以攝影機量測真實世界物體的過程中，直接面臨的問題就是攝影機鏡面所造成的成像扭曲，攝影機模型的參數未知，以及照度的大小等問題，這些因素皆會影響到量測的結果。欲利用攝影機進行電腦視覺量測時，首先要進行的第一步便是攝影機參數校正。對於尚未進行攝影機校正之前的電腦視覺系統而言，是無法辨別物體真正大小，甚至連相對大小都無法辨識。而在攝影機經過校正後，將求得的參數代入攝影機的數學模型中，並藉著影像平面上所得到的影像座標，即可求出真正物體的世界座標，進一步進行計算真正尺寸的工作。
傳統不可變焦式攝影機校正量測中，對於物件過大會導致物件無法完全入鏡，或物件過小而造成量測不易的問題，將可藉由改變焦距參數來克服此問題。針對於不可變焦的攝影機校正部份，本研究以Zhang在1999年所提出的方法為基礎進行校正。而本研究加入光學參數中影響物體倍率與解析度的「焦距參數」作一系統化的模型與討論，並將此參數獨立於Zhang式校正模型之中，而後對不同倍率下的物體作一實際上的量測，也證明改變焦距參數對於改善誤差有相當明顯的提昇。最後，我們並對初始焦距位置選擇與光圈對於量測精確度的影響，做一討論與比較。

In the process of using a digital camera to measure real word objects, the problems we face directly are radial lens distortion, unknown camera model parameters, and gauge of illumination.All those problems will affect the measurement results. When we want to use a digital camera to measure objects, the first step we need to do is to calibrate camera parameters. For an un-calibrated camera computer vision system, it couldn’t measure the real size or even the comparative size of objects. After completing camera calibration, we can obtain the parameters from calibration. With the object image coordinates, we can calculate the real size of the objects.
　　In the traditional measurement of non-zoom camera calibration, the objects can’t be measured or with difficulties in it if the objects are out of the view or the objects are too small to see. We can overcome this problem with changing the focal length parameter. For the non-zoom camera calibration, we use the Zhang method as basis that he putted forth in 1999. In this dissert, we discuss the focal length parameter and systematize it in the calibration model. We separate the focal length parameter from the Zhang calibration camera model, and measure the object size in many different focal lengths. We will prove that it can improve the measurement error when we change the focal length. Finally, we discuss iris and the initial focal length effect to the measure error.

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