Low Snr Images Of Multiple Moving Targets Real-time Identification And Applications

Firstly, the process of classifying, system design and application of pattern recognition are summarized in this thesis. The difficulties in recognizing several moving objects in real-time images with low SNR are analyzed. And then the research contents as well as resolution are both explained with emphases.Next, the three saving methods for image segmentation results, the traditional technologies of image segmentation based on edge, boundary and region, together with several common color spaces are introduced. Later on, after elaborating the disadvantages of the old methods in detecting and recognizing moving objects, a series of corresponding approaches are proposed, such as grid scan, local tracking bug and dynamic window in object tracing to reduce the huge data needed to be processed, maximum and minimum for selecting a proper segmentation threshold and improved conversion from RGB model to HSV and so on to decrease the influence of inhomogeneous lighting and the color noise, a bilinear interpolation in each quadrant to eliminate the bad effect on the recognition precise because of the distortions of the camera.After that, much emphasis is given on application study in pattern recognition with a feed-forward neural network. Both the basic BP algorithm and improved BP algorithm in the study process are described in detail, and the later is used to quicken convergence speed and improve validity of the network. According to the above-mentioned introduction, the author has designed a recognition system of moving objects based on BP neural network and experimental results are showed.Finally, as RoboCup is an applied example of this project, the learning background, strategy significance and the applied foreground in our daily life and military affairs of the robotic soccer system are summarized in this thesis. After introducing of the three control constructions in robotic soccer system and comparing with each other, we pointed out the half-independent robotic soccer system is more appropriate to be ourstudy platform. The analysis of the principle and function of each component in this kind of system and the whole process of how to carry out the vision software system from the input image to the information of robots and ball and the ways in a second development of the frame grabber on the Windows system platform are both perfectly described. This will make a great help to those who do a study in real-time image processing.