本研究之目的在於辨識印刷鋼琴樂譜文件，以架構一個具有彈性的辨識系統為主要方向，在整體的速度與辨識效率上，能夠達到不錯的效果。系統主要包含兩個部分：一為影像處理部分，另一為樂理輔助辨識與編輯部分。主要方法有：採用改良後的 Hough Transform 來分析影像傾斜度與擷取五線譜譜線；以及利用 Gray-Level Rotation 方式取得較佳之傾斜校正影像；經由分析音符的特性之後，採用了投影法與特徵分析來辨識音符，並結合基礎樂理與和聲學來輔助辨識，最後透過一個編輯系統輔助使用者訂正辨識結果，建立起一個快速又有效率的辨識系統。實驗中採用了三家不同印刷公司的十三首曲目，總計共有164個五線譜、1883個樂符及1979個音高。辨識的樣本分別採用了100 dpi、150 dpi 及 300 dpi三種解析度，實驗結果顯示一張A4大小的樂譜在100 dpi時，一分鐘內可辨識完成，且達到91.2%的辨識率；而150 dpi則需時約兩分鐘，辨識率為92.5%；300 dpi 則需時約十分鐘，辨識率為93.4%。針對不同複雜度的印刷樂譜，程式則會自動判斷，並建議使用者採用何種解析度進行辨識，以提升辨識效率。針對樂譜辨識，本研究提供了一個提升辨識速度，且兼顧辨識率的典範。此外，輔助訂正辨識結果的編輯器，則會使得整個辨識系統更為完整，且具有彈性。

This paper addresses the problem of taking printed sheet music and translating it into a MIDI format computer file. The automatic optical music score recognition system provides a more efficient and convenient approach of converting printed sheet music into MIDI file. The system recognizes music scores in a two-step process: (1) music symbol detection phase, which obtains a digitized image of the sheet music and recognizes the musical notations in the digitized image; and (2) music symbol emendation phase, which uses musical knowledge to correct the mis-identified musical symbols and then outputs the result to a pre-defined intermediary format file. The output file contains information of music symbols and confidence level values, these information could be displayed through a musical editor system developed for this research.Position and scale of the sheet music on the scanner is not restricted. After analyzing the sheet music, most of the music symbols could be recognized with only single image processing techniques. The experiments show a 91.2% recognition rate is achievable at 100 dpi taking approximately 1 minute per page. At 150 dpi, it is about 92.5% with an average processing time of 2 minute per page. At 300 dpi, the recognition rate is raised to 93.4% with an average processing time of 10 minute per page.