The Design and Implementation of Automatic Optical Recognition for Printed Music Score

碩士 === 明新科技大學 === 精密機電工程研究所 === 100 === In recent years, service robots are widely used in difference fields. Entertainment has become an important issue for robot applications. Automatic recognition of music score must immediately offer the music information to the entertainment robot for playing m...

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Bibliographic Details
Main Author: 賴明杰
Other Authors: 戴任詔
Format: Others
Language:zh-TW
Published: 2011
Online Access:http://ndltd.ncl.edu.tw/handle/11784642316987461377
Description
Summary:碩士 === 明新科技大學 === 精密機電工程研究所 === 100 === In recent years, service robots are widely used in difference fields. Entertainment has become an important issue for robot applications. Automatic recognition of music score must immediately offer the music information to the entertainment robot for playing music instruments in real time mode. This study proposes an approach to extract the music information from camera-captured music score. The system uses a monochrome progressive scan camera to capture the image of a printed music score. The resolution of the gigabit Ethernet interface camera is 1380 by 1040 pixels. The distance between the sheet music and the camera is about 80 cm. The proposed method consists of four main modules: the search module, the staff recognition module, the note recognition module, and the MIDI output module. The search module employs the connected component labeling algorithm and the projection method to determine the stave's region. The staff determination module can separate the stave's region into treble stave and bass stave by identifying the position of the horizontal staff lines. The note recognition module recognizes the stem and its related note head, scale, tail or beam by examining the vertical projection profile. The MIDI output module presents the recognition results in a MIDI form music score. Experimental studies are conducted to evaluate the performance of the proposed system and results obtained verify its recognition abilities. The recognition time is less than 4 seconds and the accuracy is bigger than 91%. Keywords:Staff recognition, Note recognition, Vertical characteristic.