形態影像處理已經廣泛的應用在影像處理技術上。但在以循序式運算為主的電腦上做形態運算會花費相當多的時間，而通常此點也較令人難以接受，因應此類問題，透過特殊的影像表示法來替代傳統的方式通常能讓人引出更有效率的演算法則。
　　四分樹資料結構在電腦視覺領域(computer vision)上已有良好的應用，諸如影像分割(segmentation)、影像壓縮等。四分樹由於其階層性組織使的有利於對影像上某特定部份之子影像做處理，故四分樹對集合運算顯的特別方便，而形態影像處理也是以集合運算為基本的運算方式，故其與四分樹的結合將使得形態影像運算更加便利。
　　儘管已有許多的形態影像處理演算法被提出，而且處理的速度也愈來愈快，但在單機上的速度提升畢竟有個極限，如果有大量的影像要處理，處理時間仍會因影像的增加而累積，所以我們採用分散式計算的方法，集結網際網路上的計算資源，以小兵的力量來成就大事業，將工作量分配出去，讓處理工作平行，使得處理的速度能往前繼續大步邁進。

　　Morphological image processing technique has been well applied to many image processing areas. However, its long computation time usually can’t be accepted when run on a general purpose sequential computer. Instead of conventional image data representation, some special data structures have led to the development of efficient algorithms.
　　The quadtree data structure has been well applied to the field of computer vision such as image segmentation and compression. The quadtree with its hierarchical data structure are advantageous due to its ability to focus on the interesting subsets of the data. Thus, the quadtree data structure are particularly convenient for set operations. Therefore, the computation for morphology processing will be facilitated by using the quadtree data structure since the set operations are the basics of the morphology processing.
　　Although many fast morphological image processing methods have been presented, there is still a need for developing a distributed computing architecture for morphological processing. We propose a scheme direct connection for client to client to improve the data transfer efficiency. Also, the image data is compressed by the quadtree for the transmission efficiency. Due to the efficiency of the network connection and data compression, we have established an efficient web-based distributed work station for morphological image processing.

第一章 引言
1-1 研究動機
1-2 相關研究
1-3 主要貢獻
1-4 論文綱要
第二章 系統之概念與設計方法
2-1 系統基本架構
2-2 提供型態影像處理的服務
2-3 使用者提供計算資源
第三章 形態影像學
3-1 簡介
3-2 黑白影像的擴張運算
3-2-1 基本運算定義
3-2-2 擴張運算的定義
3-3 黑白影像的侵蝕運算及性質
3-4 開放及閉鎖運算
第四章 四分樹上的形態運算
4-1 四分樹基本概念
4-2 影像平面座標與四分樹的對應關係
4-2-1 Morton Order與平面x, y座標之互換
4-2-2 四分樹節點在平面上的位置
4-3 四分樹資料結構的表示方式
4-3-1 指標四分樹
4-3-2 非指標四分樹
4-3-3 指標樹和字串樹的比較
4-4 四分樹上的擴張運算
4-4-1 運用四分樹的優點
4-4-2 四分樹所帶來的問題
4-4-3 樹圖案對映演算法介紹
第五章 系統機制之設計與實現
5-1 工作分配原則（動態負載平衡）
5-2 容錯性（Fault Tolerance）
5-3 提供型態影像處理服務之界面
5-4 使用者提供計算資源之界面
第六章 實驗方法與比較
6-1 樹圖案對映法之工作流程
6-2 樹圖案對映法與傳統演算法的比較
6-2-1 執行速度的比較
6-2-2 傳輸時間的比較
6-3 系統實際應用-電路圖檢測
6-4 系統通訊時間測試
6-4-1 減少傳輸路徑
6-4-2 固定通訊時間與非固定通訊時間
6-5 實驗結果討論
第七章 結論
參考文獻

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