Title :
Kalman filtering for segment detection: application to music scores analysis
Author :
Andecy, V. Poulain d´ ; Camillerapp, J. ; Leplumey, I.
Author_Institution :
IRISA, Rennes, France
Abstract :
Many symbols in music scores are linear segments. In this context, we designed an extractor of segments. It is robust towards problems of quality within binary images (scale factor, curvature, bias and noises). It is based on Kalman filtering technique. By splitting music scores into layers of detectable symbols and by applying methodically to the defined layers both this extractor and simple rules of classification for the detected segments, we were able to recognize staves, stems, slurs, beams, bar lines, black note heads and then quarters and note groups
Keywords :
optical character recognition; Kalman filtering; bar lines; beams; bias; binary images; black note heads; curvature; linear segments; music scores analysis; noises; scale factor; segment detection; segment extraction; slurs; staves; stems; Detectors; Equations; Filtering; Graphics; Head; Image segmentation; Kalman filters; Multiple signal classification; Noise robustness; Object detection;
Conference_Titel :
Pattern Recognition, 1994. Vol. 1 - Conference A: Computer Vision & Image Processing., Proceedings of the 12th IAPR International Conference on
Conference_Location :
Jerusalem
Print_ISBN :
0-8186-6265-4
DOI :
10.1109/ICPR.1994.576283