• Journal of Information Processing Systems
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• v.11 no.3
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• pp.438-449
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• 2015

Recognition systems for scanned or printed music scores that have been implemented on personal computers have received attention from numerous scientists and have achieved significant results over many years. A modern trend with music scores being captured and played directly on mobile devices has become more interesting to researchers. The limitation of resources and the effects of illumination, distortion, and inclination on input images are still challenges to these recognition systems. In this paper, we introduce a novel approach for recognizing music scores captured by mobile cameras. To reduce the complexity, as well as the computational time of the system, we grouped all of the symbols extracted from music scores into ten main classes. We then applied each major class to SVM to classify the musical symbols separately. The experimental results showed that our proposed method could be applied to real time applications and that its performance is competitive with other methods.

• The Journal of the Korea Contents Association
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• v.7 no.11
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• pp.34-42
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• 2007

In this paper, we propose a staff-line detection and removal algorithm from a music score image obtained by a mobile phone camera. As a preprocessing technique to recognize a music score image, staff-line detection and removal should be efficiently applied to the skewed or curved images. The proposed method detects a staff-line by dividing a staff according to the degree of distortion. The number of division is calculated by dividing a staff repletely until an average of differences of y coordinates in every divided position is smaller than a threshold. Therefore, the number of division can be adaptively estimated according to the degree of the distortion. For an experiment, we make various kinds of images by rotating one from $1^{\circ}\;to\;3^{\circ}$ or curving slightly upward. The results show that the proposed method performed well on the experiment images.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2015.10a
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• pp.949-951
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• 2015

컴퓨터의 활용 범위가 다양화되면서 음악 분야에도 컴퓨터의 역할이 점점 커지고 있다. 기존의 악보 인식 방법들은 대부분 특정 프로그램에서 작성된 악보만 편집과 재생이 가능하고 다른 프로그램에서 작성된 악보는 수정과 재생이 어려운 문제가 있었다. 본 논문에서는 이러한 단점을 보완하여 이미 작성된 악보를 자동으로 인식하고 재생할 수 있는 스마트폰 애플리케이션을 설계하고 구현한다. 스마트폰 소지자는 언제 어디서나 원하는 악보를 획득할 수 있으며, 폰에 내장된 카메라를 이용하여 악보를 인식시킨 후 연주 기능을 이용하여 음악을 즐길 수 있다.

• Journal of Digital Contents Society
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• v.19 no.4
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• pp.829-836
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• 2018

Sheet music is one of the inevitable elements for successful melody interpretation, playing or rendering, and performance, most of performing artists usually utilize a paper sheet music in the cases. However, the paper sheet music can be a one of the reason to degrade the concentration of audiences and artists or entire performing flows. In addition, it might be a weakness to use a paper sheet music in an outside performing place. We propose an electronic sheet music page tuner application, which can overcome these problems, based on a Tablet PC. The proposed page tuner application, which uses the OpenCV to adapt an eye tracking and behavior recognition, can provide an automatical page pass function to the performing artists. We will expect that the proposed application can highly decrease the weakness of paper sheet music.