In order to detect motion object, a moving object detection method based on adaptive threshold and Principal Components Analysis (PCA) is presented. First, a set of images of the static environment without motion object is captured to obtain the transformation matrix that used in PCA. By means of this matrix, the successive images are projected in the transformation space. On the contrary, the transformed image can also be recovered using inverse transformation. By evaluating the Euclidean distance between the original and recovered images, the motion detection is performed. The image regions whose Euclidean distance is greater than a threshold is considered like belonging to motion objects. By dynamically adjusting threshold, the algorithm can obtain the adaptive threshold that compensates to a great extent, illumination and other environmental conditions variations. The experimental results show that, the method has better robustness and effectiveness.