An Interchange Format for Optical Music Recognition Applications

Proceedings First International Conference on WEB Delivering of Music. WEDELMUSIC 2001, 2001

2015

Optical music recognition (OMR) is the task of recognizing images of musical scores. In this paper, improved algorithms for the first steps of optical music recognition were developed, which facilitated bulk annotation of scanned scores for use in an interactive score display system. Creating an initial annotation by OMR and verifying by hand substantially reduced the manual effort required to process scanned scores to be used in a live performance setting.

Computers and the Humanities, 2001

Abstract. This article describes the challenges posed by optical music recognition – a topic in com-puter science that aims to convert scanned pages of music into an on-line format. First, the problem is described; then a generalised framework for software is presented that ...

1991

This thesis describes a program which translates a digitized image of a music score into a representation more amenable to computer manipulation of the musical content. I aim for a representation in which the information manifest on a sheet of music is easily accessible, information such as: the key signature, the pitches and durations of notes, and dynamic markings associated with parts of the score. The program is designed to read music printed by a single publisher, in a single musical font. Throughout the thesis I will comment on the issues and feasibility of extending this work to other fonts and publishers. This work is done for the most part using a Connection Machine, a data parallel computer.

2012

For centuries, music has been shared and remembered by two traditions: aural transmission and in the form of written documents normally called musical scores. Many of these scores exist in the form of unpublished manuscripts and hence they are in danger of being lost through the normal ravages of time. To preserve the music some form of typesetting or, ideally, a computer system that can automatically decode the symbolic images and create new scores is required. Programs analogous to optical character recognition systems called optical music recognition (OMR) systems have been under intensive development for many years. However, the results to date are far from ideal. Each of the proposed methods emphasizes different properties and therefore makes it difficult to effectively evaluate its competitive advantages. This article provides an overview of the literature concerning the automatic analysis of images of printed and handwritten musical scores. For self-containment and for the benefit of the reader, an introduction to OMR processing systems precedes the literature overview. The following study presents a reference scheme for any researcher wanting to compare new OMR algorithms against well-known ones.

2011

Given a scanned score page, Optical Music Recognition (OMR) attempts to reconstruct all contained music information. However, the available OMR systems lack the ability to recognize transposition information contained in complex orchestral scores. 1 An additional unsolved OMR problem is the handling of orchestral scores using compressed notation. 2 Here, the information of which instrument has to play which staff is crucial for a correct interpretation of the score. But this mapping is lost along the pages of the score during the OMR process. In this paper, we present a method for retrieving the instrumentation and transposition information of orchestral scores. In our approach, we combine the results of Optical Character Recognition (OCR) and OMR to regain the information available through text annotations of the score. In addition, a method to reconstruct the instrument and transposition information for staves where text annotations were omitted or not recognized is presented. In an evaluation we analyze the impact of transposition information on the quality of score-audio synchronizations of orchestral music. The results show that the knowledge of transposing instruments improves the synchronization accuracy and that our method helps in regaining this knowledge.

1994

Proceedings of the 6th …, 2009

The systems for music score recognition are traditionally called Optical Music Recognition (OMR) systems. We have developed an OMR system called “COMSCAN” that takes an electronically printed sheet of musical notes and processes it by using the four basic steps usually used by almost all OMR systems for the recognition of musical notes. In this paper, the COMSCAN OMR system presented is fully based on our three proposed algorithms. First algorithm is for stave line detection which is a new form of horizontal projection and second algorithm called “averaging”, is for the stave line removal. This is done immediately after the stave line detection. The third algorithm is for musical note symbol identification/recognition step. It is an enhanced form of template matching technique. After the detailed description of the working of COMSCAN and the proposed algorithms, results are reported to analyze the efficiency and accuracy of proposed system. Finally, the comparison is done with the system that uses an algorithm of adding more stave lines instead of removing them.

International Journal of Contents, 2014

In this paper, we propose a smart system that can optically recognize a music score within a document and can play the music after recognition. Many historic handwritten documents have now been digitalized. Converting images of a music score within documents into digital files is particularly difficult and requires considerable resources because a music score consists of a 2D structure with both staff lines and symbols. The proposed system takes an input image using a mobile device equipped with a camera module, and the image is optimized via preprocessing. Binarization, music sheet correction, staff line recognition, vertical line detection, note recognition, and symbol recognition processing are then applied, and a music file is generated in an XML format. The Music XML file is recorded as digital information, and based on that file, we can modify the result, logically correct errors, and finally generate a MIDI file. Our system reduces misrecognition, and a wider range of music score can be recognized because we have implemented distortion correction and vertical line detection. We show that the proposed method is practical, and that is has potential for wide application through an experiment with a variety of music scores.

Proceedings ISMIR …, 2000

An adaptive optical music recognition system is being adapted as part of an experiment in developing a comprehensive framework of tools to manage the workflow of large-scale digitization projects. This framework will not only support the path from physical object and/or digitized material into a digital library repository, it will also offer effective tools for incorporating metadata and perusing the content of the resulting multimedia objects.