The goal of an OMR application is to allow the end-user to transcribe a score image into its symbolic counterpart. This opens the door to its further use by many kinds of digital processing such as playback, music edition, searching, republishing, etc.
Audiveris application is built around the tight integration of two main components: an OMR engine and an OMR editor.
The OMR engine combines many techniques, depending on the type of entities to be recognized -- ad-hoc methods for lines, image morphological closing for beams, external OCR for texts, template matching for heads, neural network for all other fixed-size shapes.
Significant progresses have been made, especially regarding poor-quality scores, but experience tells us that 100% recognition ratio is simply out of reach in many cases.
The OMR editor thus comes into play to overcome engine weaknesses in convenient ways. The user can preselect processing switches to adapt the OMR engine before launching transcription of the current score. Then the remaining mistakes can usually be quickly fixed via manual edition of a few music symbols.