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HomeAdvanced Materials ResearchAdvanced Materials Research Vols. 225-226An Overview of Optical Music Recognition in China

An Overview of Optical Music Recognition in China

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Abstract:

OMR (Optical Music Recognition) is a technology for digital musical score image processing and recognition by computer, which has broad applications in the digital music library, contemporary music education, music theory, music automatic classification, music and audio sync dissemination and etc. This paper first has a brief description of OMR research and focuses on describing the research of Chinese OMR literature, it represents the research status and results in China, then the paper pointes out that the target of OMR research in China must tend to Chinese traditional musical score image processing and pattern recognition.

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Periodical:

Advanced Materials Research (Volumes 225-226)

Pages:

223-227

DOI:

https://doi.org/10.4028/www.scientific.net/AMR.225-226.223

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Cite this paper

Online since:

April 2011

Authors:

Gen Fang Chen, Wen Jun Zhang

Keywords:

Chinese Traditional Music, Image Processing, Musical Score, Optical Music Recognition, Pattern Recognition

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© 2011 Trans Tech Publications Ltd. All Rights Reserved

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[1] Pruslin, D.H. Automated Recognition of Sheet Music. Doctor of Science dissertation, MIT. (1966).

[2] Kia Ng, et al. CIMS: Coding Images of Music Sheets", The Interactive-Music Network, unpublished.

[3] Fujinaga, I. Optical music recognition using projections. M. A: Thesis. (1988).

[4] Modayur, B. R., et al. MUSER-a prototype musical recognition system using mathematical morphology. Intelligent Systems Laboratory, EE Dept, FT-10: University of Washington. (1992).

[5] Watkins, G. A fuzzy syntactic approach to recognising hand-written music., Proceedings of the International Computer Music Conference. (1994), pp.297-302.

[6] Yoda, I., K. Yamamoto, et al. Automatic construction of recognition procedures for musical notes by genetic algorithm,. International Association for Pattern Recognition Workshop on Document Analysis Systems. World Scientific. (1995)., pp.225-36.

[7] Stückelberg M.V. Musical score recognition using probabilistic inference, UM. (1999).

[8] Stückelberg, M. V., C. Pellegrini, et al. An architecture for musical score recognition using highlevel domain knowledge., Proceedings of the Fourth International Conference on Document Analysis and Recognition 2. (1997), pp.813-8.

DOI: 10.1109/icdar.1997.620624

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

[10] Fujinaga, I., S. Moore, et al. Implementation of exemplar-based learning model for music cognition. Music, mind and science. S. W. Yi. Seoul, Seoul National University Press. (1999).

[11] Fahmy, H., A graph-grammar approach to high-level music recognition, Department of Computing and Information Science. Kingston, Ontario, Canada, Queen's University. (1991).

[12] Huang Zhipeng. An overview of China's electronic music disciplines. Music Research. No. 2 (2008).

[13] http: /www. cnki. net/, unpublished.

[14] Wang Linquan, Zhang Wenyi and Zheng Gang. Music recognization system by region feature. Journal of Software. Vol. 5 No. 11.

[15] Wang Linquan, Zhang Wenyi , Zheng Gang. Preprocessing and measuring environment parameter for computer to recognize music. Computer Engineering. Vol. 21 No. 1, (1995).

[16] Zhang Dengsheng, Li Haizhou. The study of music image recognition. Journal of Anqing Normal College. No. 3 Vol. 1 (1995).

[17] Zhang Dengsheng, Li Haizho. A recognition system for printed music score based on projection method. Pattern Recognition and Artificial Intelligence，Vol. 8 No. A01 (1995), pp.106-111.

[18] Zhang Dengsheng. Image data acquisition from printed-music by PC. Journal of Anqing Normal College No. 1 (1996).

[19] Zhang Dengsheng, Zhang Ling, Li Haizhou. Automatic recognition and recover of printed-music. Journal of Anqing Normal College. Vol. 2 No. 3 (1996).

