关键词: 图像目标识别, 数据融合, DS证据理论, 序列图像, BP神经网络

Abstract: It is much difficult to recognize a 3D target just based on a single 2D target image because of the multivocal information. In this paper, 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 inputed 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 aircrafts quickly and accurately. Besides this, this method has strong robustness to a priori parameter and the attitude variety of aircraft images.

Key words: image recognition, data fusion, DS evidence reasoning, sequential image, BP neural network