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    首頁> 外文學位 >Tracking and detection of crack patterns using minimal path techniques.
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    Tracking and detection of crack patterns using minimal path techniques.

    機譯:使用最小路徑技術跟蹤和檢測裂紋圖案。

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    摘要

    The research in the thesis investigates the use of minimal path techniques to track and detect cracks, modeled as curves, in critical infrastructure like pavements and bridges. We developed a novel minimal path algorithm to detect curves with complex topology that may have both closed cycles and open sections using an arbitrary point on the curve as the sole input. Specifically, we apply the novel algorithm to three problems: semi-automatic crack detection, detection of continuous cracks for crack sealing applications and detection of crack growth in structures like bridges.;First, we provide the background of the problem of crack detection and critically assess the strengths and limitations of six current algorithms. Detection of cracks in these structures is very challenging because of multiple textures, shadows, variable lighting, irregular background and high noise present in the images, and this motivated our research into minimal path techniques. Next, a background of the minimal path techniques theory is provided. The current state of the art minimal path techniques only work with prior knowledge of either both terminal points or one terminal point plus total length of the curve. For curves with multiple branches, all terminal points need to be known. Therefore, we developed a new algorithm that detects curves and relaxes the necessary user input to one arbitrary point on the curve. The document presents the systematic development of this algorithm in three stages. First, an algorithm that can detect open curves with branches was formulated. Then this algorithm was modified to detect curves that also have closed cycles. Finally, a robust curve detection algorithm was devised that can increase the accuracy of curve detection. The robust algorithm tackles two problems: spurious detection of curve portions and inability to detect complex topological curves that have sharp corners at branches. The algorithm was applied to crack images and the results of crack detection were validated against the ground truth. A new quantification measure called the buffered Hausdorff distance measure was developed for the experimental validation. In addition, the algorithm was also used to detect features like catheter tube and optical nerves in medical images. We finally conclude by giving some future research directions. In particular, the algorithm can be extended to detect higher dimensional curves and the computational speed of the algorithm can be improved by optimizing the use of redundant information.
    機譯:本文的研究調查了在道路和橋梁等關鍵基礎設施中使用最小路徑技術跟蹤和檢測以曲線為模型的裂縫的方法。我們開發了一種新穎的最小路徑算法,可使用曲線上的任意點作為唯一輸入來檢測具有復雜拓撲的曲線,該曲線可能同時具有閉合循環和開放截面。具體來說,我們將新算法應用于三個問題:半自動裂縫檢測,用于裂縫密封應用的連續裂縫檢測以及橋梁等結構中的裂縫增長檢測。首先,我們提供了裂縫檢測問題的背景和關鍵評估六種當前算法的優勢和局限性。由于圖像中存在多種紋理,陰影,可變照明,不規則的背景和高噪聲,因此檢測這些結構中的裂縫非常具有挑戰性,這促使我們對最小路徑技術進行了研究。接下來,提供了最小路徑技術理論的背景?,F有技術的最小路徑技術僅在兩個端點或一個端點加上曲線的總長度的先驗知識下起作用。對于具有多個分支的曲線,需要知道所有端點。因此,我們開發了一種新算法,該算法可以檢測曲線并將所需的用戶輸入放到曲線上的任意點。該文件分三個階段介紹了該算法的系統開發。首先,提出了一種可以檢測帶有分支的開放曲線的算法。然后,對該算法進行了修改,以檢測也具有閉合循環的曲線。最后,設計了一種魯棒的曲線檢測算法,可以提高曲線檢測的準確性。健壯的算法解決了兩個問題:曲線部分的虛假檢測和無法檢測在分支處具有尖角的復雜拓撲曲線。將該算法應用于裂紋圖像,并根據地面真實性驗證了裂紋檢測結果。為了進行實驗驗證,開發了一種稱為量化的Hausdorff距離度量的新量化度量。此外,該算法還用于檢測醫學圖像中的特征,例如導管和光學神經。最后,我們給出了一些未來的研究方向。特別地,該算法可以擴展為檢測更高維度的曲線,并且可以通過優化冗余信息的使用來提高算法的計算速度。

    著錄項

    • 作者

      Kaul, Vivek.;

    • 作者單位

      Georgia Institute of Technology.;

    • 授予單位 Georgia Institute of Technology.;
    • 學科 Engineering Civil.;Engineering Electronics and Electrical.
    • 學位 Ph.D.
    • 年度 2010
    • 頁碼 114 p.
    • 總頁數 114
    • 原文格式 PDF
    • 正文語種 eng
    • 中圖分類
    • 關鍵詞

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