We have developed an airport monitoring system that traces the movement of airplanes in the parking areas of airports. For this system, we have developed an image processing method, a two-stage normalized background subtraction method that can detect moving objects and determine the sizes of those objects under illumination changes, which are inevitable for outdoor monitoring systems. The two-stage method consists of local and global normalized subtraction. With this method, airplanes can be detected in a stable manner under illumination changes, which means that the brightness in each pixel is not constant due to changes in atmospheric phenomena, such as the shadows of clouds. And false detection problems due to the presence of boarding bridges are solved by utilizing differences in motion between an airplane and the boarding bridge, such as the direction of movement. We have evaluated this method using 140 hours of video images that contain scenes with a variety of conditions, such as the presence of cloud shadows, the turning on and off of lights, night, rainfall and so on. As a result, we have confirmed a 95% level of accuracy of airplane detection. This system is now in operation at Kansai International Airport and is performing most satisfactorily.