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Calibration Method for Mapping Camera Based on a Precise Grouped Approach Method
Zheng, L. N.; Yuan, G. Q.; Leng, X.; Wu, Y. F.
2018
发表期刊International Journal of Pattern Recognition and Artificial Intelligence
ISSN0218-0014
卷号32期号:11页码:12
摘要This paper introduces a new calibration method for the mapping camera called Precise Grouped Approach Method (PGAM). The conventional calibration method for the mapping camera is the exact measuring angle method. The accuracy of this method can be reduced by theoretical uncertainties and the number and distribution of observation points. PGAM is able to overcome these disadvantages and improve the accuracy. Firstly, we reduce the theoretical uncertainties by means of a grouped approach method, which rectifies the high-precision rotation stage to zero position. Secondly, a weighted theory is applied to eliminate the effect of the number and distribution of observation points. Finally, the accuracy of PGAM is analyzed. The experiment result shows that the calibration accuracy is significantly improved when using the proposed PGAM algorithm, compared to the conventional one under the identical experimental condition.
关键词PGAM mapping camera calibration exact measuring angle method weighted theory machine vision metrology Computer Science
DOI10.1142/s0218001418550194
收录类别SCI ; EI
引用统计
文献类型期刊论文
条目标识符http://ir.ciomp.ac.cn/handle/181722/60922
专题中国科学院长春光学精密机械与物理研究所
推荐引用方式
GB/T 7714
Zheng, L. N.,Yuan, G. Q.,Leng, X.,et al. Calibration Method for Mapping Camera Based on a Precise Grouped Approach Method[J]. International Journal of Pattern Recognition and Artificial Intelligence,2018,32(11):12.
APA Zheng, L. N.,Yuan, G. Q.,Leng, X.,&Wu, Y. F..(2018).Calibration Method for Mapping Camera Based on a Precise Grouped Approach Method.International Journal of Pattern Recognition and Artificial Intelligence,32(11),12.
MLA Zheng, L. N.,et al."Calibration Method for Mapping Camera Based on a Precise Grouped Approach Method".International Journal of Pattern Recognition and Artificial Intelligence 32.11(2018):12.
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