本文提出的測量車相機檢定(camera calibration)是解算相機的內方位元素、相機拍攝的像點系統性偏移向量、測量車上任意兩相機之間的相對方位，並且不使用檢定場而直接使用像點像坐標觀測值與各式物空間條件來解算。

本文的研究目標是匯集及設計出不利用檢定場而能夠應用於測量車(mobile mapping system)相機檢定之方法。利用環境中常見並且能夠使用的條件，如物空間(object space)距離、角度、已知點坐標等。聯合各種物空間條件進行光束法平差以求出相機檢定參數。

實驗結果顯示使用物空間條件檢定測量車相機參數是可行的，使用已知的三種方法─滅點幾何、兩滅點求解內方位元素、以及物空間三軸條件。這三種方法使用同樣的求解條件時(相同的滅點、影像上相同直線段端點像元)得到的相機內方位元素結果相同。本文結合各式物空間條件，如物空間中可用的已知線段長度、角度、物點共平面、垂直條件、水平條件、坐標差值、高程差、已知點位高程以及已知點位坐標等，求解相機檢定參數，並分析檢定成果與精度。本文以物空間已知條件(距離、水平與垂直條件、坐標差值)求解的內方位元素、外方位元素精度分別可達 0.008~0.010mm、 1~13公分、 0.052°~0.211°。
關鍵字：相機檢定、滅點、物空間三軸條件、光束法平差

In this thesis, the camera calibration for a mobile mapping system (MMS) is to determine the interior orientation parameters, field of systematic bias vectors of image point positions, and the relative orientation of arbitrary two cameras on the MMS. Image coordinates of image points and diverse object space conditions are utilized to evaluate the aforementioned parameters without the need on calibration field.

This thesis utilizes four methods for the calibration of cameras on a MMS in which the calibration is done anywhere the MMS stays. The object space conditions such as the known distances, angles or coordinate differences are integrated with bundle adjustment to estimate the parameters of all cameras on a MMS.

Test results show that the proposed object-space-condition method is applicable for calibrating cameras of a MMS. The interior orientation parameters determined by three methods - three-vanishing-point method, two-vanishing-point method, and three-coordinate-axis method - are the same if they use the same set of image points inclusive of vanishing points and end points of vanishing lines. The object-space-condition method integrates different kinds of conditions (such as known lengths, angles, coordinate differences, coordinates, object heights as well as the perpendicular and parallel conditions) in object space to estimate the camera parameters by using the images taken by cameras on a mobile mapping system. The object space conditions adopted in all tests include known distances, coordinate differences, the parallel and perpendicular conditions, and are used to evaluate the precision of interior orientation elements and exterior orientation parameters defined in a local 3D coordinate system, which are about 0.008~0.010mm、 1~13cm、 0.052~0.211 degrees, respectively.
Keyword: Camera Calibration, Vanishing Points, Three-Axes Conditions in Object Space, Bundle Adjustment

王幰彰，2004。滅點偵測之研究－基於θ-直方圖統計分析法。國立成功大學 測量及空間資訊學系，碩士論文。

交通部、內政部，2008。道路交通標誌標線號誌設置規則。2008年6月18日修訂, 2009年8月19日下載自交通部運輸研究所 運輸安全資訊網http://safety.iot.gov.tw/rule/rule2.asp。

陳順宇、鄭碧娥，1998。統計學。華泰書局。

陳連晃，1986。近景攝影測量中以物空間三軸條件取代控制測量之研究。國立成功大學航空測量研究所，碩士論文。

詹黃祥，2001。近景數化影像半自動式混凝土裂縫量測。國立中央大學 土木工程研究所，碩士論文。

劉彥秀，2003。最小二乘模型與影像套合之後續探討。國立成功大學 測量及空間資訊學系，碩士論文。

Baarda W, 1968, “A Testing Procedure for Use in Geodetic Networks”, Netherlands Geodetic Commission, 2(5).

Cantoni, V., Lombardi, L., Porta, M., Sicard, N., 2001, “Vanishing Point Detection: Representation Analysis and New Approaches”, Proceedings of the 11th International Conference on Image Analysis and Processing, 90-94.

Canny, J., 1986, “A Computational Approach to Edge Detection”, Transactions on Pattern Analysis and Machine Intelligence, PAMI-8:679-698.

Douskos, V., Kalisperakis, I., Karras, G., Petsa, E., 2008, ”Fully Automatic Camera Calibration Using Regular Planar Patterns”, The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, XXXVII(B5):21-26.

Erdas, Inc., 2008, IMAGINE Enterprise Editor (IEE) User’s Guide, September 2008, Georgia USA, IEE_User_Guide.pdf.

Gonzalez, R. C. and Woods, R. E., 2002, “Digital Image Processing”, 2nd ed., Prentice Hall.

Grammatikopoulosa, L., Karrasa, G., Petsab, E., 2004, “Camera Calibration Combining Images with Two Vanishing Points”, International Archives of the Photogrammetry, Remote Sensing & Spatial Information Sciences, 35(5):99-104.

Hough, P. V. C., 1962, "Method and Means for Recognizing Complex Patterns", U.S. Patent 3069654.

Kruck, E.J., 2006, “BINGO 5.3 User’s Manual”, Geoinformatics & Photogrammetric Engineering Company, D–73430 Aalen, Germany, Version 5.3, BingoManual_53_English.

Laplace, C., Berg, M., Lai, H., Mandravellos, Y., 1991, “DevC++4.9.9.2”, Free Software Foundation Inc., http://www.bloodshed.net/, Cambridge, Massachusetts, USA.
Meidow, J., 2004, “Calibration of Stationary Cameras by Observing Objects of Equal Heights on A Ground Plane”, The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 1067-1072.

Rother, C., 2002, “A New Approach to Vanishing Point Detection in Architectural Environments”, Image and Vision Computing, 20:647-655.

Shufelt, J. A., 1999, “Performance Evaluation and Analysis of Vanishing Point Detection Techniques”, Transactions on Pattern Analysis and Machine Intelligence, 21(3):282–288.

van den Heuvel, F.A., 1998, “Vanishing Point Detection for Architectural Photogrammetry”, International Archives of Photogrammetry and Remote Sensing, 32(5):652-659.

van den Heuvel, F.A., 1999, “Estimation of Interior Orientation Parameters from Constraints on Line Measurements in A Single Image”, International Archives of Photogrammetry and Remote Sensing, 32( 5W11):81-88.

Wang, L. L. and Tsai, W. H., 1990, “Computing Camera Parameters using Vanishing-Line Information from a Rectangular Parallelepiped”, Machine Vision and Applications, (3):129-141.

Wolf, P. R. and Dewitt, B. A., 2000, “Elements of Photogrammetry with Applications in GIS”, 3rd ed., McGraw-Hill.

Wolf, P. R. and Ghilani, C. D., 1997, “Adjustment Computations: Statistics and Least Squares in Surveying and GIS”, John Wiley & Sons.

Xie, W., Zhang, Z., Zhang, J., 2004, “Multi-Image Based Camera Calibration Without Control Points ”, The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences,36-41.

Zhan, Z., 2008, “Camera Calibration Based on Liquid Crystal Display(LCD)”, The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, XXXVII( B3b):15-20.

Zhang Z., 1999. “Flexible Camera Calibration by Viewing A Plane from Unknown Orientations”. International Conference on Computer Vision, 666-673.