臺灣博碩士論文加值系統

擴散曲線是一種新的向量基元，這種基元被繪製時會將圖片上的區域分開，而且可以在曲線兩側定義顏色。這些顏色會從曲線上平滑地向兩側擴散，遂至整張圖片。本論文基於擴散曲線的特性，提出了一個點陣圖向量化的自動化方法。我們從點陣圖中萃取輪廓、顏色及模糊資訊，並轉換成擴散曲線所需要的幾何基元。我們的方法可以將點陣圖轉換成一組擴散曲線，這組擴散曲線所表示的向量圖會很接近原始的點陣圖內容，而且可以很容易地編輯或製作成動畫。

Diffusion curve is a novel vector-based primitive. It partitions the space through which it is drawn and define colors on each side. These colors smoothly diffuse outwards from each side until they cover the entire image. In this thesis, we propose a method to automatically vectorize a raster image. Our method extracts the contour, color and blur attribute from the raster image, and represents the raster image by the geometry primitives of diffusion curves. The vector graphics, which is represented by a set of diffusion curves closely approximates the original image, can be easily edited or animated.

中文摘要 1
ABSTRACT 2
誌謝 3
目錄 4
中英文對照表 6
第一章 緒論 8
第二章 文獻回顧 10
2.1 向量圖形工具 10
2.2 擴散曲線應用 10
第三章 方法 17
3.1 概觀 17
3.2 擴散曲線 18
3.2.1 資料結構 18
3.2.2 顯像方法 18
3.2.2.1 顏色來源 20
3.2.2.2 顏色擴散 21
3.2.2.3 模糊資訊擴散 21
3.2.2.4 綜合結果 22
3.3 輪廓偵測 23
3.3.1 方向梯度量值 23
3.3.2 亮度、顏色及紋理梯度 24
3.3.3 多重解析度的強度組合 26
3.4 輪廓追蹤 27
3.4.1 摩爾鄰居演算法 27
3.4.2 轉換成貝茲樣條曲線 28
3.5 萃取顏色及模糊資訊 29
第四章 結果 31
第五章 貢獻與未來展望 38
5.1 貢獻 38
5.2 未來展望 38
參考資料 40

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