Study Of Biological Vision Model For Automatic Target Recognition Technology

ATR (Automatic Target Recognition) is one of the tough challenges in the research of the world military technology nowadays, in which the computer vision technology has been applied. However, many visual missions such as edges detection, spatial location estimation and target tracking, which seem to be very simple in biological vision, are unable to be solved well now in computer vision. It leads to the bottleneck for the improvement on ATR. This doctoral dissertation is based on the project named Research and Simulation on the Algorithm of Automatic Target Recognition Based on the Model of Biological Vision. And the project is supported by the Foundation of Astronomic Technology in 2003. In this paper the improvement on the model of the receptive field in the system of biological vision is presented. With the improved model being used, several key technologies such as edges detection and target tracking in ATR are focused in this paper. The main parts are as follow:(1) Based on the widely learning of references, several representative types of classical and non-classical model of receptive field even the improvement on the models are discussed. Each improvement corresponds to a mechanism in biological visual. And the mechanism that when we keep our eyes on the optical intensity changes in given direction for a long time, the eyes are sensitive to the optical intensity change in the direction is interesting. But we can find that neither the classical receptive field which has the construction of concentric circles nor its improvement can explain the mechanism. Then an anisotropic stretch receptive field model which has arbitrary direction is put forward.(2) The new model of receptive field is applied to explain the phenomenon on the simultaneous contrast in biological vision successfully. Then the mathematical model that can describe the mechanism of the simultaneous contrast is constructed. After the analysis of the feasibility that applying the mathematical model to high-pass filtering on theory and in practice, two algorithms named A New Anisotropic High-pass Filtering Algorithm Based on Region Angle Searching and An Improved Edge's Orientation Estimation Algorithm are proposed respectively.(3) The new model of receptive field is applied to explain the phenomenon on the gazing in biological visual system successfully. According to the mechanism that the Short-Term Synaptic Plasticity caused by repeating stimulation can lead to distortion in receptive fields of neurons in human vision system, a hypothesis on the manner of distortion in receptive fields is proposed in this paper. Based on the hypothesis, the mathematical model that can describe the mechanism of the gazing is constructed. A new algorithm named An Edge Detection Algorithm Based on Short-term Synaptic Plasticity in Gazing Mechanism in Human Visual System is advanced in order to verify the rationality of the hypothesis. Finally an adaptive linear filtering algorithm is established.(4) The new model of receptive field is also applied to motion estimation in this paper. The new concept called virtual edge and its mathematical definition are presented. The new receptive field model can be used as a function to detect the virtual edge with target's moving. With the small target being inducted to the events of motion, the ideal model of temporal difference detection function and the actual one are brought forth. With the analysis of the characteristics of the two models, a rational strategy about parameters chosen is determined. Then a motion estimation algorithm based on the temporal difference detection function is proposed.(5) Several new modules are designed to solve the problems such as error correction on directions, the feasibility and the real-time performance in target tracking. Combined the proposed motion estimation algorithm with the several modules above, a new algorithm based on the temporal difference detection function is put forward. The experiments show that the small target which is moving at random on simple and complex backgrounds can be tracked effectively. The analysis and the comparison of the algorithm's complexity are also completed at last.Finally, the main contributions in this dissertation are summarized and some suggestions and directions for the future work in this field are given.