本論文使用DNA於二維平面的WLC模型建構出自我交叉之DNA於AFM掃描下的影像，以細線化後的數位影像為基礎，分析與歸納9宮格掃瞄視窗中的像素排列組合，建立出所有代表交叉特定圖形之資料庫，使電腦自動化偵測影像中的交叉區域，並辨識出正確的線段交叉走向。大量被辨識出方向的交叉DNA影像加入原始一批無包含交叉的樣本，以費里曼鏈碼及形狀數編碼的方式為基礎[1]，重新計算出更準確的新估測器係數k1～k12，在DNA輪廓長度計算上擁有比過去佳的準確度。本論文所開發之交叉走向辨識演算法可應用推廣至不同形狀、不同型態之長條生物樣本之生醫研究領域中，或任何數位曲線的圖形辨識。

This study analyzes crossing-DNA images acquired from Atomic Force Microscopy (AFM) systems, with a proposed novel method identifying the true direction of DNA self-crossing area, within its image by analyzing and classifying the pixel permutation in a rolling window scanning automation process. A new batch of direction-identied-crossing-DNA-image samples will add to our in-house study group [1] to update an even more accurate set of geometrical modication coefcients (k1～k12) for DNA contour length estimation, based on a Freeman Chain Code segmented shape number methodology.

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