Recognition of Printed Music Score
This article describes our implementation of the Optical Music Recognition System (OMR). The system implemented in our project is based on the binary neural network ADAM. ADAM has been used for recognition of music symbols. Preprocessing was implemented by conventional techniques. We decomposed the OMR process into several phases. The results of these phases are summarized.
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- 1.T. Beran, Optical Music Recognition (in Czech), MSc report Department of Computer Science and Engineering Czech Technical University in Prague (1999)Google Scholar
- 2.J. E. Bresenham: Algorithm for Computer Control of a Digital Plotter. IBM Systems Journal 4(1965) 25–30Google Scholar
- 3.J. Gomes and L. Velho: Image Processing for Computer Graphics. (1997) Springer-Verlag New YorkGoogle Scholar
- 4.V. Hlaváč and M. Šonka: Computer vision (in Czech). (1992) Grada PragueGoogle Scholar
- 5.S. E. M. O‘Keefe and J. Austin: Application of an Associative Memory to the Analysis of Document Fax Images. Br. Machine Vision Conference (1994) 315–326Google Scholar
- 6.D. E. Lloyd: Automatic Target Classification Using Moment Invariants of Image Shapes. Technical Report RAE IDN AW126. (1978) Farnborough U.K.Google Scholar
- 7.P. Martin and C. Bellissant: Lowlevel analysis of music drawing images. First International Conference Document Analysis and Recognition (1991) 417–425Google Scholar
- 8.K. C. Ng and R. D. Boyle: Segmentation of Music Primitives. Br. Machine Vision Conference (1990) 345–347Google Scholar
- 9.K. C. Ng and R. D. Boyle: Recognition and Reconstruction of Primitives in Music Scores. Image and Vision Computing 14 (1996) 39–46Google Scholar
- 10.T. W. Ridler and S. Calvard: Picture thresholding using an iterative selection method. IEEE Transaction SMC 8 (1978) 630–632Google Scholar
- 11.M. Roth: An Approach To Recognition Of Printed Music. Eidgenössische Technische Hochschule Zürich, MSc Report (1994)Google Scholar
- 12.M. Šonka, V. Hlaváč and R. Boyle: Image processing, Analysis, and Computer Vision. Chapman & Hall Computing London (1993)Google Scholar