Name
Abstract | ||
|---|---|---|
Optical Music Recognition (OMR) is a technique for converting printed musical documents into computer readable formats. In this paper, we present a simple OMR system that can perform well for ordinary musical documents such as ballad and pop music. This system is constructed based on fundamental image processing and pattern recognition techniques, thus it is easy to implement. Moreover, this system has a strong capability in skew restoration and inverted musical score detection. From a series of experiments, the error for our skew restoration is below 0.2 degrees for any possible document rotation and the accuracy of inverted musical score detection is up to 98.89%. The overall recognition accuracy of our OMR can achieve to nearly 97%, a figure comparable with current commercial OMR software. However, if taking into image skew into consideration, our system is superior to commercial software in terms of recognition accuracy. |
Year | DOI | Venue |
|---|---|---|
2013 | 10.1142/S0218001413530054 | INTERNATIONAL JOURNAL OF PATTERN RECOGNITION AND ARTIFICIAL INTELLIGENCE |
Keywords | Field | DocType |
OMR, skew restoration, inverted musical score detection | Optical music recognition,Computer vision,Musical,Image processing,Commercial software,Speech recognition,Software,Popular music,Artificial intelligence,Skew,Mathematics | Journal |
Volume | Issue | ISSN |
27 | 7 | 0218-0014 |
Citations | PageRank | References |
1 | 0.37 | 7 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Yung-sheng Chen | 1 | 726 | 84.83 |
| Feng-Sheng Chen | 2 | 174 | 8.31 |
| Chin-Hung Teng | 3 | 93 | 11.19 |