近年來由於電腦資訊的普及與進步，使得各種資料的存取漸漸邁向數值化及自動化。地圖的儲存方式也不再受限於傳統的圖紙式地圖而用電腦數值化的方法，使空間資訊朝三維展示的方向進行。因此，使傳統的航空攝影測量漸漸邁向數值攝影測量的領域，其中都市區三維幾何模型（3D City Model）的建置便為數值攝影測量中一個重大的研究。

　　三維幾何模型的建置則需要有完整建物萃取資訊提供後續的工作。而由方位已知的都市區航照影像中，萃取出有意義的三維線段，如建物屋頂的水平線段或斜線段，是協助都市區建物三維幾何模型自動化重建的一個重要步驟。而目前三維線段的獲取主要還是透過影像萃取的二維直線進行處理而得。因為這個原因，使萃取影像線特徵的完整性成為建物重建的一個重要問題。影像線特徵物萃取的不完整不僅無法組成有意義的三維線段，而且會導致之後無法重建完整的建物。

　　由於彩色影像邊緣線偵測的演算法也越漸成熟，因此本研究期望利用彩色影像作為來源資料的處理。希望找尋比黑白影像更加完整的邊緣線段，來補足黑白影像之遺漏，並對不同形式的彩色影像邊緣線偵測的演算法進行比較其之間的差異性。

　　Recently ,due to the popularity and progress of the computer technology, data access become digitized and automatic. Besides, in order to spatial information 3 dimensionally, map data is also in digital form instead of traditional paper-printed map. In order to provide 3D spatial information photogrammetrically, the automatic reconstruction of urban 3D city model is a very important research.

　　The successfulness of reconstruction of 3D city model depends largely on complete extraction of edge information in imgaes. In urban aerial images with known which orientaion, extraction of meaningfull 3D lines, for example, horizontal edges and gable lines of building roofs, is a significant step for the automatic buildings reconstruction in urban area. However, up to now, 3D lines can only be mainly acquired by first extracting 2D lines in images. Thus, the completeness of extraction of 2D line features in images is an essential factor for the successfulness of building reconstruction. Incomplete extraction of 2D of line features could prevent the reconstruction of 3D lines and hence the reconstruction complete buildings.

　　It is generally know that multispectral images have more information than single band images, therefore it is the goal of this paper to investigate the advantages of color images. In expectation that more complete edges could be found from color images than from monochrome images. In additional to that different kinds of algorithm for edge detection of color image are investigated to compare their suitability for practical usage.

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