Name
Abstract | ||
|---|---|---|
The preservation of musical works produced in the past requires their digitalization and transformation into a machine-readable format. The processing of handwritten musical scores by computers remains far from ideal. One of the fundamental stages to carry out this task is the staff line detection. We investigate a general-purpose, knowledge-free method for the automatic detection of music staff lines based on a stable path approach. Lines affected by curvature, discontinuities, and inclination are robustly detected. Experimental results show that the proposed technique consistently outperforms well-established algorithms. |
Year | DOI | Venue |
|---|---|---|
2009 | 10.1109/TPAMI.2009.34 | IEEE Trans. Pattern Anal. Mach. Intell. |
Keywords | Field | DocType |
robustness,optical character recognition,indexing terms,image analysis,degradation,algorithms,music,machine readable format,writing,documentation,design methodology,artificial intelligence | Optical music recognition,Computer vision,Music information retrieval,Pattern recognition,Musical acoustics,Computer science,Edge detection,Optical character recognition,Image processing,Robustness (computer science),Machine-readable data,Artificial intelligence | Journal |
Volume | Issue | ISSN |
31 | 6 | 0162-8828 |
Citations | PageRank | References |
51 | 3.71 | 6 |
Authors | ||
5 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| J. dos Santos Cardoso | 1 | 51 | 3.71 |
| Artur Capela | 2 | 57 | 5.24 |
| Ana Rebelo | 3 | 183 | 16.21 |
| Carlos Guedes | 4 | 158 | 13.18 |
| Joaquim Pinto Da Costa | 5 | 262 | 14.82 |