Music-Score-Reader (OMR)

Optical music recognition (OMR) has been the subject of research for decades.
An accessible and easy-to-use OMR application could provide an amazing tool for improving the musical education experience.
For example, a novice musician could use such a tool to hear what a selected piece of music should sound like.

Ideally, an OMR, given an image of a simple or complex music sheet, automatically identifies the notes and plays the musical piece.
For this project, the goal is to develop an algorithm to parse music sheet images,

produce the associated annotation, and implement a playback mechanism for the parsed musical notes.
Also handles the orientated images.

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Process Overview

The process is broken down into the following tasks:

0. Preparations for the Process	1. Staff Lines Detection and Removal	2. Segmentation
Detect the image orientation. Remove unwanted margins. Getting Number of staves.	Detect the location of all staff lines. Remove staff lines. Fill in the gaps.	Process row by row. Calculate boundaries for each symbol. Extract Symbol.
3. Symbol Recognition	4. Note Identification	5. Music Transformation
Calculate matching score against training data. Minimum score threshold: 74%. Pick a label with a maximum score.	Calculate centre point coordinate. Compare with staff lines coordinates to get the pitch. Use a recognition label to get the duration.	Generate sound data. Play the song.

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Some Runtime Screenshots

Annotated JingleBells	Annotated TwinkleTwinleLitterStar	Annotated BashSheet
Stave Section with the BarLines	Stafflines Detection	Stave Section with the Stems

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Getting Started

The user has to open the Main.m in order to start the program. In the 10th line, the user has to specify the image path. After setting up correctly the path, the code can be executed.

All the tested images were severally tested, which is provided under the TestCases folder.

After inserting the correct image path into the Main.m and running it, a recognizedScore variable is created, which contains all the necessary information for the music score excluding the dynamics (like the mf and ff) and the accidentals.

The created audio sample is located in the TestCases folder and it is exported with the name GeneratedAudio.wav.

Future Plans

Deploying a stand-alone application (.exe) with a Simple GUI that works dynamically with a large number of score sheets.

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Prerequisites

MATLAB is required in order to run the current project (2017 or later is preferable).

References

• VIP Helping Paper
• Andy Zeng Trial for staff lines detection
• FFT-Based Correlation to Locate Image Features
• Identifying round objects
• Piano key frequencies
• Using Fundamental Frequency to play audio
• Image Orientation
• Text Annotation

Copyrights

• Kareem S. Fathy
• KAN Org.
• FCIS, University of Ain Shams, Egypt