Goal-Directed Evaluation of Binarization Methods
IEEE Transactions on Pattern Analysis and Machine Intelligence
Adaptive Binarization of Historical Document Images
ICPR '06 Proceedings of the 18th International Conference on Pattern Recognition - Volume 03
Assessing Optical Music Recognition Tools
Computer Music Journal
Optical music recognition for scores written in white mensural notation
Journal on Image and Video Processing - Special issue on image and video processing for cultural heritage
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Optical music recognition (OMR) systems are promising tools for the creation of searchable digital music libraries. Using an adaptive OMR system for early music prints based on hidden Markov models, we leverage an edit distance evaluation metric to improve recognition accuracy. Baseline results are computed with new labeled training and test sets drawn from a diverse group of prints. We present two experiments based on this evaluation technique. The first resulted in a significant improvement to the feature extraction function for these images. The second is a goal-directed comparison of several popular adaptive binarization algorithms, which are often evaluated only subjectively. Accuracy increased by as much as 55% for some pages, and the experiments suggest several avenues for further research.