The analysis of aerial sequential image is of significant importance to estimating the flight path of the unmanned air vehicle. In condition that there is no proiri knowledge on the model and the scenes in the aerial sequential images change continuously

first the images are filtered because of a large amount of noise. Second

the image is segmented into regions by analysis of the gray histogram

then the edge elements covered by the segmented regions are extracted by the improved Canny operator. In order to extract the model effectively

the concept of region feature comparison factor is proposed. Furthermore

the approach based on this concept to extract the suitable model is presented. And

due to robustness and low computational complexity of the matching method based on the hausdorff distance

it is used to resolve the model tracking in each frame of sequential images. Simultaneously

the model is updated in the process of the tracking on account of the model degradation in the aerial sequential images. In addition

on the basis of the projection principle of the camera

it is analyzed how to estimate the flight path of the unmanned air vehicle via the motion of the model in the aerial sequential images. After an experiment using the real aerial sequential images

it is demonstrated that the model extraction and tracking approach is feasible. It provides the foundation for the estimation of flight path of the unmanned air vehicle by use of the aerial image sequence.