Automatic target recognition method based on sequential images

It is much difficult to recognize a 3D target just based on a single 2D target image because of the multivocal information. An automatic target recognition method based on sequential 2D images is proposed. Firstly, the modified Hu invariant moments are used as the invariant characteristic vectors, which are further inputted to a back-propagation neural network (BPNN) classifier. Then the BPNN classifier gives the primary recognition result, which is combined with the training error to achieve the basic belief assignment (BBA). Finally, a revised Dempster-Shafer (DS) reasoning method named absorption method, which can deal with high conflicting evidences, is applied to implement the final reasoning decision. The simulation based on multiple aircraft images with various attitudes demonstrates that the proposed method can recognize the air-crafts quickly and accurately. Besides this, this method has strong robustness to a priori parameter and the attitude variety of aircraft images.