We present a method for detecting shadows and changes of manmade objects based on background model.Original object detection method based on background model assumes that image pixels of nature background can be modeled as a Gaussian distribution

however regions containing man-made objects do not match with this model.So objects can be detected from the nature background.Our tests proved this background model is not applicable to medium scale aerial photos because in that scale man-made objects take up more percentages in the image and cannot be reqarded as a tail in Gaussian distribution.This paper improves the background model

and treats both nature and man-made objects as background

and shadows as detection objects.Using this model

we firstly detect object’s shadows from anomaly of Gaussian distribution and use some filter operators to eliminate those shadows not from man-made objects.Our tests proved that the detection effect of man-made object’s shadows is quite impressive.Then the original images were compensated using the shadow images.After compensating

we got images without shadows.At last change detection was made base on those compensating images.For convenience of the experiment

images were partitioned into several areas of interest（AOI）

and coarse matching of counterpart AOIs of old and new images was made.And then we detected man-made objects’ shadows in AOIs

and those containing man-made objects are remained and those shadows detected will be considered as man-made objects information and be discarded.Then we compensated the AOIs with shadows detection images

and used difference change detection method to compare these AOIs and got the final change detection results.Our tests used aerial images taken at the year 2000 as old images

whose scale is 1∶8000

and aerial images taken at the year 2002 as new images

whose scale is 1∶15000.Experiment results prove our method is effective.