A new graph-like classification method applied to ancient handwritten musical symbols

International Journal on Document Analysis and Recognition

Volumn 6, Issue 1, 2003, Pages 10-22

  Pinto, João Caldas ^a   Vieira, Pedro ^a   Sousa, João M ^a  

^a INSTITUTO SUPERIOR TÉCNICO   (Portugal)

Author keywords

Binary image segmentation; Binary pattern recognition; Feature selection; Optical music recognition

Indexed keywords

BINARY PATTERN RECOGNITION; CLASSIFICATION METHODS; HIGH DEGREE OF ACCURACY; KEY ISSUES; MUSICAL SYMBOLS; OPTICAL MUSIC RECOGNITION; RECOGNITION PROCESS;

ALGORITHMS; BINARY IMAGES; FEATURE EXTRACTION;

PATTERN RECOGNITION;

EID: 33749051805     PISSN: 14332833     EISSN: 14332825     Source Type: Journal    
DOI: 10.1007/s10032-003-0102-3     Document Type: Article

References (18)

1. Armand J-P (1993) Musical score recognition: a hierarchical and recursive approach. Second international conference on document analysis and recognition, ICDAR, Tsukuba Science City, Japan
2. Bainbridge D, Carter N (1997) Automatic recognition of music notation. In: Bunke H, Wang P (eds) Handbook of optical character recognition and document image analysis, World Scientific, Singapore, pp 557-603
3. Banks S (1990) Signal processing, image processing and pattern recognition. Prentice-Hall, New York
4. Blostein D, Baird HS (1992) A critical survey of music image analysis. In: Baird HS, Bunke H, Yamamoto K (eds) Structured document image analysis, Springer, Berlin Heidelberg New York, pp 405-434
5. Pinto JC, Vieira P, Ramalho M, Mengucci M, Pina P, Muge F (2000) Ancient music recovery for digital libraries. Fourth European conference on research and advanced technology for digital libraries, ECDL 2000, Lisbon, pp 24-35
6. Duda RO, Hart PE (1973) Pattern recognition and scene analysis. Wiley, New York
7. Ferraté G, Pavlidis T, Sanfeliu A, Bunke H (eds) (1988) Syntactic and structural pattern recognition. NATO ASI Series, vol 45. Springer, Berlin Heidelberg New York
8. Hoppner F, Klawonn F, Kruse R, Runkler T (1999) Fuzzy cluster analysis: methods for classification, data analysis and image recognition. Wiley, New York
9. Jang JSR, Sun C-T, Mizutani E (1997) Neuro fuzzy and soft computing: a computational approach to learning and machine intelligence. Prentice-Hall, New York
10. Kohavi R, Provost F (1998) Glossary of terms. Editorial for the special issue on applications of machine learning and the knowledge discovery process, 30:271-274
11. Leplumey J, Camillerapp J, Lorette G (1993) A robust detector for music staves. Second international conference on document analysis and recognition, ICDAR, Tsukuba City Science, Japan
12. Ng KC, Boyle RD (1996) Recognition and reconstruction of primitives in music scores. Image Vision Comput 14:39-46
13. Patterson DW (1996) Artificial neural networks: theory and applications. Prentice-Hall, New York
14. Pépin F, Randriamahefa R, Fluhr C, Philipp S, Cocquerez JP (1993) Printed music recognition. Second international conference on document analysis and recognition, ICDAR, Tsukuba City Science, Japan
15. Rossant F (2002) A global method for music symbol recognition in typeset music sheets. Pattern Recogn Lett 23:1129-1141
16. Serra J (1982) Image analysis and mathematical morphology, vol 1. Academic, London
17. Yu FT, Jutamulia S (eds) Optical pattern recognition. Cambridge University Press, Cambridge
18. Wang PS (1977) Handbook of optical character recognition and document image analysis. World Scientific, Singapore