||Optical music recognition (OMR) allows pages of sheet music to be interpreted by a computer, and converted into a versatile machine-readable format. There are many advantages of such a system. For instance, a soloist could have the computer play an accompaniment for rehearsal; a user could build music database occupying less memory; or a musicologist could make an edition, modification, or print of the captured image.|
Typically, OCR techniques can not be used in music score recognition since music notation presents a two dimensional structure: in a staff the horizontal position denotes different duration for notes and the vertical position defines the height of the note. That the quality or the typesetting of a score is not the same, or some of the man-made factors make many related researches could not process flexibility, or could only recognize with restriction.
The paper covers two fields of knowledge: one is image processing technology, mainly based on projection, which is employed to extract horizontal and vertical line to abridge the recognition field, and morphology, which recognize musical symbols. The other is music metric, which provides the help on the analysis, and corrects the errors after recognizing.
This system divides into three phases. It starts with all the pre-processing that is needed to de-skew input image, which afford to staff line detection and removal. Then, the symbol recognition, detects the vertical and non-vertical line musical symbol respectively, which are combined into a notation to refine by metric. Finally, the results are stored in a musical representation language, which could be converted into the MIDI format and the music can be played on a MIDI synthesizer.
The experiment shows this system could get a satisfied result successfully in short time, and there is no hard-and-fast claim for image resolution.