生態農業：農業地景生態監測及復育【土木工程學系楊明德教授】

論文篇名 英文：Morphological segmentation based on edge detection-II for automatic concrete crack measurement
中文：應用基於MSED-II之形態學影像分割於混凝土裂縫
期刊名稱 Computers and Concrete
發表年份,卷數,起迄頁數 2018, 21(6), 727-739
作者 Su, T. C., Yang, M. D.*(楊明德)
DOI 10.12989/cac.2018.21.6.727
中文摘要 裂縫是混凝土劣化的最常見的典型特徵，因此傳統監測和健康評估對於缺失識別並建立適當修復的策略，以延長混凝土結構的使用壽命至關重要。目前，影像分割演算法已應用於基於檢測影像的混凝土結構裂縫分析。提供裂縫資息（包括長度，寬度和面積）的裂縫分割結果有助於檢查人員對混凝土結構進行表面檢查。本研究提出了一種基於邊緣檢測-II（MSED-II）的形態學分割影像演算法，試驗於幾個混凝土路面和建築物表面影像。此外，進行了交叉曲率評估（CCE），一種線性模式的影像分割技術，以評估它們在混凝土裂縫分割中的效率。結果表明，與CCE相比，MSED-II可以提高混凝土裂縫分割的效率。混凝土裂縫的最小面積，長度和寬度測量誤差分別為5.68％，0.23％和0.00％，證明MSED-II對於混凝土裂縫的自動測量是有效的。
英文摘要 Crack is the most common typical feature of concrete deterioration, so routine monitoring and health assessment become essential for identifying failures and to set up an appropriate rehabilitation strategy in order to extend the service life of concrete structures. At present, image segmentation algorithms have been applied to crack analysis based on inspection images of concrete structures. The results of crack segmentation offering crack information, including length, width, and area is helpful to assist inspectors in surface inspection of concrete structures. This study proposed an algorithm of image segmentation enhancement, named morphological segmentation based on edge detection-II (MSED-II), to concrete crack segmentation. Several concrete pavement and building surfaces were imaged as the study materials. In addition, morphological operations followed by cross-curvature evaluation (CCE), an image segmentation technique of linear patterns, were also tested to evaluate their performance in concrete crack segmentation. The result indicates that MSED-II compared to CCE can lead to better quality of concrete crack segmentation. The least area, length, and width measurement errors of the concrete cracks are 5.68%, 0.23%, and 0.00%, respectively, that proves MSED-II effective for automatic measurement of concrete cracks.