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研究生:蔡顏丞
研究生(外文):Yen-Cheng Tsai
論文名稱:動態邊界偵測在微陣列影像上的分析
論文名稱(外文):Microarray Image Analysis by Active Contour Models
指導教授:白敦文
指導教授(外文):Tun-Wen Pai
學位類別:碩士
校院名稱:國立海洋大學
系所名稱:資訊科學學系
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:2003
畢業學年度:90
語文別:中文
論文頁數:88
中文關鍵詞:微陣列動態邊界偵測臨界值膨脹腐蝕初始輪廓
外文關鍵詞:microarrayactive contour modelthresholddilateerodedefault contour
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  • 被引用被引用:0
  • 點閱點閱:167
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摘要
在本論文中,我們提供一套可以動態偵測物件邊界的組合模組,用以分割微陣列影像中的各種實驗反應,在影像分析的系統中,主要透過將Snake演算法配合影像前置處理技術來進行適應性的邊界輪廓擷取。
為了正確地偵測影像訊號與繪出物件輪廓,我們提供適當的影像前置處理技術且在動態偵測邊界能量最小化的過程中,我們依照影像本身特性產生需要的參數權重。在Snake最佳化方面,我們提出一種增進效率及效能的方法,運用前置影像處理程式的動態計算,包括臨界值選取、參數的調整、輪廓形變追蹤等,產生各別不同的初始輪廓線,使Snake在自動收斂的過程中能夠得到較佳的偵測效果。
本論文也使用了實際的微陣列晶片實體影像進行測試,實驗的結果顯示我們所建議的系統,在邊界偵測的追蹤上,展現出高效能與許多令人期待的研究成果。

Abstract
A framework for segmenting multiple objects in an image based on deformable contours is proposed for Microarray Image Analysis. In this framework , image pre-processing techniques are designed prior to Snake algorithms to detect the boundary of each responsing image adaptively .
The image preprocessing models for initial parameters of Active Contour Models are introduced to enhance the signals and removed the noises from a degraded image. We generate these necessary weighting parameters for energy minimization. These approaching methodology for snake optimization based on adaptive programming are discussed in this thsis which include thresholding , modifying values , and contour tracing of an object.
Comprehensive experiments are performed and comparisons are made between individual energy based methods . results show highly encouraging and are able to provide many potential applications in a variety of tracking scenarios.

論文口試委員-------------------------------------------------I
中文摘要 ---------------------------------------------------II
英文摘要 --------------------------------------------------III
目錄 --------------------------------------------------IV
圖目錄 --------------------------------------------------VII
表目錄 ---------------------------------------------------IX
第一章.序論 ------------------------------------------1
1.1 研究動機 ------------------------------------------1
1.2 相關文獻 ------------------------------------------2
1.3 章節提要 ------------------------------------------3
第二章. 微陣列影像分割 ----------------------------------6
2.1 微陣列影像結構與成像原理 -------------------------7
2.2 傳統影像分割 ---------------------------------11
2.2.1 Histogram Equalization演算法 ---------------11
2.2.2 Region Growing(區域成長) ------------------------15
2.2.3 Sobel Operator ---------------------------------16
2.3 影像前置處理與初始輪廓之偵測 ---------------19
2.3.1 變異數影像(Variance Map) ------------------------19
2.3.2 臨界值選取(Thresholding) ------------------------23
2.3.3 Dilate、Erode演算法 ------------------------27
2.3.4 Boundary Tracing(邊界描繪) ---------------30
第三章. 微陣列影像分析 ---------------------------------33
3.1 動態邊界偵測簡介 ---------------------------------33
3.2 影像分割與初始點位置 ------------------------42
3.3 參數的調整與影響 ---------------------------------45
第四章. 系統概述與實驗結果 ---------------------------------49
4.1 系統概述 ------------------------------------------49
4.2 影像合成實驗 ---------------------------------53
4.3 微陣列影像實驗 ---------------------------------56
4.3.1微陣列影像分割 ---------------------------------56
4.3.2輪廓形變追蹤 ------------------------------------------63
第五章. 結論及未來展望 ---------------------------------68
5.1 結論 ------------------------------------------68
5.2 未來展望 ------------------------------------------69
參考文獻. ---------------------------------------------------71
附錄一. ------------------------------------------75

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