OcrV1, Main, Exploration, bibRecord, 001404

Development of a written music recognition system using Java and open source technologies

Identifieur interne : 001404 ( Main/Exploration ); précédent : 001403; suivant : 001405

Development of a written music recognition system using Java and open source technologies

Auteurs : Gernot Loibner [Autriche] ; Andreas Schwarzl [Autriche] ; Matthias Kovac [Autriche] ; Dietmar Paulus [Autriche] ; Wolfgang Polzleitner [Autriche]

Source :

Proceedings of SPIE, the International Society for Optical Engineering [ 0277-786X ] ; 2005.

RBID : Pascal:06-0297695

Descripteurs français

Pascal (Inist)
- Robotique, Système ouvert, Langage JAVA, Logiciel libre, Développement logiciel, Texte, Utilisation information, Reconnaissance forme, Reconnaissance caractère, Reconnaissance optique caractère, Génie logiciel, Vision ordinateur, Traitement image, Musique, Système temporisé, Détection adaptative, Détection seuil, Méthode adaptative, ..
Wicri :
- topic : Robotique, Génie logiciel, Musique.

English descriptors

KwdEn :
- Adaptive detection, Adaptive method, Character recognition, Computer vision, Image processing, Information use, JAVA language, Music, Open source software, Open systems, Optical character recognition, Pattern recognition, Robotics, Software development, Software engineering, Text, Threshold detection, Timed system.

Abstract

We report on the development of a software system to recognize and interpret printed music. The overall goal is to scan printed music sheets, analyze and recognize the notes, timing, and written text, and derive the all necessary information to use the computers MIDI sound system to play the music. This function is primarily useful for musicians who want to digitize printed music for editing purposes. There exist a number of commercial systems that offer such a functionality. However, on testing these systems, we were astonished on how weak they behave in their pattern recognition parts. Although we submitted very clear and rather flawless scanning input, none of these systems was able to e.g. recognize all notes, staff lines, and systems. They all require a high degree of interaction, post-processing, and editing to get a decent digital version of the hard copy material. In this paper we focus on the pattern recognition area. In a first approach we tested more or less standard methods of adaptive thresholding, blob detection, line detection, and comer detection to find the notes, staff lines, and candidate objects subject to OCR. Many of the objects on this type of material can be learned in a training phase. None of the commercial systems we saw offers the option to train special characters or unusual signatures. A second goal in this project is to use a modern software engineering platform. We were interested in how well Java and open source technologies are suitable for pattern recognition and machine vision. The scanning of music served as a case-study.

Affiliations:

Autriche

Links toward previous steps (curation, corpus...)

to stream PascalFrancis, to step Corpus: 000384
to stream PascalFrancis, to step Curation: 000402
to stream PascalFrancis, to step Checkpoint: 000417
to stream Main, to step Merge: 001447
to stream Main, to step Curation: 001404

Le document en format XML

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<front><div type="abstract" xml:lang="en">We report on the development of a software system to recognize and interpret printed music. The overall goal is to scan printed music sheets, analyze and recognize the notes, timing, and written text, and derive the all necessary information to use the computers MIDI sound system to play the music. This function is primarily useful for musicians who want to digitize printed music for editing purposes. There exist a number of commercial systems that offer such a functionality. However, on testing these systems, we were astonished on how weak they behave in their pattern recognition parts. Although we submitted very clear and rather flawless scanning input, none of these systems was able to e.g. recognize all notes, staff lines, and systems. They all require a high degree of interaction, post-processing, and editing to get a decent digital version of the hard copy material. In this paper we focus on the pattern recognition area. In a first approach we tested more or less standard methods of adaptive thresholding, blob detection, line detection, and comer detection to find the notes, staff lines, and candidate objects subject to OCR. Many of the objects on this type of material can be learned in a training phase. None of the commercial systems we saw offers the option to train special characters or unusual signatures. A second goal in this project is to use a modern software engineering platform. We were interested in how well Java and open source technologies are suitable for pattern recognition and machine vision. The scanning of music served as a case-study.</div>
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Development of a written music recognition system using Java and open source technologies

Development of a written music recognition system using Java and open source technologies

Source :

Descripteurs français

English descriptors

Abstract

Links toward previous steps (curation, corpus...)

Le document en format XML

Pour manipuler ce document sous Unix (Dilib)

Pour mettre un lien sur cette page dans le réseau Wicri