A Self-Adaptive Parameter Optimization Algorithm in a Real-Time Parallel Image Processing System
Aiming at the stalemate that precision, speed, robustness, and other parameters constrain each other in the parallel processed vision servo system, this paper proposed an adaptive load capacity balance strategy on the servo parameters optimization algorithm (ALBPO) to improve the computing precision...
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| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
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Wiley
2013-01-01
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| Series: | The Scientific World Journal |
| Online Access: | http://dx.doi.org/10.1155/2013/978548 |
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| author | Ge Li Xuehe Zhang Jie Zhao Hongli Zhang Jianwei Ye Weizhe Zhang |
| author_facet | Ge Li Xuehe Zhang Jie Zhao Hongli Zhang Jianwei Ye Weizhe Zhang |
| author_sort | Ge Li |
| collection | DOAJ |
| description | Aiming at the stalemate that precision, speed, robustness, and other parameters constrain each other in the parallel processed vision servo system, this paper proposed an adaptive load capacity balance strategy on the servo parameters optimization algorithm (ALBPO) to improve the computing precision and to achieve high detection ratio while not reducing the servo circle. We use load capacity functions (LC) to estimate the load for each processor and then make continuous self-adaptation towards a balanced status based on the fluctuated LC results; meanwhile, we pick up a proper set of target detection and location parameters according to the results of LC. Compared with current load balance algorithm, the algorithm proposed in this paper is proceeded under an unknown informed status about the maximum load and the current load of the processors, which means it has great extensibility. Simulation results showed that the ALBPO algorithm has great merits on load balance performance, realizing the optimization of QoS for each processor, fulfilling the balance requirements of servo circle, precision, and robustness of the parallel processed vision servo system. |
| format | Article |
| id | doaj-art-b368ccd10d8d4ac2b9d9e2d6d0db6e32 |
| institution | Kabale University |
| issn | 1537-744X |
| language | English |
| publishDate | 2013-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | The Scientific World Journal |
| spelling | doaj-art-b368ccd10d8d4ac2b9d9e2d6d0db6e322025-08-20T03:39:21ZengWileyThe Scientific World Journal1537-744X2013-01-01201310.1155/2013/978548978548A Self-Adaptive Parameter Optimization Algorithm in a Real-Time Parallel Image Processing SystemGe Li0Xuehe Zhang1Jie Zhao2Hongli Zhang3Jianwei Ye4Weizhe Zhang5State Key Laboratory of Robotics and System, Harbin Institute of Technology, No. 2, Yikuang Street, Harbin 150001, ChinaState Key Laboratory of Robotics and System, Harbin Institute of Technology, No. 2, Yikuang Street, Harbin 150001, ChinaState Key Laboratory of Robotics and System, Harbin Institute of Technology, No. 2, Yikuang Street, Harbin 150001, ChinaSchool of Computer Science and Technology, Harbin Institute of Technology, No. 92, West DA-Zhi Street, Harbin 150001, ChinaSchool of Computer Science and Technology, Harbin Institute of Technology, No. 92, West DA-Zhi Street, Harbin 150001, ChinaSchool of Computer Science and Technology, Harbin Institute of Technology, No. 92, West DA-Zhi Street, Harbin 150001, ChinaAiming at the stalemate that precision, speed, robustness, and other parameters constrain each other in the parallel processed vision servo system, this paper proposed an adaptive load capacity balance strategy on the servo parameters optimization algorithm (ALBPO) to improve the computing precision and to achieve high detection ratio while not reducing the servo circle. We use load capacity functions (LC) to estimate the load for each processor and then make continuous self-adaptation towards a balanced status based on the fluctuated LC results; meanwhile, we pick up a proper set of target detection and location parameters according to the results of LC. Compared with current load balance algorithm, the algorithm proposed in this paper is proceeded under an unknown informed status about the maximum load and the current load of the processors, which means it has great extensibility. Simulation results showed that the ALBPO algorithm has great merits on load balance performance, realizing the optimization of QoS for each processor, fulfilling the balance requirements of servo circle, precision, and robustness of the parallel processed vision servo system.http://dx.doi.org/10.1155/2013/978548 |
| spellingShingle | Ge Li Xuehe Zhang Jie Zhao Hongli Zhang Jianwei Ye Weizhe Zhang A Self-Adaptive Parameter Optimization Algorithm in a Real-Time Parallel Image Processing System The Scientific World Journal |
| title | A Self-Adaptive Parameter Optimization Algorithm in a Real-Time Parallel Image Processing System |
| title_full | A Self-Adaptive Parameter Optimization Algorithm in a Real-Time Parallel Image Processing System |
| title_fullStr | A Self-Adaptive Parameter Optimization Algorithm in a Real-Time Parallel Image Processing System |
| title_full_unstemmed | A Self-Adaptive Parameter Optimization Algorithm in a Real-Time Parallel Image Processing System |
| title_short | A Self-Adaptive Parameter Optimization Algorithm in a Real-Time Parallel Image Processing System |
| title_sort | self adaptive parameter optimization algorithm in a real time parallel image processing system |
| url | http://dx.doi.org/10.1155/2013/978548 |
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