This paper presents an optical music recognition (OMR) system to process the handwritten musical scores of Kunqu\nOpera written in Gong-Che Notation (GCN). First, it introduces the background of Kunqu Opera and GCN. Kunqu\nOpera is one of the oldest forms of musical activity, spanning the sixteenth to eighteenth centuries, and GCN has\nbeen the most popular notation for recording musical works in China since the seventh century. Many Kunqu\nOperas that use GCN are available as original manuscripts or photocopies, and transforming these versions into\na machine-readable format is a pressing need. The OMR system comprises six stages: image pre-processing,\nsegmentation, feature extraction, symbol recognition, musical semantics, and musical instrument digital interface\n(MIDI) representation. This paper focuses on the symbol recognition stage and obtains the musical information\nwith Bayesian, genetic algorithm, and K-nearest neighbor classifiers. The experimental results indicate that symbol\nrecognition for Kunqu Opera''s handwritten musical scores is effective. This work will help to preserve and popularize\nChinese cultural heritage and to store Kunqu Opera scores in a machine-readable format, thereby ensuring the\npossibility of spreading and performing original Kunqu Opera musical scores.
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