针对不同质量的手写乐谱扫描,有效的谱线检测、恢复和去除方法

Fatemeh Alirezazadeh, M. Ahmadzadeh
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引用次数: 4

摘要

五线谱的检测和去除是光学音乐识别(OMR)系统中最重要的预处理步骤之一。本文提出了一种从乐谱的全局信息中提取和还原五线谱的新方法。首先确定员工线的位置。因此,音乐人员是切片的。在每个切片上识别工作线段,然后在充分了解工作线段位置的情况下,可以重建变形、中断或部分移除的工作线段。本文提出了一种基于去除所有检测到的五线谱的五线谱去除算法。最后,利用傅里叶变换和高斯低通滤波器对分离和中断的信号进行重构。该方法已在ICDAR 2012下举办的曲谱移除比赛数据集上进行了测试。实验结果表明,该方法在各种线材变形情况下是有效的。关键词:傅里叶变换,高斯低通滤波器,光学音乐识别,行长编码,五线谱去除。
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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.
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