14 February 2015 Apply lightweight recognition algorithms in optical music recognition
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Proceedings Volume 9445, Seventh International Conference on Machine Vision (ICMV 2014); 944504 (2015) https://doi.org/10.1117/12.2180715
Event: Seventh International Conference on Machine Vision (ICMV 2014), 2014, Milan, Italy
Abstract
The problems of digitalization and transformation of musical scores into machine-readable format are necessary to be solved since they help people to enjoy music, to learn music, to conserve music sheets, and even to assist music composers. However, the results of existing methods still require improvements for higher accuracy. Therefore, the authors propose lightweight algorithms for Optical Music Recognition to help people to recognize and automatically play musical scores. In our proposal, after removing staff lines and extracting symbols, each music symbol is represented as a grid of identical MN cells, and the features are extracted and classified with multiple lightweight SVM classifiers. Through experiments, the authors find that the size of 10 ∗ 12 cells yields the highest precision value. Experimental results on the dataset consisting of 4929 music symbols taken from 18 modern music sheets in the Synthetic Score Database show that our proposed method is able to classify printed musical scores with accuracy up to 99.56%.
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Viet-Khoi Pham, Viet-Khoi Pham, Hai-Dang Nguyen, Hai-Dang Nguyen, Tung-Anh Nguyen-Khac, Tung-Anh Nguyen-Khac, Minh-Triet Tran, Minh-Triet Tran, } "Apply lightweight recognition algorithms in optical music recognition", Proc. SPIE 9445, Seventh International Conference on Machine Vision (ICMV 2014), 944504 (14 February 2015); doi: 10.1117/12.2180715; https://doi.org/10.1117/12.2180715
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