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JACIII Vol.23 No.4 pp. 782-790
doi: 10.20965/jaciii.2019.p0782
(2019)

Paper:

Real-Time Optical Music Recognition System for Dulcimer Musical Robot

Zhe Xiao*,**, Xin Chen*,**,†, and Li Zhou***

*School of Automation, China University of Geosciences
No.388 Lumo Road, Hongshan District, Wuhan 430074, China

**Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems
No.388 Lumo Road, Hongshan District, Wuhan 430074, China

***School of Arts and Communication, China University of Geosciences
No.388 Lumo Road, Hongshan District, Wuhan 430074, China

Corresponding author

Received:
February 19, 2019
Accepted:
March 29, 2019
Published:
July 20, 2019
Keywords:
musical robot, OMR, notation recognition, staff line removal, shape model descriptor
Abstract

Traditional optical music recognition (OMR) is an important technology that automatically recognizes scanned paper music sheets. In this study, traditional OMR is combined with robotics, and a real-time OMR system for a dulcimer musical robot is proposed. This system gives the musical robot a stronger ability to perceive and understand music. The proposed OMR system can read music scores, and the recognized information is converted into a standard electronic music file for the dulcimer musical robot, thus achieving real-time performance. During the recognition steps, we treat note groups and isolated notes separately. Specially structured note groups are identified by primitive decomposition and structural analysis. The note groups are decomposed into three fundamental elements: note stem, note head, and note beams. Isolated music symbols are recognized based on shape model descriptors. We conduct tests on real pictures taken live by a camera. The tests show that the proposed method has a higher recognition rate.

Cite this article as:
Z. Xiao, X. Chen, and L. Zhou, “Real-Time Optical Music Recognition System for Dulcimer Musical Robot,” J. Adv. Comput. Intell. Intell. Inform., Vol.23, No.4, pp. 782-790, 2019.
Data files:
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Last updated on Nov. 18, 2019