Recognition and tracking of target based on three-dimensional joint transform correlation

Classical joint transform correlator (JTC) has been widely used in pattern recognition and target tracking. However, when a real-time three-dimensional (3-D) object is captured as a two- dimensional (2-D) image, the key depth information for discriminating different objects is lost. In some cases, two dissimilar objects may appear to be the same appearance in their 2-D space. In this paper, a novel optical-electrical hybrid JTC is presented by analyzing a series of 2-D projections of the 3-D tested objects from different points of view. After encoding the key depth information into the 2-D power spectrum as the phase factor of the complex amplitude, we can obtain the 3-D joint power spectrum (JPS) and the 3-D joint correlation output, respectively. The presence of the 3-D object and its precise spatial position can be recognized by analyzing the correlation peak. Simultaneously, in order to reconstruct the original target images from the finite discrete spectrum, the space parameters of the system are founded based on discussing the relation between the number of the 2-D projections and the quality of the correlation output. Furthermore, the way to overcome the shortcomings in the correlation output, such as a low correlation peak, a low peak-to-sidelobe ratio and a wide correlation peak width, are discussed. The simulation result shows that the proposed method is effective for recognition and tracking the targets distributed in 3-D space.