis System with the MRF-Based Information Integration Scheme,
ICPR96(II: 725-729).
IEEE DOI Link 9608
(NTT Basic Res. Labs, J) BibRef

Reed, K., Parker, J.,
Automatic Computer Recognition of Printed Music,
ICPR96(III: 803-807).
IEEE DOI Link 9608
(Univ. of Calgary, CDN) BibRef

d'Andecy, V.P., Camillerapp, J., Leplumey, I.,
Kalman filtering for segment detection: application to music scores analysis,
ICPR94(A:301-305).
IEEE DOI Link 9410
BibRef

Leplumey, I., Camillerapp, J., Lorette, G.,
A Robust Detector for Music Staves,
ICDAR93(902-905). BibRef 9300

Sicard, E.,
An efficient method for the recognition of printed music,
ICPR92(III:573-576).
IEEE DOI Link 9208
BibRef

Kato, H., Inokuchi, S.,
A Recognition System for Printed Piano Music using Musical Knowledge and Constraints,
SDIA92(xx-yy). 0905
BibRef

Carter, N.P., Bacon, R.A.,
Automatic Recognition of Printed Music,
SDIA92(xx-yy). 0905
BibRef

Itagaki, T., Isogai, M., Hashimoto, S., Ohteru, S.,
Automatic Recognition of Several Types of Musical Notation,
SDIA92(xx-yy). 0905
BibRef

Chapter on OCR, Document Analysis and Character Recognition Systems continues in
Detection and Correction of Document Skew, and other Distortions .