(3.236.231.61) 您好!臺灣時間:2021/05/15 23:38
字體大小: 字級放大   字級縮小   預設字形  
回查詢結果

詳目顯示:::

我願授權國圖
: 
twitterline
研究生:林文靖
研究生(外文):Wen Ching Lin
論文名稱:樂譜自動辨識之電腦視覺系統設計
論文名稱(外文):A computer vision system for automatic music score recognition
指導教授:陳明揚 
指導教授(外文):Ming-Yang Chern
學位類別:碩士
校院名稱:國立中正大學
系所名稱:電機工程研究所
學門:工程學門
學類:電資工程學類
論文種類:學術論文
論文出版年:2001
畢業學年度:89
語文別:中文
論文頁數:61
中文關鍵詞:光學樂譜辨識簡化的Hough轉換垂直與水平投射模組比對
外文關鍵詞:Optical music recognitionSimplified Hough transformVertical and horizontal projectiontemplate matching
相關次數:
  • 被引用被引用:2
  • 點閱點閱:254
  • 評分評分:
  • 下載下載:0
  • 收藏至我的研究室書目清單書目收藏:1
在本論文中,我們提出了一個辨識樂譜的可靠的程序架構─完整的光學樂譜辨識系統(OMR),在提出架構中所採用的技巧如下:旋轉對應、簡化的Hough轉換、垂直與水平投射、模組比對、符號外觀與音樂的文法,這些技巧將在本論文中詳細的說明,藉由使用與結合這些技巧,我們可以將樂譜中的資訊以及相關的訊息萃取出,實驗結果將在本篇中列出以展示我們所提方式的有效性,同時關於效能以及相關的限制也會在本篇論文中提出。
In this thesis, we propose a robust process architecture---complete optical music recognition (OMR) system, for the recognition of printed music score. Among the techniques employed by the proposed architecture are: rotation mapping, simplified Hough transform, vertical and horizontal projection, template matching, symbol profiles and music grammars. These techniques will be illuminated in details in this thesis. By using and combining with these techniques we can extract all the information and useful knowledge from the music score. Experiment results are shown to demonstrate the effectiveness of the proposed methodology and discussion of its performance and limits are given as well.

目錄
中文摘要 I
英文摘要 II
目錄 III
第一章簡介 ………………………………………………1
1.1 目標與應用 ……………………………………………………1
1.1.1 與編輯樂譜相關的應用層面 …………………………3
1.1.2 與資料收集相關的應用層面 …………………………3
1.1.3 其他的應用層面 …………………………………….4
1.2 與OCR(optical character recognition)的簡略比較 ….4
1.3 常用術語說明 ……………………………………………….6
1.4 音符名稱列表 ……………………………………………….9
1.5 做法簡介 ……………………………………………………10
第二章影像傾斜校正 ………………………………….12
2.1 影像傾斜角度偵測 …………………………………………13
2.2 圖像旋轉修正 ………………………………………………15
第三章五線譜之偵測 ………………………………….21
3.1 五線譜偵測之相關探討 ……………………………………22
3.2 五線譜之區域偵測 …………………………………………26
3.3 五線譜譜線偵測 ……………………………………………28
3.4 五線譜譜線消除 ……………………………………………31
第四章音符辨識與整合輸出 ………………………….36
4.1 相關音符辨識技巧簡介 ……………………………………36
4.2 符號之區域偵測 ……………………………………………41
4.3 符號辨識法則 ………………………………………………43
4.3.1 偵測小節線 ………………………………………….43
4.3.2 音符記號辨識 ……………………………………….44
4.3.3 辨識屬性符號 ……………………………………….47
4.4 辨識整合 ……………………………………………………48
第五章實驗結果與討論 ……………………………….50
5.1 系統需求 ……………………………………………………50
5.2 影像傾斜修正之實驗結果………………………………….51
5.3 五線譜譜線偵測與消除之實驗結果……………………….53
5.4 符號區域偵測之實驗結果 …………………………………56
5.5 辨識結果輸出 ………………………………………………57
5.6 效能分析 ……………………………………………………58
第六章結論 .……………………………………………61
參考文獻

[1]. D. Blostein, H.S. Baird, “A Critical Survey of Music Image Analysis,” Structured Document Image Analysis, Springer Verlag, 1992, pp.405-434.
[2]. H. Kato, S. Inokuchi, “A Recognition System for Printed Piano Music,” Structured Document Image Analysis, Springer Verlag, 1992, pp.435-455.
[3]. I. Leplumey, J. Camillerapp & G. Lorette “A Robust Detector for Music Staves,” Document Analysis and Recognition, Proceedings of the Second International Conference, 1993, pp. 902 —905.
[4]. R. Randriamahefa, J.P. Cocquerez, C.Fluhr, F.Pepin, S.Philipp, “ Printed Music Recognition,” Document Analysis and Recognition, Proceedings of the Second International Conference, 1993, pp. 898 —901.
[5]. Y.S. Wong, A. Choi, “A Two Level Model-Based Object Recognition Technique,” Speech, Image Processing and Neural Networks, Proceedings, ISSIPNN '94, 1994 International Symposium, vol.1, 1994, pp. 319 -322.
[6]. K.T Reed, J.R. Parker, “Automatic Computer Recognition of Printed Music,” Pattern Recognition, Proceedings of the 13th International Conference, vol.3, 1996, pp.803 -807.
[7]. K. Wijaya, D. Bainbridge, “Staff Line Restoration,” Image Processing and Its Applications, 1999. Seventh International Conference, 1999, pp.760 —764.
[8]. S. Marinai, P. Nesi, “Projection Based Segmentation of Musical Sheets,” Document Analysis and Recognition, 1999. ICDAR '99. Proceedings of the Fifth International Conference, 1999, pp. 515 —518.
[9]. S. Baumann, “A Simplified Attributed Graph Grammar for High Level Music Recognition,” Document Analysis and Recognition, 1995, Proceedings of the Third International Conference, vol.2, 1995, pp. 1080 -1083.
[10]. D. Bainbridge, T.C. Bell, “Dealing With Superimposed Objects in Optical Music Recognition,” Image Processing and Its Applications, 1997, Sixth International Conference, vol.2, 1997, pp.756 -760.
[11]. D. Bainbridge, T.C. Bell, “An Extensible Optical Music Recognition System,” Proc. Of The Nineteenth Australasian Computer Science Conference, 1996, pp. 308-317.
[12]. D. Bainbridge, “Optical music recognition: A generalized
approach,” Second New Zealand Computer Science Graduate Conference, 1996.
[13]. S.D. Lee, “Automatic Optical Music Recognition,” 1996 http://www.cs.hku.hk/~sdlee/project.html.
[14]. D. Ballard and C. Brown, “Computer Vision”, Englewood Cliffs. NJ: Prentice- Hall, 1982.
[15]. R.C. Gonzalez, R.E. Woods, “Digital Image Processing”, Addison Wesley, 1992.
[16]. E. Sicard, “An Efficient Method for the Recognition of Printed Music,” Pattern Recognition, 1992. Vol.III. Conference C: Image, Speech and Signal Analysis, Proceedings., 11th IAPR International Conference on , 1992 , pp. 573 —576.
[17]. G.M. Rader, “Creating printed music automatically,” Computer, Volume: 29 Issue: 6, June 1996, pp. 61 —68.

QRCODE
 
 
 
 
 
                                                                                                                                                                                                                                                                                                                                                                                                               
第一頁 上一頁 下一頁 最後一頁 top