Musical Pitch Alphabets Generator Using Haar-like Feature

Abstract

Optical Music Recognition (OMR) has become a study trend with the increasing demand for digital sheet music. In this paper, we explore techniques and algorithms to implement optical music recognition. This paper aims to encourage people who just begin and enjoy learning object detection by using a simple and comprehensible framework called Haar-like Feature to detect the music notation. Furthermore, it also assists beginner musicians who have a difficult time in memorizing the music theory and rules by generating musical alphabets. The paper will include the process of how to generate the cascade classifier model and how to imply them to detect the target object.