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A Shortest Path Approach for Staff Line Detection

机译:员工线路检测最短路径方法

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Many music works produced in the past still exist only as original manuscripts or as photocopies. Preserving them entails their digitalization and consequent accessibility in a digital format easy-to-manage. The manual process to carry out this task is very time consuming and error prone. Optical music recognition (OMR) is a form of structured document image analysis where music symbols are isolated and identified so that the music can be conveniently processed. While OMR systems perform well on printed scores, current methods for reading handwritten musical scores by computers remain far from ideal. One of the fundamental stages of this process is the staff line detection. In this paper a new method for the automatic detection of music stave lines based on a shortest path approach is presented. Lines with some curvature, discontinuities, and inclination are robustly detected. The proposed algorithm behaves favourably when compared experimentally with well-established algorithms.
机译:过去产生的许多音乐作品仍然只存在于原稿或作为复印件中。保留它们以易于管理的数字格式为数字化和后续可访问性。执行此任务的手动过程非常耗时和易于错误。光学音乐识别(OMR)是结构化文档图像分析的一种形式,其中隔离和识别音乐符号,以便可以方便地处理音乐。虽然OMR系统对印刷成绩进行了良好,但电脑通过计算机读取手写音乐评分的当前方法仍然远离理想。这个过程的基本阶段之一是员工线路检测。本文介绍了一种基于最短路径方法自动检测音乐塔里线的新方法。鲁棒地检测到具有一些曲率,不连续性和倾斜的线。当实验比较时,所提出的算法在实验与良好的算法进行比较时的表现得很好。

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