A shortest path approach for staff line detection

• Type: Article in International Conference Proceedings Book
• Date: 2007

Authors

Ana Rebelo (Author) Other; Artur Capela (Author) Other; Joaquim F Pinto da Costa (Author) FCUP; Carlos Guedes (Author) Other; Eurico Carrapatoso (Author) FEUP; Jaime S Cardoso (Author) FEUP

Conference proceedings International

Title: AXMEDIS 2007: THIRD INTERNATIONAL CONFERENCE ON AUTOMATED PRODUCTION OF CROSS MEDIA CONTENT FOR MULTI-CHANNEL DISTRIBUTION, PROCEEDINGS

Pages: 79-85

3rd International Conference on Automated Production of Cross Media Content for Multi-Channel Distribution

Barcelona, SPAIN, NOV 28-30, 2007

Indexing

ISI Web of Knowledge - 8 Citations

Scopus - 12 Citations

Scientific classification

CORDIS: Technological sciences > Technology > Computer technology

FOS: Natural sciences > Computer and information sciences

Other information

Authenticus ID: P-004-CKG

DOI: 10.1109/axmedis.2007.16

Abstract (EN): Many music works produced in the past still exist only as original manuscripts or as photocopies. Preserving them entails their digitalization and consequent accessibility in a digital format easy-to-manage. The manual process to carry out this task is very time consuming and error prone. Optical music recognition (OMR) is a form of structured document image analysis where music symbols are isolated and identified so that the music can be conveniently processed. While OMR systems perform well on printed scores, current methods for reading handwritten musical scores by computers remain far from ideal. One of the fundamental stages of this process is the staff line detection. In this paper a new method for the automatic detection of music stave lines based on a shortest path approach is presented. Lines with some curvature, discontinuities, and inclination are robustly detected. The proposed algorithm behaves favourably when compared experimentally with well-established algorithms.

Language: English

Type (Professor's evaluation): Scientific

No. of pages: 7