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논문검색

Research on Robustness Tracking of Maneuvering Target for Bionic Robot

초록

영어

In order to improve vision tracking quality of the bionic robot, the new automatic tracking algorithm system is proposed in this paper. Base on design of FPGA image acquisition system, the scene noise is removed by adaptive wiener filtering. Aiming at the problem of ROI region extraction in the scene, the seed pixel is selected with background subtraction, orderly, the neighborhood point is judged, the label of the primary selection seed is calibrated. The scene image segmentation algorithm is proposed based on snake model. The matching process is to find the maximum optimization process of the similar function, and the gradient drop method is adopted in mean shift algorithm. Extended kalman filtering is used to realize the robustness state estimation and prediction of the target tracking system. The results given by tracing experiment indicate that the proposed detailed algorithm is effective for partial loss of maneuvering target.

목차

Abstract
 1. Introduction
 2. FPGA Image Acquisition System
 3. Wiener Filtering Algorithm
 4. Region Growing Algorithm
 5. Snake Model
 6. The Mean Shift Iteration Algorithm
 7. Extended Kalman Filter
 8. Experiment and Analysis
 9. Conclusions
 References

저자정보

  • Wang Peng School of Mechanical and Power Engineering, Harbin University of Science and Technology, Harbin, China
  • Wu Jian School of Mechanical and Power Engineering, Harbin University of Science and Technology, Harbin, China
  • Zhang Yuan School of Mechanical and Power Engineering, Harbin University of Science and Technology, Harbin, China
  • Li Jixiang College of Automation, Harbin University of Science and Technology, Harbin, China
  • Zhang Peng College of Automation, Harbin University of Science and Technology, Harbin, China

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