Abstract:
For centuries, music has been divided over two traditions in the form of written documents
and aural transmission normally called musical scores. Many of these scores are published in
manuscript form and So they are at risk of being lost over time. The system takes a music
score image as input, segments music symbols after preprocessing the image, then
recognizes their pitch and duration. Finally, MIDI files are generated. Similar to optical
music recognition (OMR) systems, programs similar to optical character recognition systems
have been in intensive development for many years. This thesis provides an overview of
automatic analysis of handwritten music scores. An overview of the literature provides an
overview of OMR processing systems for the benefit of the reader and self-interest. The
OMR system can provide various benefits to the scientific community for an effective and
powerful printed and handwritten music score. We have presented some of the strategies of
OMR utilizing computer vision and deep learning based approaches for music scores and
printed processing.
