Effective staff line detection, restoration and removal approach for different quality of scanned handwritten music sheets

Musical staff detection and removal is one of the most important preprocessing steps of an Optical Music Recognition (OMR) system. This paper proposes a new method for detecting and restoring staff lines from global information of music sheets. First of all the location of staff lines is determined. Therefore, music staff is sliced. The staff line segments are recognized at each slice and then with adequate knowledge of staff line locations, the deformed, interrupted or partly removed staff lines can be rebuilt. A new approach for staff removal algorithm is suggested in this paper fundamentally based on removing all detected staff lines. At last, the Fourier transform and Gaussian lowpass filter will help to reconstruct the separated and interrupted symbols. It has been tested on the dataset of the musical staff removal competition held under ICDAR 2012. The experimental results show the effectiveness of this method under various kinds of deformations in staff lines. Keywords: Fourier Transform, Gaussian Low Pass Filter, Optical Music Recognition, Run Length Coding, Staff Line Removal.