[20] Zhang Dengsheng, Zhou Yuezhen. Image pre-processing for music recognition. Journal of Anqing Normal College. Vol. 3 No. 2 (1997).

[21] Zhang Dengsheng, Ma Songde, Music recognition system based on sentence structure rules, Journal of Anqing Normal College. Vol. 3 No. 3, (1997).

[22] Zhang Dengsheng, Xu Binzheng, Ma Songde, Structure split and image recover for music recognition, Journal of Data Acquisition & Processing. Vol. 12 No. 3 (1997).

[23] Zhang Dengsheng，Ma Songde. A recognition system of multi-voice music staff. Computer Engineering. Vol. 24 No. 3, (1998).

[24] Liu Xiaoxiang, Zhang Shusheng, Wang Peng, Digital music library and the optical music recognition, Journal of Academic Libraries, Vol. 20 No. 5 (2002).

[25] Liu Xiaoxiang, Zhang Shusheng, Wang Jin, ZhuYuzhang, Computer optical music recognition, Computer Engineering, Vol. 29 No. 2 (2003).

[26] Liu Xiaoxiang, Zhang Shusheng, Wang Jin, Staff lines detection and remove for music image[J], Journal of Image and Graphics，(2003)，8(zl): 1-5.

[27] Chen Genfang, OMR Research and Prototype Design[D], Dissertation for Master of Engineering in Zhejiang University, (2003), pp.53-54.

[28] LIU Xiaoxiang, ZHANG Shusheng, WANG Jing, WANG Peng, A fast algorithm for music score image skew detection, Computer Engineering, Vol. 30 No. 2 (2004).

[29] Chen Genfang, A new approach to recognition oblique musical score based on detecting of direction number, Journal of Hangzhou Teachers College, Vol. 3 No. 2 (2004).

[30] Liu Xiaoxiang, Zhang Shusheng, A fast and robust approach to detect and remove staff lines from music score image, Computer Engineering and Application，No. 25 (2004).

[31] Jin Yongtang, Zhu Penghua. Computer Optical Music Recognition, DA ZHONG KE JI. Cumulatively No. 8 (2005), pp.96-07.

[32] Liu Xiaoxiang, Optical Music Recognition and Implement [D], Dissertation for Doctor of Engineering in Northwestern Polytechnical University. (2006).

[33] JIANG Yi-nv, ZHANG Yin, ZHANG San-yuan, Research of numbered musical notation recognition method, Computer Engineering and Application, No. 32 (2006), pp.204-206.

[34] Jiang Yi-nv. Research of Numbered Musical Notation Recognition [D], Dissertation for Master of Engineering in Zhejiang University (2006).

[35] CHEN Genfang, ZHANG Wenjun, Music iImage matching algorithm based on OMR technique, Computer Engineering. Vol. 33 No. 7, (2007), pp.169-171.

[36] MA YEQIAN, LI CHANGHU. Research and application of the purgation on musical note. CONTROL & AUTOMATION. Vol. 23 No. 12-1, (2007).

[37] Chen Genfang, ZhangWenjun, The musical information extraction from digital musical score based on mathematical morphology and musical notation, Computer App lications and Software, ISSN1000-386X*CN31-1260/TP , Vol. 25 No. 8, (2008). 8.

DOI: 10.1109/etcs.2009.261

[38] Chen Genfang, ZHANGWenjun, Watermarking algorithm for embedding MIDI information into digital music score, Journal of Shanghai University. Vol. 14 No. 2, (2008): 125-129.

[39] WANG Yufeng, ZHAO Li, Researches on music segmentation technology of OMR, Sciencepaper Online. Vol. 4 No. 2, (2009): 109-114.

[40] LIU Xiao-xiang, ZHANG Shu-sheng, Structure analysis approach of music notes for optical music recognition, Computer Engineering and Design, (2009), 30(3): 709-713.

[41] LIU Xiao –xiang, Primitives extraction of music notes in multi -voice scores, , Computer Engineering and Applications. Computer Engineering and Applications, (2009), 45(4): 186-189.